... Figura 6: Interacciones de la radiación con la atmosfera y la tierra Fuente: (Lillesand, Kiefer, & Chipman, 2004) La energía reflejada ocurre cuando la radiación rebota en el objetivo y es redirigida. La absorción resulta cuando la energía es absorbida dentro del objetivo. ...

... La forma geométrica en que el objetivo refleja la energía es también una importante consideración (Lillesand, Kiefer, & Chipman, 2004). La superficie de la tierra es rugosa lo que provoca una reflexión diferente dependiendo de la situación, de esta manera cuando la superficie tiende a ser plana la reflexión es especular generándose un ángulo de incidencia igual al de reflexión. ...

... Como su nombre lo indica, el radar fue desarrollado como medio para detectar la presencia de objetos, distancia, y a veces su posición angular mediante el uso de ondas de radio. Este proceso implica la transmisión de ráfagas cortas, o pulsos de energía de microondas en la dirección de interés, registrando así la fuerza y el origen de ecos o reflejos recibidos desde el campo de visión del sistema (Lillesand, Kiefer, & Chipman, 2004). Según Lillesand (2004) las principales carácteristicas de este sensor activo es que es capaz de penetrar la atmósfera bajo prácticamente cualquier condición, así, dependiendo de la longitud de onda en acción, la energía de microondas puede traspasar la neblina, la lluvia ligera, nieve, nubes, y humo. ...

  • Sergio Andrés González Sergio Andrés González

Los humedales a nivel mundial y nacional han sido objeto de una presión constante de distintos usos de suelo que ha provocado una pérdida significativa de su superficie, por esta razón, y considerando la importancia de los servicios ecosistémicos que estos proveen, se debe estudiar constantemente su estado actual. La nueva posibilidad que ostentan las recientes imágenes gratuitas multiespectrales Sentinel 1 y de radar Sentinel 2, sumado a nuevos enfoques de clasificación supervisada (enfoque por objetos, OBIA), permite abordar esta problemática desde una nueva perspectiva. El caso de humedales marismas de la región del Bío Bío, como los humedales Rocuant-Andalién, Lenga, y Tubul Raqui, serán incorporados al estudio para principalmente obtener las superficies de las morfologías internas presentes en estos. Finalmente, el resultado es la comparación (evaluación del desempeño) de los enfoques tradicional por pixel y enfoque por objetos, que nos permitirá evaluar su utilización. Los resultados permiten afirmar la mejora en los porcentajes de desempeño del clasificador mediante el enfoque por objetos debido a que hay una mejora en el promedio de 15% para la fiabilidad global de las Cubiertas de Usos de Suelo (CUS), y un 3% de la fiabilidad global de las Morfologías internas de los Humedales (MIH) mediante el uso de OBIA-Random Forest.

... Multispectral strategy is the basis for using remote sensing to differentiate between land cover types [12]. This approach is a significant instrument for the production, tracking and management of natural resources [13,14]. Satellite data is a great tool for preparing geological maps, even for mountainous geological territories, because of its low implementation costs and duration variations in construction relative to traditional methods [15]. ...

... Remote sensing is the art of collecting, processing and describing images that record the cooperation between electromagnetic energy and matter [13,14]. Land, soil, climate, topographical parameters can be employed by the integration of GIS and remote sensing for spatiotemporal variations in Earth observation and all-natural resources applications (Fig. 2). ...

... Land, soil, climate, topographical parameters can be employed by the integration of GIS and remote sensing for spatiotemporal variations in Earth observation and all-natural resources applications (Fig. 2). The use of remotely sensed data in Earth observation and all-natural resources applications is a modern and advanced approach that helps monitor all environmental phenomena involved in the agricultural development process, water bodies and reservoirs, eventually helping obtain results that provide a predictive view of the resource status and the possibility of building and adopting appropriate policies [13]. ...

The Iraqi marshlands in Mesopotamia are considered a major landmark of world heritage and a main feeding and rest destination for bird breeding. The marshes of Iraq have been subjected to intentional desiccation and desertification several times. Detecting the water content of major Iraqi marshlands is the main scope of this study. Satellite imagery can be employed to assemble the data required for water, vegetation and dry area evaluation in marshlands. The assessment was performed using the adaptive technology of supervised classification that depends on the shade of each object's colour. Several types of Landsat satellite, MSS, TM, ETM+ and OLI/TIRS and 64 satellite images were used to fulfil the objective. Results show that the classification of visual variations is the most suitable economical approach to detecting various environmental changes amongst the common methods. The 48 years in the marshes of Iraq (1972–2020) can be represented in two main stages. The increasing tendency in the second stage is nearly double the decreasing tendency in the first stage. The surface area in the first stage deteriorated dramatically until it reached the lowest level of approximately 432 km2 in 2000 due to water encroachment and desiccation. Then, the area started to increase over time to approximately 4335 km2 in the second stage towards the year 2020, except for sudden declines in 2015 and 2018. The average water surface for the first and second stages were 1877 and 2012 km2, respectively.

... Remote sensing (RS) is the science and art of obtaining information about an area, phenomenon or object through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation [4]. RS systems measure the emitted or reflected energy from the Earth's surface using a sensor mounted on an aircraft or a spacecraft platform. ...

... RS data can be used in environmental monitoring programs where the objective is to monitor changes in surface phenomena over time [7]. Digital spatial data analysis and mapping; RS and GIS are widely applied in environmental and natural resources monitoring [4]. ...

... Land cover refers to the physical attributes of Earth's surface; captured in the distribution of water, vegetation and soil other physical characteristics of the land, as well as those made by human exercises e. g., built ups [22]. While, land use refers to the human activities or economic function related to a particular piece of land [4]. The general term used for alteration of terrestrial surface by human is the land use and land cover change (LULCC). ...

Coastlines mapping techniques or the coastline automated analyses have been sought after. In practice, various sorts of seacoasts, for example, biological, silty, arenaceous, artificial, and bedrock coasts, have their own attributes, which force various degrees of intricacy on coastline mapping. As an extraordinary kind of complex artificial coast, aquaculture coast is shaped by the farming of aquatic organisms on silt tidal flats. With the rapid growth of coastal aquaculture in recent years, aquaculture coasts have increased in some developing countries. It has been estimated that aquaculture coasts constitute about 30% of all coastlines in mainland China. In order to identify, monitor, model, and manage the vast expanse of coastal aquaculture, effective methods of extracting aquaculture coastlines from remotely sensed imagery are desired. Secondly, with the rapid economic development in coastal areas, the development of coastal zone resources is also increasing day by day, which benefits the development of island coastal zone. Using oneself has become an important link in the development of marine economy. Due to the limited coastal resources and low environmental carrying capacity, the overexploitation and utilization of coastal resources will lead to a series of problems, such as coastal erosion, coastal migration and accumulation, island area reduction, etc., Both man-made activities and natural factors will lead to coastline changes, which will lead to corresponding changes in coastal ecological environment, thus affecting the coordinated development of coastal economy and the survival of coastal residents. Therefore, efficient, accurate and timely acquisition of coastline information and research on the spatial-temporal changes of coastline are of great significance to the protection of the living environment of coastal residents, the effective development of island and coastal resources, the coordination of sustainable economic development in coastal areas and the mitigation of marine disasters. This paper presents a review of those papers reporting coastline extraction and land use and land cover (LULC) change analysis using remote sensing (RS) and geographic information system (GIS) technology.

... By analysis of atmospheric photographs, where the analysis is used to perform the equation between image and image and detect the change zones. (Wright, Lillesand, & Kiefer, 1980) [2] To detect the variable after analysis, two different dates are categorized independently. The area of change is then extracted by a direct comparison of the categorization results (Duro, 2012) [3]. ...

... By analysis of atmospheric photographs, where the analysis is used to perform the equation between image and image and detect the change zones. (Wright, Lillesand, & Kiefer, 1980) [2] To detect the variable after analysis, two different dates are categorized independently. The area of change is then extracted by a direct comparison of the categorization results (Duro, 2012) [3]. ...

  • Nawfal S. Abd-Alwahab
  • Nawal K. Ghazal

The technology of change detection is a technique by which changes are verified in a certain time period. Remote sensing images are used to detect changes in agriculture land for the selected study area located south of Baghdad governorate in Agricultural Division of AL-Rasheed district because this method is very effective for assessing change compared to other traditional scanning techniques. In this research two remotely sensed images for the study area were taken by Landsat 8 and Sentinel-2, the difference between them is one month to monitor the change in the winter crops, especially the wheat crop, where the agriculture began for the wheat crop there in the Agricultural Division of AL-Rasheed district at 15/11/2018. The first preprocessing procedure was the extraction of the NDVI (Normalized Difference Vegetation Index) values for the two scenes of Landsat 8 and the two scenes of Sentinel-2B and then using the change detection between them to compare the changes in agriculture land. Also, change detection was implemented between NIR bands because they are most severely affected by biomass or the amount of available chlorophyll-containing in plant structures. The results of the change detection for Sentinel-2B were more accurate than for the Landsat 8 as demonstrated by field visits for the study area, where the changes in the distribution of vegetal cover (wheat and other winter crops) were clear and accurate in the image of Sentinel-2B, as opposed to Landsat's 8 image, where the variation in vegetation cover was not accurate, especially for the change detection between NIR bands.

... Interpretation is made for the physical properties of objects and phenomena that appear in the image. Level of complexity might be come up while we are interpretating the image from the simplest object recognition on the earth's surface to the origin of the detailed information about the complex interaction between the surface of the earth and under the earth's surface [1]. scanning consists of 8 channels, namely TM1, TM2, TM3, TM4, TM5, TM6, TM7 and TM8, 30 meters of spatial resolution channels 1,2,3,4,5, and 7, while the channel 6 has 60 meters of spatial resolution. ...

... In the satellite image there are several channels that collect and store the information on each wavelength called adjacent layers (bands). The collection of some spectral layers at the same time and area are called multispectral image [1]. . ...

  • Muhammad Ilham Muhammad Ilham
  • Khairul Munadi
  • Sofiyahna Qubro

Remote sensing image quality and the improvement of remote sensing image position accuracy on Landsat ETM satellite is highly needed in term of remote sensing. Therefore, it is required one way or more to obtain the quality and accuracy of the image which uses image processing. Fusion technique is one of the image processing example that is using an existing descriptions to catch the result of image that can provide better information in the content. In this final task, multispectral images have high spectral information content and low spatial, also high spatial information content in panchromatic image that it is needed to do the image fusion in order to have a spectral information content and high spatial to compare the performance of some fusion rules wavelet-based on the multispectral image fusion and panchromatic imagery. The image used is Landsat ETM. The performance of image fusion rules is compared with the mean gradient parameters, mutual information, mean square error and correlation coefficient. Based on the test results, image fusion has an influence on the information content of multispectral imagery and panchromatic imagery, which is the spectral and spatial information content are getting better, the ratio of the 6 image fusion rules have inconsistent values of the three image testings to the mean gradient parameters, mutual information and mean square error and the results of image fusion of the fifth fusion rules on the correlation coefficient have a consistent value of the three image testings.

... Most other remote sensing products typically used within Earth Observation and related data applications that often started in disciplines such as geodesy, geography, ecology or similar, were using multispectral information, not just greyscale visible information. For example, multispectral information such as infrared, or many other wavelengths is preferred in several band combinations to display and help separate land use categories such as vegetation from buildings etc. much better than just black and white images [31]. Therefore, it might be the case that CORONA and similar data are rather underestimated, which might explain the surprisingly low range of publications to be found under search terms such as "CORONA" and "natural hazard" for example (see Appendix A). ...

... One important area is the application of the stereo-optical photographs taken by the CORONA missions. They permit not only visual interpretation with specific hardware viewers known from orthophotography and photogrammetry [31] that adds height information to the observer. This can help to better identify features such as building heights, topography and more. ...

  • Alexander Fekete Alexander Fekete

Open Access: https://www.mdpi.com/2072-4292/12/19/3246 Urban growth and natural hazard events are continuous trends and reliable monitoring is demanded by organisations such as the Intergovernmental Panel on Climate Change, the United Nations Office for Disaster Risk Reduction, or the United Nations Human Settlements Programme. CORONA is the program name of photoreconnaissance satellite imagery available from 1960 to 1984 provides an extension of monitoring ranges in comparison to later satellite data such as Landsat that are more widely used. Providing visual comparisons with aerial or high-resolution OrbView satellite imagery, this article demonstrates applications of CORONA images for change detection of urban growth and sprawl and natural hazard exposure. Cases from El Alto/ La Paz in Bolivia, Santiago de Chile, Yungay in Peru, Qazvin in Iran, and Mount St. Helens in the USA are analysed. After a preassessment of over 20 disaster events, the 1970 Yungay earthquake-triggered debris avalanche and the natural hazard processes of the 1980 Mt St. Helens volcanic eruption are further analysed. Usability and limitations of CORONA data are analysed, including the availability of data depending on flight missions, cloud cover, spatial and temporal resolution, but also rather scarce documentation of natural hazards in the 1960s and 70s. Results include the identification of urban borders expanding into hazard-prone areas such as mountains, riverbeds or erosion channels. These are important areas for future research, making more usage of this valuable but little-used data source. The article addresses geographers, spatial planners, political decision makers and other scientific areas dealing with remote sensing.

... Normalized Difference Vegetation Index (NDVI), and Leaf Area Index (LAI) were calculated by visible and near-infrared bands Lillesand, et al., 2004). For Landsat sensitive indicator of the amount and condition of green vegetation. ...

... - Three commonly used vegetation indices (NDVI, LAI, and SAVI) were computed using the in GRASS-SEBAL. Those indices were used to calculate the outgoing longwave radiation through a function of surface temperature Normalized Difference Vegetation Index (NDVI), and Leaf Area Index (LAI) were calculated by infrared bands (Waters, et al., 2002;Lillesand, et al., 2004). For Landsat-8, NDVI is a sensitive indicator of the amount and condition of green vegetation. ...

Abstract On land, Evapotranspiration (ET) plays an important role in the water cycle and is an important parameter in water resources management. Remote sensing is one of the important sources of data and techniques to estimate many climate elements including evapotranspiration. The estimation based on remote sensing is vital for the management of water resources in the catchment. This study estimated the spatio-temporal variation of evapotranspiration in the lower Gilgel Abay catchment, Lake Tana sub-basin from January to March 2016. The evapotranspiration was quantified using the Surface Energy Balance (SEBAL) algorithm and Landsat 8 imagery with climate data. For this analysis, ASTER GDEM, GRASS-python & reference weather parameters from Bahir Dar weather station were used. Parameters including surface radiance, surface reflectance, surface albedo, NDVI, LAI, surface emissivity, surface temperature, net radiation, soil heat flux, sensible heat flux, and latent heat flux were computed. Consequently, the hourly, daily, monthly and seasonal evapotranspiration in the study area were calculated with SEBAL python. The pixel wise calculation shows that the values of the spatial variation of mean ET varied from 0 mm/day to 7.39 mm/day with a mean value of 4.78 mm/day for 23 December 2016. The computed ET values for the months December to March, the maximum estimated ET over the whole catchment ranged from 6.51 mm/day to 7.82 mm/day. The mean ET ranged from 4.37 mm/day to 4.78 mm/day while the seasonal ET was 539.92 mm for 2016. ET values were computed for different conventional methods using REF-ET software. The value of Standard P-M for the weather station was used as a reference to compare the values obtained from other conventional methods as well as SEBAL method. The mean value of the study area from SEBAL calculation approached the point values of CIMIS penman, standard P-M and Priestly Taylor methods. The analyses are vital from the perspective of water resources management on various surfaces of the earth that need to be understood to achieve sustainable development of water resources in the basin and recommended to apply in the remaining sub-basins in the region. Keywords: Evapotranspiration, Gilgel Abay, GRASS-GIS, Landsat-8, RS, SEBAL.

... Normalized Difference Vegetation Index (NDVI) as obtained from the MODIS sensor (Lillesand et al., 2004) was used as a surrogate for infestation during the simulation. The results showed that the optimum number of points for the entire study area is 72 682 ( Figure 10) using a stratified proportional sample approach (Figures 11 and 12). ...

...  areas with high vegetation activity as obtained from the MODIS derived average NDVI over a five year period (Lillesand et al., 2004)  catchments with more than 50% of remaining natural and semi-natural areas as obtained from National Land Cover (2005)  arid bioregions (Mucina and Rutherford, 2006) were removed  catchments falling within the Kruger National Park were removed  only two quaternary catchments were allowed per tertiary catchment. ...

... Penginderaan jauh sebagai ilmu dan seni untuk memperoleh informasi mengenai objek, area, dan fenomena melalui data yang direkam oleh perangkat tanpa kontak langsung, (Lillesand, Kiefer, & Chipman, 2004). Penginderaan jauh memiliki kemampuan untuk memperoleh data mengenai kondisi permukaan Bumi, misalnya pemetaan tutupan vegetasi dengan menggunakan normalized difference vegetation index (NDVI). ...

Kota Semarang sebagai ibukota provinsi di Indonesia mengalami laju migrasi yang intensif dari desa ke kota. Akibatnya, suhu permukaan lahan (SPL) menjadi semakin panas dan mengarah pada variasi suhu skala lokal dari waktu ke waktu. Tujuan penelitian yaitu 1) menyelidiki distribusi SPL dan tutupan vegetasi di Semarang, dan 2) menginvestigasi kondisi ekologi kota skala mikro yang berkenaan dengan SPL berdasarkan nilai urban thermal field variance index (UTFVI). Landsat 8 digunakan untuk mengekstraksi SPL dan tutupan vegetasi melalui nilai normalized difference vegetation index (NDVI). Selanjutnya, UTFVI diklasifikasikan berdasarkan nilai SPL. Hasil penelitian menunjukkan nilai NDVI yang rendah yang merepresentasikan lahan terbangun dan rumput mayoritas tersebar di bagian utara dan tengah Semarang. Nilai NDVI yang tinggi yang merepresentasikan tutupan vegetasi sebagian besar berlokasi di bagian selatan Semarang. Area yang kondisi ekologisnya buruk hingga paling buruk mayoritas terdistribusi di bagian tengah kota hingga ke arah pesisir di bagian utara. Kecamatan-kecamatan yang perlu diprioritaskan terkait restorasi ekologi adalah kecamatan Ngaliyan, Semarang Utara and Semarang Barat. Penelitian lebih lanjut dapat berfokus pada upaya menemukan pendekatan yang cocok untuk merestorasi degradasi ekologi perkotaan dari aspek suhu.

... Linear features on a satellite image regularly reflect the geological lineaments (faults or fractures) and hydrological structures (river or shoreline) [Lillesand et al., 2004]. The lineaments were extracted from the PCA image to show distinct structural features (including faults, shears and fractures). ...

... Successful identification of crops requires knowledge of the developmental stages of each crop in the area to be inventoried. Because of changes in crop characteristics during the growing season photography from several dates during the growing cycle can by very useful in the interpretation process (Lillesand T.M., 2003) [3] . A cropping system is defined as the cropping pattern and its management to derive benefits from a given resource based under a specific environmental condition. ...

  • Savitpal
  • Vinod Kumar Vinod Kumar
  • M P Sharma
  • Ashok Beniwal

Cropping pattern and crop rotation study including detailed temporal and spatial information, are needed for agriculture sustainable management, crop monitoring and food security issues. The lack of information on agriculture is the major obstacles hampering efficient policy making and research to achieve food security. Cropping pattern analysis was carried out by Geospatial technology aided integration crop inventory information. The land evaluation approach using this technology based integration has been exercised to emphasize the possibility of raising the suitability of different cropping areas for a particular use with good management practices. The study was carried out for analysis cropping pattern and crop rotation by using space based remote sensing data with secondary spatial non-spatial data. The basic primary data used in this study was IRS Resource-Sat (IRS-P6) LISS III data of 2007-08. The cropping pattern and crop rotation of study area were analysed through digital image processing using windows platform of Geomatica Analysis software, ERDAS Imagine and Arc GIS software. This study reveals that rice wheat cropped area is 49 percent and 61 percent of total agriculture area respectively. The each crop like sugarcane, cotton and mustard are less than ten percent area to total agricultural area. This analysis clearly indicating that cropping pattern is in favour of rice wheat with fallow and other crops rotation and increase in crop intensity due to rice & wheat cultivation dominance. However, decrease of area under pulses and oilseed crops have led to decline in crop diversification. This cropping scenario leads to adverse agro ecological effects.

... Zobrazowania lotnicze i satelitarne Ziemi są źródłem cennych informacji o przestrzeni geograficznej. Oferują rozszerzenie analizy poza to co widoczne (Lillesand i in., 2015) dzięki dostępności do kanałów spoza spektrum światła widzialnego i zwiększenie rozdzielczości spektralnej dzięki obrazowaniu hiperspektralnemu. Ich wykorzystanie pozwala na lepsze zrozumienie zjawisk zachodzących w skali makro bez ograniczeń wynikających z tradycyjnych obserwacji w skali lokalnej (Tang i in., 2009). ...

  • Maciej Adamiak Maciej Adamiak

Zastosowanie uczenia maszynowego (ML, ang. machine learning) oraz uczenia głębokie-go (DL, deep learning), zwłaszcza głębokich konwolucyjnych sieci neuronowych (DCNN, ang. deep convolutional neural network), w przetwarzaniu oraz interpretacji obrazu jest obecnie szeroko omawianym zagadnieniem wśród przedstawicieli aktywnie rozwijającego się środowiska naukowego skupionego w ramach takich dziedzin jak teledetekcja oraz geoinformacja. Niniejsza publikacja jest próbą usystematyzowania wiedzy dotyczącej DL oraz jego zastosowania we wspomaganiu interpretacji przestrzeni geograficznej na podstawie zobrazowań lotniczych i satelitarnych. Przeglądem zagadnień DL zainteresowani będą przede wszystkim geografowie, którzy chcieliby wzbogacić prowadzone badania naukowe o metody oparte o sztuczne sieci neuronowe. W tekście przedstawione zostały główne koncepcje DL oraz metody wraz z przykładowymi kategoriami zadań, które można zrealizować przy ich pomocy. Mowa o semantycznej segmentacji, klasyfikacji, augmentacji materiału badawczego i inżynierii cech. Prezentacja każdej z tych kategorii została wzbogacona o opis przypadku użycia i przegląd literatury, umożliwiając w ten sposób wykonanie pierwszego kroku ku zastosowaniu danej techniki w przyszłych projektach badawczych. Zakończenie artykułu stanowi dyskusja nad nowymi kierunkami rozwoju DL w ramach dyscypliny nauk o Ziemi i środowisku.

... Google satellite image available in open source software QGIS 3.14 was used to prepare land use land cover map (LULC) of the study area.Various scene elements like tone, texture, shape, size and association were considered during image interpretation. Ground truth data were collected to confirm various land use classes [17]. The slope map was derived from 10m CartoDEM generated under SISDIP project for Meghalaya at North Eastern Space Applications Centre (NESAC). ...

Land use planning based on soil, slope, existing land use land cover and knowledge of the ecology and socio- economy was done for micro watershed 3B2A1d2d of Digaru watershed located in Meghalaya. High resolution Google image was used to prepare present land use land cover map. Areas suitable for rice, maize and pineapple were identified using geospatial technology based on land evaluation using information on soil, slope, rainfall and temperature and requirements of crops. Alternate land use plan was prepared based on crop suitability and existing land user. The study reveals that soils are high in organic carbon and nitrogen, moderately acidic in reaction and medium in phosphorus and potassium. Soils are sufficient in iron and copper. Zinc and manganese is deficient in 21.88% and 3.92% area. Crop suitability analysis reveals that only 57 ha area is suitable for rice and 144 ha area is suitable for maize and pineapple. Based on crop suitability, low lying areas are suggested for rice and maize and pineapple is suggested on uplands. Areas not suitable for any crop are suggested for afforestation. Keywords: Geospatial tools; Soil fertility; Crop suitability; Meghalaya

... Linear features on a satellite image regularly reflect the geological lineaments (faults or fractures) and hydrological structures (river or shoreline) [Lillesand et al., 2004]. The lineaments were extracted from the PCA image to show distinct structural features (including faults, shears and fractures). ...

  • Sichugova Lola Sichugova Lola
  • Dilbarkhon Fazilova

This work presents the results of lineaments interpretation using the automated method of the satellite images in the territory of the Charvak water reservoir in Uzbekistan. Tectonic and local (water impoundment in Charvak reservoir) features of the region deformation were determined on base LINE algorithm in software PCI Geomatica. The thematic map with the geospatial arrangement of lineaments was constructed on base of satellite images LANDSAT-8 processing. We concluded that water level fluctuations have a greater influence on the appearance of the lineaments structure than periods of water filling and downstream in the reservoir. Lineament density maps showed dominantly increased density towards the north-southern direction is due to tectonic features of the region and the west-eastern direction is due to water level fluctuations in the reservoir. The lineaments density maps for summer-autumn periods showed the faults arising from water level fluctuations only. Winter-spring period affected with high influence of the seasonal (snow pack, rainfall) processes as well.

... Limestone is a significant resource available in Pakistan [1] and is used to produce cement, concrete, road base, and dimension stone products [2]. Since conventional exploration/prospecting practices are costly, time-consuming, are limited by physical access to hilly terrains, and prone to accumulating errors, remote sensing has been widely utilized in lithological/geological mapping [3][4][5][6][7][8][9][10]. Most minerals respond to near infrared (NIR), shortwave infrared (SWIR), and thermal infrared (TIR) wavelengths [11][12][13]. ...

Low-resolution Geological Survey of Pakistan (GSP) maps surrounding the region of interest show oolitic and fossiliferous limestone occurrences correspondingly in Samanasuk, Lockhart, and Margalla hill formations in the Hazara division, Pakistan. Machine-learning algorithms (MLAs) have been rarely applied to multispectral remote sensing data for differentiating between limestone formations formed due to different depositional environments, such as oolitic or fossiliferous. Unlike the previous studies that mostly report lithological classification of rock types having different chemical compositions by the MLAs, this paper aimed to investigate MLAs' potential for mapping subclasses within the same lithology, i.e., limestone. Additionally, selecting appropriate data labels, training algorithms, hyperparameters, and remote sensing data sources were also investigated while applying these MLAs. In this paper, first, oolitic (Samanasuk), fossiliferous (Lockhart and Margalla) limestone-bearing formations along with the adjoining Hazara formation were mapped using random forest (RF), support vector machine (SVM), classification and regression tree (CART), and naïve Bayes (NB) MLAs. The RF algorithm reported the best accuracy of 83.28% and a Kappa coefficient of 0.78. To further improve the targeted allochemical limestone formation map, annotation labels were generated by the fusion of maps obtained from principal component analysis (PCA), decorrelation stretching (DS), X-means clustering applied to ASTER-L1T, Landsat-8, and Sentinel-2 datasets. These labels were used to train and validate SVM, CART, NB, and RF MLAs to obtain a binary classification map of limestone occurrences in the Hazara division, Pakistan using the Google Earth Engine (GEE) platform. The classification of Landsat-8 data by CART reported 99.63% accuracy, with a Kappa coefficient of 0.99, and was in good agreement with the field validation. This binary limestone map was further classified into oolitic (Samanasuk) and fossiliferous (Lockhart and Margalla) formations by all the four MLAs; in this case, RF surpassed all the other algorithms with an improved accuracy of 96.36%. This improvement can be attributed to better annotation, resulting in a binary limestone classification map, which formed a mask for improved classification of oolitic and fossiliferous limestone in the area.

... Passive microwave depends on the physical temperatuSre and surface emissivity of the earth's surface. In principle, passive sensors, like radiometers, measure the thermal emission of the surface at the microwave wavelength, and translate that energy to brightness temperature [16,17]. ...

A continuous spatio-temporal database of accurate soil moisture (SM) measurements is an important asset for agricultural activities, hydrologic studies, and environmental monitoring. The Advanced Microwave Scanning Radiometer 2 (AMSR2), launched in May 2012, has been providing SM data globally with a revisit period of two days. It is imperative to assess the quality of this data before performing any application. Since resources of accurate SM measurements are very limited in Puerto Rico, this research will assess the quality of the AMSR2 data by comparing with ground-based measurements and perform a downscaling technique to provide a better description of how the sensor perceives the surface soil moisture as it passes over the island. The comparison consisted of the evaluation of the mean error, root mean squared error, and the correlation coefficient. Two downscaling techniques were used and their performances were studied. The results revealed that AMSR2 products tend to underestimate. This is due to the extreme heterogeneous distributions of elevations, vegetation densities, soil types, and weather events on the island. This research provides a comprehensive study on the accuracy and potential of the AMSR2 products over Puerto Rico. Further studies are recommended to improve the AMSR2 products.

... The BPF comprises multilayered thin films that are attached on a subtract such as glass [32]. In a comparison with other spectroscopic techniques, NDIR has low energy consumption, because IR sources with wavelengths in the range of 1-15 µm can operate at a lower temperature than other sources [35]. ...

Carbon dioxide (CO2) is an indicator of indoor air quality. Ventilation based on the use of a CO2 indicator helps to prevent people from acquiring many diseases, especially respiratory viral infections. Therefore, the monitoring of CO2 is a pivotal issue in the control of indoor air quality. A nondispersive infrared (NDIR) analyzer with a wide range of measurements (i.e., ppmv to percentage levels) was developed for measuring carbon dioxide (CO2) in an indoor environment. The effects of optical pathlength and interfering gases were investigated. The pathlengths of the analyzer were varied at 4.8, 8, 10.4 and 16 m, and the interference gases were CO; NO2; SO2; H2O; BTEX (i.e., benzene, toluene, ethylbenzene and m-/p-xylene) and formaldehyde. The lower detection limit, selectivity and sensitivity were determined to evaluate the performance of the analyzer. It was found that different pathlengths should be used to produce linear calibration curves for CO2 from ppmv to percentage levels. As a result, a wide-range NDIR analyzer, coupled with flexible pathlengths from 4.8 to 10.4 m, was developed. In terms of interference, only H2O should be taken into account due to its high concentration in indoor air. CO should be considered in some special locations at the ppmv level. The measurement errors for ppmv and the percentage levels were 0.4 and 0.9%, respectively.

... For both images, data confusion matrices were created using the test samples to check the accuracy of the classification results, as shown in Tables 2 and 3. Then, it's predicted along with the kappa coefficient using the confusion matrix defined below (Lillesand et al., 2004). ...

  • Pawan Thapa Pawan Thapa

Rapid urbanization has a significant impact on land use, climate, and rainfall. By unbalancing energy demand, random land cover change has a detrimental effect on Kathmandu's land surface temperature and precipitation. Higher land surface temperature (LST) in urban areas increases energy consumption, which the impoverished are unable to meet with their meager income. Detection and prediction of the influence of land changes on land surface temperature and precipitation. The results revealed that land cover change was a significant driver of LST increase during 2000 and 2018. The study shows how the land cover has changed over time, increasing built-up areas while decreasing forest, open space, and riverine and lake regions. The removal of trees resulted in an increase in maximum and lowest temperature and a considerable decrease in precipitation. By 2025, land use and land cover change trends are likely to deteriorate, with forest, farmland, and water bodies all expected to decline by 15%, 18%, and 25%, respectively. Urbanized areas are expected to rise the most in 2025, with a 20% increase. The fundamental cause of these changes is rapid urbanization, which is accompanied by a lack of solid planning and increasing rural-urban mobility. These changes are associated with the soar in temperature, rainfall, energy use, which positively influence poor people. It recommends that city planners consider their urban design plan and policy.

... Table ( shows the results of this classification of level (I) within the study area with respect to area and their percentage. The information of the Level I of land use was taken, for example, while efficiently and economically gathered over large areas by a landsat type of satellite or from high-altitude imagery, which could also be interpreted from conventional largescale aerial photographs imagery or compiled by ground survey, (Lillesand, and Kiefer, 2000). For level I, the details of classes on the study area can be summarized as Classes can change one to another with a time, and there are many methods by which land cover change may be studied using remotely sensed data (Mas, 1999). ...

... Throughout the range beyond 1.3 µm, leaf reflectance is approximately inversely related to the total water present in a leaf, a function of the moisture content. In the range from about 0.7 to 1.3 µm, a plant leaf typically reflects 40-50% of the energy incident upon it primarily due to the internal structure of plant leaves [55]. The NDII index was first assessed for different years after 2006, at different dates of the July-August period, and an emerging repetitive pattern was identified for the island (except for the areas burned in 2007, 2012, and 2016). ...

  • Nektaria Adaktylou
  • Dimitris Stratoulias
  • Rick Landenberger

Wildfires burn tens of thousands of hectares of forest, chaparral and grassland in Mediterranean countries every year, giving rise to landscape, ecologic, economic, and public safety concerns. On the Greek island of Chios and in many other Mediterranean landscapes, areas affected by fire are difficult to access and control due to rugged terrain, requiring wildfire preparedness and response plans that support fire fighting. This study utilized open source data and a weighted linear combination to extract factors that determine wildfire risk. Landsat satellite imagery and publicly available geospatial data were used to create a Geographic Information System and a multi-criteria analysis to develop a methodology for spatially modeling fire risk on Chios, a Greek island with frequent fire occurrence. This study focused on the static, structural component of the risk assessment to produce a spatial distribution of fire risk as a thematic map. Fire weather conditions were accounted for using Fuel Moisture Content, which reflected dryness of dead fuels and water deficit of live biomass. To assess the results, historic fire data representing actual occurrence of fire incidents were compared with probable fire locations predicted by our GIS model. It was found that there was a good agreement between the ground reference data and the results of the created fire risk model. The findings will help fire authorities identify areas of high risk for wildfire and plan the allocation of resources accordingly. This is because the outputs of the designed fire risk model are not complex or challenging to use in Chios, Greece and other landscapes.

... Land use refers to the ways in which human beings use and manage land and its re-sources as a way of sustaining their lives [1]. It differs from land cover, which refers to the biological and physical materials that exist on the surface of land, whether natural or manmade [2,3]. Land use includes agricultural, residential, commercial or any other anthropogenic uses of the land by people. ...

The socioeconomic and ecological value of Lake Victoria is threatened by significant regional development and urbanization. This study analyzed spatial-temporal land use/land cover changes in the Kenyan Lake Victoria basin from 1978-2018 using Landsat 3, 4-5 and 8 imagery, with a view to identifying the extent and potential impacts of urbanization on the basin. Supervised image classification was undertaken following the Maximum Likelihood algorithm to generate land use/land cover maps at ten-year intervals. Results indicate that the basin is characterized by six main land use/land cover classes namely, agricultural land, water bodies, grasslands and vegetation, bare land, forests and built-up areas. Further, the results indicate that the basin has experienced net increases in built-up areas (+97.56%), forests (+17.30%) and agricultural land (+3.54%) over the last 40 years. During the same period, it experienced net losses in grassland and vegetation (-37.36%), bare land (-9.28%) and water bodies (-2.19%). Generally, the changing landscapes in the basin are characterized by conversion of natural environments to built-up environments and driven by human activities, urban populations and public policy decisions. The study therefore recommends the establishment of a land use system that creates a balance between the ecological realm and sustainable development.

... This index describes the compactness ratio of objects. The compression of the image objects is obtained using Equation (4) [79] by dividing the area and perimeter of the object by the total number of pixels. In this criterion, the value range of the effects is between zero and infinity, which in a satisfactory situation is equal to 1. ...

This study aimed to classify an urban area and its surrounding objects after the destructive M7.3 Kermanshah earthquake (12 November 2017) in the west of Iran using very high-resolution (VHR) post-event WorldView-2 images and object-based image analysis (OBIA) methods. The spatial resolution of multispectral (MS) bands (~2 m) was first improved using a pan-sharpening technique that provides a solution by fusing the information of the panchromatic (PAN) and MS bands to generate pan-sharpened images with a spatial resolution of about 50 cm. After applying a segmentation procedure, the classification step was considered as the main process of extracting the aimed features. The aforementioned classification method includes applying spectral and shapes indices. Then, the classes were defined as follows: type 1 (settlement area) was collapsed areas, non-collapsed areas, and camps; type 2 (vegetation area) was orchards, cultivated areas, and urban green spaces; and type 3 (miscellaneous area) was rocks, rivers, and bare lands. As OBIA results in the integration of the spatial characteristics of the image object, we also aimed to evaluate the efficiency of object-based features for damage assessment within the semi-automated approach. For this goal, image context assessment algorithms (e.g., textural parameters, shape, and compactness) together with spectral information (e.g., brightness and standard deviation) were applied within the integrated approach. The classification results were satisfactory when compared with the reference map for collapsed buildings provided by UNITAR (the United Nations Institute for Training and Research). In addition, the number of temporary camps was counted after applying OBIA, indicating that 10,249 tents or temporary shelters were established for homeless people up to 17 November 2018. Based on the total damaged population, essential resources such as emergency equipment, canned food, and water bottles can be estimated. The research makes a significant contribution to the development of remote sensing science by means of applying different object-based image-analyzing techniques and evaluating their efficiency within the semi-automated approach, which, accordingly, supports the efficient application of these methods to other worldwide case studies.

... The NDVI was computed following an established standard NDVI derivation process. The NDVI was used because the normalization in the equation partially compensates for illumination conditions and surface terrain effects such as minimizing soil and reducing background effects (Lillesand and Kiefer, 1979;Lillesand et al., 2004). The NDVI data at 250 m spatial resolution and 16-day composite temporal resolution interval acquired by MODIS on the Terra platform (MOD13Q1) were used to derive the NDVI time series relevant for phenological analysis. ...

  • Anthony Egeru Anthony Egeru
  • John Paul Magaya
  • Derick Ansyijar Kuule
  • Jjumba Justine Namaalwa

Phenological properties are critical in understanding global environmental change patterns. This study analyzed phenological dynamics in a savannah dominated semi-arid environment of Uganda. We used moderate-resolution imaging spectroradiometer normalized difference vegetation index (MODIS NDVI) imagery. TIMESAT program was used to analyse the imagery to determine key phenological metrics; onset of greenness (OGT), onset of greenness value, end of greenness time (EGT), end of greenness value, maximum NDVI, time of maximum NDVI, duration of greenup (DOG) and range of normalized difference vegetation index (RNDVI). Results showed that thicket and shrubs had the earliest OGT on day 85 ± 14, EGT on day 244 ± 32 and a DOG of 158 ± 25 days. Woodland had the highest NDVI value for maximum NDVI, OGT, EGT, and RNDVI. In the bushland, OGT occurs on average around day 90 ± 11, EGT on day 255 ± 33 with a DOG of 163 ± 36 days. The grassland showed that OGT occurs on day 96 ± 13, EGT on day 252 ± 36 with a total DOG of 156 ± 33 days. Early photosynthesis activity was observed in central to eastern Karamoja in the districts of Moroto and Kotido. There was a positive relationship between rainfall and NDVI across all vegetation cover types as well as between phenological parameters and season dynamics. Vegetation senescence in the sub-region occurs around August to mid-September (day 244-253). The varied phenophases observed in the sub-region reveal an inherent landscape heterogeneity that is beneficial to extensive pastoral livestock production. Continuous monitoring of savannah phenological patterns in the sub-region is required to decipher landscape ecosystem processes and functioning.

... The morphological elements and units were mapped based on the visual interpretation of satellite images (e.g., Landsat-TM/OLI and ALOS PALSAR), topographic maps, and DEMs, using interpretative criteria described by Lillesand et al. (2004). The topographic and geological profiles were prepared with DEM aid, made from the interpolation of topographic data at a scale of 1:10,000 (dataset from IGC-SP) and Shuttle Radar Topography Mission (SRTM) and ALOS PALSAR, with 30 and 12 m spatial resolution, respectively. ...

The evolution of fluvial systems has been related to tectonics and climate controls across various spatiotemporal scales. Despite the growing efforts to investigate the effects of those controls in fluvial dynamics, studies in intraplate tropical regions are lacking. Here, we applied geomorphological, sedimentological, and optically stimulated luminescence dating (OSL) techniques to investigate the effects of climate and tectonic factors on the evolution of the Upper and Middle Tietê River during the late Quaternary, especially concerning alluvial aggradation and terrace formation. The Tietê River is one of the most important rivers of southeast Brazil, flowing from steep crystalline to low-relief sedimentary intraplate terrains, in an area with evidence of Cenozoic tectonics and under a tropical monsoon climate. We recognized one fluvial terrace level in the Upper Tietê valley and a sequence of seven terraces, from 2 to 105 m above the channel level, in the Middle Tietê. These terraces are composed of thin deposits (<10 m) of sand and gravel. The terraces of the Upper Tietê and the high and intermediate terrace levels of the Middle Tietê River are strath terraces, while the low terraces of the middle reach are cut-and-fill terraces. Lithological shifts and structural features of the watershed terrain play a strong role in the occurrence and distribution of these terrace levels. The Serra de Paranapiacaba, a regional knickzone, hinders the lowering of base level and river incision to upstream, limiting the formation and preservation of terraces in high topographic levels in the Upper Tietê. The formation of seven terrace levels in the Middle Tietê River was controlled by the combination of low erosional resistance of the lithological substrate and high stream power and coarse bedload that increased the erosion efficiency of the channels. Thus, the influence of intraplate tectonics on the fluvial landscape is restricted to passive controls by exhumated basement structures from older tectonic events. OSL dating of sedimentary deposits in different terrace levels indicate five periods of aggradation in the Middle Tietê valley since 18 ka: 17.7 ± 1.7 ka; 9.8 ± 1.0 to 8.6 ± 0.8 ka; 7.1 ± 0.7 to 5.8 ± 0.5 ka; 4.2 ± 0.4 to 3.1 ± 0.3 ka; and 0.6 ± 0.06 ka. The results indicate that changes in the activity of the South American Monsoon System induced changes in vegetation cover and water discharge in the river valleys of southeastern Brazil over the past 18 ka. The aggradation periods are correlated with drier environmental conditions and sparser vegetation. In contrast, valley incision occurred under transitions to wetter environmental conditions and was made possible by vegetation recovery. Therefore, climate-induced changes in the water discharge were the main allogenic control on the late Quaternary landscape evolution.

... The maximum-likelihood classifier was adopted from a parametric classification algorithm [27][28][29][30] and divided into four classes: urban, vegetation, forest and waterbodies ( Table 2). The classes that were involved in the selection of the training sites were used as a reference in the user-guided approach [17,[31][32][33][34]. For each of the predetermined change detection types, training samples were selected by delimiting the polygons in the study area. ...

The objective of this research was to detect changes in forest areas and, subsequently, the potential forest area that can be extended in the South Sumatra province of Indonesia, according to the Indonesian forest resilience classification zones. At first, multispectral satellite remote sensing datasets from Landsat 7 ETM+ and Landsat 8 OLI were classified into four classes, namely urban, vegetation, forest and waterbody to develop Land Use/Land Cover (LULC) maps for the year 2003 and 2018. Secondly, criteria, namely distance from rivers, distance from roads, elevation, LULC and settlements were selected and the reclassified maps were produced from each of the criteria for the land suitability analysis for forest extension. Thirdly, the Analytical Hierarchy Process (AHP) was incorporated to add expert opinions to prioritize the criteria referring to potential areas for forest extension. In the change detection analysis, Tourism Recreation Forest (TRF), Convertible Protection Forest (CPF) and Permanent Production Forest (PPF) forest zones had a decrease of 20%, 13% and 40% in area, respectively, in the forest class from 2003 to 2018. The Limited Production Forest (LPF) zone had large changes and decreased by 72% according to the LULC map. In the AHP method, the influential criteria had higher weights and ranked as settlements, elevation, distance from roads and distance from rivers. CPF, PPF and LPF have an opportunity for extension in the highly suitable classification (30%) and moderately suitable classification (41%) areas, to increase coverage of production forests. Wildlife Reserve Forests (WRFs) have potential for expansion in the highly suitable classification (30%) and moderately suitable classification (52%) areas, to keep biodiversity and ecosystems for wildlife resources. Nature Reserve Forests (NRFs) have an opportunity for extension in the highly suitable classification (39%) and moderately suitable classification (48%) areas, to keep the forests for nature and biodiversity. In case of TRF, there is limited scope to propose a further extension and is required to be managed with collaboration between the government and the community.

... Confusion matrix is a table that shows the correspondence between the classification product and a reference data. The UA is a measure of the commission error and specifies the probability that a pixel classified into a given class is truly represented by that class on the ground (Lillesand et al., 2014). The PA is the measure of omission error, which shows how well the training pixels of the given class are classified. ...

Remote sensing technique has been used in this paper to study the effect of underground coal mining subsidence on the health condition and growth pattern of the native vegetation. The study site was an underground coal mining area of Singareni Collieries Company Limited (SCCL), India. Mining was performed in 2001, and subsidence occurred in 2001-2002. Satellite imagery of the undamaged forest before the mining subsidence was compared with the affected forest after the mining subsidence. The changes in vegetation covered areas were analyzed based on digital image classification approach and vegetation index. The evaluation of vegetation changes was performed for years 2000–2005 (period 1), 2005–2010 (period 2), 2010–2018 (period 3), and the entire study period of 2000–2018 (period 4), separately. It was observed that the dense vegetation area was reduced by 16.91% during period 1 (after 3-4 years of the occurrence of subsidence), while during the consecutive later periods of 2 and 3, it increased by 24.27% and 6.59%, respectively. During the entire period 4 of the study, dense vegetation was increased by 13.95%. This would be because of natural recovery and gradual stabilization of the native soil due to the absence of human interference in the long term of time. The sparse vegetation and non-vegetated area were changed by +14.22% and +2.68% during period 1, while they were changed by -15.36%, -7.91%, and -8.91%, +1.32%, during periods 2 and 3, respectively.

... The classification method was the most essential aspect of the processing of remotely sensed data (Roy & Giriraj, 2008). Traditional classification methods, such as pixel-based with maximum likelihood approaches, have been widely used in mapping of land use and land cover, and are based on multivariate probability density functions of classes (Lillesand et al., 2008;Hashim et al., 2019). However, advanced classification algorithms, such as support vector machine (SVM), have recently been developed to improve classification accuracy (Deilmai et al., 2014). ...

Information on urban vegetation and land use is critical for sustainable environmental management in cities. In general, urban vegetation is important for urban planning because it helps to maintain a balance between the natural environment and the built-up region. The assessment of the composition and configuration of the vegetation is important to highlight the urban ecosystem. Thus, obtaining information about urban vegetation is critical for developing a sustainable urban development strategy. Remote sensing is increasingly being used to generate such data for mapping and monitoring changes in urban vegetation. The aim of this study is to identify and classify vegetation using the high-resolution Pleiades satellite image in urban park areas using pixel-based image analysis. Pixel based method was applied and support vector machine algorithm was used for classification of urban vegetation. Comparison of accuracy was made from the error matrices, overall accuracy and kappa coefficient for vegetation and non-vegetation classes. The overall accuracy for the classification approach was 98.98% and a kappa value of 0.97. The result demonstrates the ability of high-resolution imagery to accurately extract urban vegetation despite the complex surface of the urban area. The findings can be used to support other research and applications related to urban green space monitoring, conservation, and future urban vegetation planning.

... For the purpose of supervised classification, the classes with the same spectral signatures were merged. This allows all the pixels that are included in an image to be automatically assigned to the land cover classes [70]. The maximum-likelihood classifier was employed by applying training sets developed from Landsat images. ...

Natural landscapes have changed significantly through anthropogenic activities, particularly in areas that are severely impacted by climate change and population expansion, such as countries in Southeast Asia. It is essential for sustainable development, particularly efficient water management practices, to know about the impact of land use and land cover (LULC) changes. Geographic information systems (GIS) and remote sensing were used for monitoring land use changes, whereas artificial neural network cellular automata (ANN-CA) modeling using quantum geographic information systems (QGIS) was performed for prediction of LULC changes. This study investigated the changes in LULC in the Perak River basin for the years 2000, 2010, and 2020. The study also provides predictions of future changes for the years 2030, 2040, and 2050. Landsat satellite images were utilized to monitor the land use changes. For the classification of Landsat images, maximum-likelihood supervised classification was implemented. The broad classification defines four main classes in the study area, including (i) waterbodies, (ii) agricultural lands, (iii) barren and urban lands, and (iv) dense forests. The outcomes revealed a considerable reduction in dense forests from the year 2000 to 2020, whereas a substantial increase in barren lands (up to 547.39 km2) had occurred by the year 2020, while urban land use has seen a rapid rise. The kappa coefficient was used to assess the validity of classified images, with an overall kappa coefficient of 0.86, 0.88, and 0.91 for the years 2000, 2010, and 2020, respectively. In addition, ANN-CA simulation results predicted that barren and urban lands will expand in the future at the expense of other classes in the years 2030, 2040, and 2050. However, a considerable decrease will occur in the area of dense forests in the simulated years. The study successfully presents LULC changes and future predictions highlighting significant pattern of land use change in the Perak River basin. This information could be helpful for land use administration and future planning in the region.

... Several advanced algorithms have evolved in recent times that can be used for developing LULC maps to classify remote sensing images, such as the artificial neural networks, decision trees, support vector machines, object-based image analysis, etc. (Grekousis et al., 2015;Kumar et al., 2020;Otukei and Blaschke, 2010;Singh et al., 2020a). The most common classifiers used in processing remote sensing images are K-Means, ISO-Data, Minimum-Distance (Lillesand et al., 2004). ...

The land use and land cover (LULC) maps are often required by planners and policymakers for effective planning and management interventions at the local, national, regional and global levels. Various attempts have been made to develop LULC maps using field-based surveys and by processing remotely sensed images. These maps can be developed using different tools and methodologies at different scales to achieve different levels of accuracy. With the advent of remote sensing technologies and its application in making LULC maps, attempts have been made to develop such maps with improved accuracy and consistency. The machine learning-based approaches have been attempted to develop LULC maps with varying levels of accuracy using different satellite images. Making LULC maps for a large region such as India covering a total area of ca. 3,287,469 km2 can be a cumbersome process using conventional approaches. Thus the map was developed using remotely sensed images using machine learning algorithm (Mnlogit) on LANDSAT images (2005, 2006, 2007 and 2016) for entire India region. We developed LULC maps of years 2005, 2006, 2007 and 2016 to test the consistency of classification using the trained Mnlogit model using field survey based signatures for corresponding years in respective images. We could achieve reasonably good accuracy varying in the range of 80–86% during all four years. A Kappa statistic - K (hat), was obtained in the range of 0.71–0.81 which indicates reasonably good accuracy. The study can be replicated for other regions using other available satellite remote sensing images to obtain LULC maps. In general, the suggested approach in this study will help planners to obtain LULC maps at different time intervals to study land-use change dynamics in a shorter time and cost-effective way.

... are highly sensitive to water, and its data acquisition is not affected by clouds, weather, day or night [13,14], which is helpful in drawing water distribution maps and monitoring river water surfaces [15,16]. Machine learning algorithms based on remote sensing data and geographic information systems (GISs) have been successfully applied to river surface monitoring [17][18][19][20][21][22]. ...

  • Zelin Huang
  • Wei Wu
  • Hongbin Liu
  • Jin Hu Jin Hu

The knowledge of water surface changes provides invaluable information for water resources management and flood monitoring. However, the accurate identification of water bodies is a long-term challenge due to human activities and climate change. Sentinel-1 synthetic aperture radar (SAR) data have been drawn, increasing attention to water extraction due to the availability of weather conditions, water sensitivity and high spatial and temporal resolutions. This study investigated the abilities of random forest (RF), Extreme Gradient Boosting (XGB) and support vector machine (SVM) methods to identify water bodies using Sentinel-1 imageries in the upper stream of the Yangtze River, China. Three sets of hyper-parameters including default values, optimized by grid searches and genetic algorithms, were examined for each model. Model performances were evaluated using a Sentinel-1 image of the developed site and the transfer site. The results showed that SVM outperformed RF and XGB under the three scenarios on both the validated and transfer sites. Among them, SVM optimized by genetic algorithm obtained the best accuracy with precisions of 0.9917 and 0.985, kappa statistics of 0.9833 and 0.97, F1-scores of 0.9919 and 0.9848 on validated and transfer sites, respectively. The best model was then used to identify the dynamic changes in water surfaces during the 2020 flood season in the study area. Overall, the study further demonstrated that SVM optimized using a genetic algorithm was a suitable method for monitoring water surface changes with a Sentinel-1 dataset.

... In this research, six different types of land cover like Built-up land, Cultivated Land, Water Body, Forest Cover, Open Field, and Barren Land are selected for the research. In supervised classification consists of three steps: 1) training steps, 2) classification stage and 3) output stage (Lillesand, Kiefer, & Chipman, 2004). Once the image was classified, it is always mandatory to check the accuracy The error matrix constitutes N * N elements based on ground truth data (reference data) against classified image where N indicates a total number of classes. ...

Bagan-Nyaung Oo area is the most picturesqu earchitectural complex in Myanmar. Bagan-Nyaunng Oo area is situated between 94°45̍ 00̎ E to 95°00̍ 00̎ E and 21°00̍ 00̎ to 21°15̍ 00̎ N. The research aims are to demonstrate the application of Remote Sensing (especially satellite image analysis) and to interpret the Engineering Geology approach to Environmental Geology and vice versa. The research area covers mostly the alluvial plain flanking the Ayeyarwady River and partly the debris and small fan materials derived from Tuywin Taung and Tantkyi Taung hills whichare exposed with rocks of Miocene to Oligocene. Bed rock in the area is mainly represented by rocks of Irrawaddy Formation (Late Miocene to Pliocene), Okhmintaung Formation (Upper Oligocene) and Padaung Formation and Shwezettaw Formation (Lower Oligocene). Mainly the alluvial soils of Quaternary-Recent are deposited on the plain and along the river banks by fluvial action.The areas susceptible to landslides, rock falls, mass movements, and debris flows hazards are demarcated in the Tuywin Taung and Tantkyi Taungthat have been encountered with a number of small tension cracks, active and old landslides. Side cutting in both sides of Ayeyarwady River banks is caused by river bank scouring and rain water resulting into steep slopes. In the rainy season, low lands adjacent to the Ayeyarwady River and the main streams in the area are affected by flood. Low to medium bearing capacity areas are concentrated in the areas where active alluvial fan and river bed deposits. Most of the plain area is covered by a firm soil with a stable bearing capacity and so appropriate for small to medium scale construction purposes. Several locations of construction materials quarry sites are seen in the study area. Improper quarrying of construction materials trigger the landslides and river bank scouring. Existing land use patterns in the study area are agricultural, sparse forest and scrub, settlements, industries, recreation centres infrastructures, small land fill and waste disposal sites. The root causes of river water pollution in Nyaung Oo area are direct connection of sewage drainage, sewage pipe line, haphazard disposal of industrial, hospital and hotels waste in open space and stream and improper dumping of solid wastes into the riverside area. 70, severely damaged more than half of the important structures and irreparably destroyed many of them. Flood causes, destruction by earthquakes, landslides and erosion and LCLU (Land Cover/Land Use) evaluation are mentioned. The research would be a general help to planners and developers at local level particularly in hazard mitigation, environmental management and civil engineering developments within the research area.

  • Joel Mejia Joel Mejia
  • María Gabriela Camargo

Se desarrolló un enfoque para la evaluación ambiental en relación con el desarrollo de las actividades humanas, considerando el entorno biofísico desde su funcionalidad compleja para la planificación urbana. Dicho enfoque fue aplicado para la realización del Plan de Desarrollo Urbano Local de la ciudad de Barinas, Venezuela. El enfoque funcional considera el entorno biofísico como un elemento no inerte, que cumple funcionalidades en distintas perspectivas: como fuente de recursos, como soporte fisico y como receptor de efluentes, que en conjunto inciden en el desarrollo de la ciudad actual y futura. Cuando se supera la lógica de funcionamiento del sistema biofísico a causa de una demanda socio económica, se generan problemas ambientales como: contaminación de aguas, suelos y aire, polución, pérdida de biodiversidad, erosión, entre otros, que inciden en el desarrollo territorial. Si se respeta el funcionamiento del entorno biofísico, su capacidad de carga, será posible garantizar calidad de vida a la población y transitar hacia la sostenibilidad. Se describe como evaluar cada funcionalidad para identificar los problemas ambientales y orientar estrategias y acciones de planificación urbana.

Uydu teknolojilerinin gelişmesi ile Uzaktan Algılama (UA) kullanıcısı her geçen gün artmaktadır. UA arazi örtüsü ve kullanımının tespit edilmesi, su kaynakları yönetimi, değişim analizi vb. olmak üzere birçok kullanım alanına sahiptir. UA teknikleriyle elde edilen veriler, özellikle arazi örtüsü kullanımının zamansal değişiminin belirlenmesinde yaygın olarak kullanılmaktadır. Arazi örtü değişiminin kullanımında, o alanın zamanla başka arazi kullanımı ve bitki örtüsü sınıflarına dönüşüp dönüşmediği gözlemlenmektedir. Su kaynaklarının izlenmesi, korunması ve optimum kullanım koşullarının değerlendirilmesi çalışmalarında uzaktan algılama teknolojilerinden de yararlanılmaktadır. Bu teknolojiler, su kaynakları ile ilgili araştırmalarda karar verme ve yönetim konularında önemli altlık oluşturmaktadır. Ayrıca, su kaynaklarındaki zamansal değişimlerin belirlenmesi ve gerekli önlemlerin alınması aşamasında da uzaktan algılama çok önemli avantajlar sağlamaktadır. Bu çalışmada da Ankara'ya 20 km uzaklıkta bulunan Gölbaşı ilçesinde yer alan Mogan Gölü ve çevresinin Landsat uydu görüntüleri kullanılarak su yüzeyi ve arazi örtüsünün değişim analizi belirlenmiştir. Çalışma alanına ait 1998-2010 yılları arası üç periyot olacak şekilde Landsat TM5 uydu görüntüleri ve 2019 yılına ait Landsat 8 OLI_TIRS uydu görüntüsü kullanılmıştır. Metot olarak kontrolsüz ve kontrollü sınıflandırma (en çok benzerlik) yöntemleri kullanılarak su yüzey alanları, yapay yüzeyler, tarım alanları, ormanlık ve doğal alanlar olmak üzere 4 adet sınıf belirlenmiştir. Bölgeye ait alansal değişim incelenmiş ve yıllara göre değişimler birbiriyle karşılaştırılmıştır.

Due to the importance of forests in sustainable development and conservation of the global ecosystem, deforestation monitoring has become increasingly crucial in semi-arid regions. Persian Oak ( Quercus ) forests in the Zagros region, in western Iran, are one of the endangered ecosystem. The negative consequences of the destruction of forests will make life difficult in the central Iranian plateau. Development of agriculture, illegal grazing, and dust are the primary source of degradation and deforestation in the Zagros Mountains. The objective of this study was to evaluate changes in Nayangiz forest cover over two periods: (1) from 1980 to 2000, before the stricter forest law enforcement; (2) Since 2000, after enactment of strict forest laws such asinhibition of borer beetles in Oak forests and dust protection. The Landsat TM, ETM+, and OLI images were used for this purpose. After calibration, a deep learning method known as a convolutional neural network (CNN) algorithm was applied for supervised image classification. The classification accuracy was 92.2%, 94.1%, and 94.7% for all three images, respectively. Then the map of changes between each class was generated using the image classification difference method. Comparison with the changed classes shows the rates of deforestation and reforestation in each year. Before 2000, the percentage of land use change from forest cover to agricultural land was more than 37%, but in the second period this land use change (from forest cover to agricultural land) was reduced to 15%. However, a significant percentage of deforestation (23%) has been due to the effects of dust and land use change since 2000.In the study area, illegal agriculture and overgrazing led to increased dust production, which paved the way for desertification in the near future, and the mentioned factors are the factors that should be considered in order to turn forest cover into barren lands in the second period.Keywords: Land use land cover, Landsat image, convolutional neural networks, deforestation, change detection.

Rapid changing climate has increased the risk of natural hazards and threatened global and regional food security. Near real-time monitoring of crop response to agrometeorological hazards is fundamental to ensuring national and global food security. However, quantifying crop responses to a specific hazard in the natural environment is still quite challenging, especially over large areas, due to the lack of tools to separate the independent impact of the hazard on crops from other confounding factors. In this study, we present a general difference-in-differences (DID) framework to monitor crop response to agrometeorological hazards at near real-time using widely accessible remotely sensed vegetation indices (VIs). To demonstrate the effectiveness of the DID framework, we applied it in quantifying the dry-hot wind impact on winter wheat in northern China as a case study using the VIs calculated from the MODIS data. The monitoring results for three years with varying severity levels of dry-hot events (i.e., 2007, 2013, and 2014) demonstrated that the framework can effectively detect winter wheat growing areas affected by dry-hot wind hazards. The estimated damage shows a notable relationship (R2 = 0.903, p < 0.001) with the dry-hot wind intensity calculated from meteorological data, suggesting the effectiveness of the method when field data on a large scale is not available for direct validation. The main advantage of this method is that it can effectively isolate the impact of a specific hazard (i.e., dry-hot wind in the case study) from the mixed signals caused by other confounding factors. This general DID framework is very flexible and can be easily extended to other natural hazards and crop types with proper adjustment. Not only can this framework improve the crop yield forecast but also it can provide near real-time assessment for farmers to adapt their farming practice to mitigate impacts of agricultural hazards.

Background: Depression areas are essential structural components of Karst ecosystems. Their influence in the carbon and nitrogen dynamics under different land uses, which could be effectively used to define management strategies aiming to combat global warming, however, is not clear. This study investigated the changes in selected soil attributes across four land use types (forest, degraded forest, rangeland and cropland) both in depressed and non-depressed areas in a karst ecosystem in Kahramanmaras, Turkey. Soil attributes investigated in this study included soil pH, soil moisture (SM), soil organic carbon (SOC), total nitrogen content (TN), available water (AW), hydraulic conductivity (HC), root rate (RR) and C/N ratio.

  • Chhabi Lal Chidi Chhabi Lal Chidi
  • Ramesh Kumar Salami Magar
  • Dipendra Salami Magar

Growing urbanization results built up surfaces converting from agriculture land, forest and other natural land cover surfaces. Increasing built up surfaces, means of transport and industrial activities are major results for increasing temperature in the city area as compared to other areas. Increasing heat is a concern to human health of the people living in urban areas. Increasing temperature in the city area in developing countries is being a growing concern. Kathmandu valley is one of the most rapidly growing urbanization in Nepal. The present study aims to assess the changing Land Surface Temperature (LST) in Kathmandu valley using LANDSAT 7 images. Similarly, Urban Heat Island (UHI) effect was evaluated in land use categories which were derived from Google Earth images. Study revealed that built up area contributed highly to increase land surface temperature. New built up with compact settlement area has higher land surface temperature as compare to other land use/land cover surfaces. City core has higher LST as compared to less urbanized and surrounding parts. The LST has highly increased during 1999 to 2017 with increasing urbanization. However, the ecological condition of UHI effect is not so bad till date but the study result indicated the continuous increasing urbanization may result worse ecological condition in Kathmandu Valley in the future.

  • Arif Oguz Altunel Arif Oguz Altunel

GIS INTEGRATED FOREST ROAD PLANNING, Geographic Information Systems (GIS) have turned out to be an increasingly significant tool for environmental planning and environmental impact studies in recent years. Different "Multi Criteria Decision Making" (MCDM) approaches are developed to combine factors in land suitability analyses for potential land uses. These MCDM approaches are used to develop a common suitability index. Results from the MCDM analysis are then linked to a GIS for more detailed spatial analysis. By evaluating alternative forest road routes in the office, on a Digital Terrain Model, generated with a GIS, days or even weeks can be saved of valuable field time and ultimately, a better design can emerge. Through the use of GIS, many alternatives can be quickly analyzed for alignment, slope stability, grades and construction cost using standard GIS functionality. In this study, a GIS based road-pegging approach was tried to assist in initial road planning by eliminating the error prone traditional method. Pegging was done on a DTM with digital contours, built on a land suitability data generated with MCDM. As a result of the investigation, by itself, a proposed new road route required 7 % less road mileage in total while it exploited the forest 3 % more than the present route. When combined with the skyline systems, the exploitation ratio rose up to 19.7 % more than that of the present route. In short, 96.9 % of the whole forest can be exploited with newly proposed road route. Interaction with aquatic systems (proximity to a suggested 60 m immediate buffer around creeks) is 16.6 % less than the present situation. This paper looks at the usefulness and capabilities of GIS, backed by a MCDM approach in the evaluation of a built forest road network, and in planning of a new hypothetical network. It was intended to show that GIS could be an invaluable tool in forest road and transportation planning. With it, numerous inputs, impossible to integrate in the past, can be incorporated into an environmentally sound forest road planning.

  • Carlos Álvaro Carlos Álvaro

As alterações climáticas e a crescente artificialização de espaços naturais têm produzido impactes que se traduzem, designadamente, na alteração de habitats naturais. O impacto destas mudanças nos arbovírus, ou seja, nos vírus que são transmitidos por animais artrópodes, com particular destaque para os mosquitos como transmissores destes, têm representado um grande desafio à saúde pública, devido às alterações climáticas e ambientais que favorecem a amplificação da transmissão de vírus e a transposição da barreira entre espécies. As mudanças no uso e ocupação do solo são um fator de potencialização da proliferação das espécies de mosquitos que transmitem doenças como a Dengue, o Zika e Chicungunha. A par disto, a variabilidade espaço�temporal dos índices de vegetação (Vegetation indices) tem sido positivamente correlacionada com a taxa de incidência destas doenças. A utilização de tecnologias de observação da terra (OT), como meio para sinalização destes habitats, constitui uma ferramenta de combate permitindo antecipar, prevenir e controlar as novas doenças infeciosas emergentes, em especial destaque, arbovírus, para evitar grandes riscos sociais e económicos.

  • Muhammad Naufal Islam Muhammad Naufal Islam

Kebudayaan sebagai hasil cipta, karsa, dan karya manusia memiliki peranan sentral dalam kehidupan manusia. Kebudayaan sebagai landasan filosofis memberikan pedoman kepada manusia dalam berinteraksi baik dengan sesama maupun dengan lingkungan sekitar. Kebencanaan sebagai bagian dari fenomena tidak pernah lepas dalam kehidupan manusia. Kemunculan berbagai nilai mengenai fenomena bencana merupakan hasil interaksi antara fenomena bencana dengan manusia dalam suatu keruangan. Kehadiran nilai berimplikasi terhadap pemaknaan masyarakat dalam menanggapi fenomena bencana yang termanifestasi pada pola perilaku masyarakat dalam pengurangan resiko bencana. Berbagai pemaknaan masyarakat terhadap fenomena bencana mengacu pada nilai yang berada dalam kehidupan masyarakat , tak terkecuali menyangkut nilai-nilai kultural yang tumbuh dan berkembang dalam kehidupan bermasyarakat. Penelitian ini bertujuan untuk menungkap mengenai pemaknaan masyarakat lokal dalam menanggapi fenomena bencana, sehingga pemaknaan ini berimplikasi pada bagaimana pola respon yang ditunjukkan oleh masyarakat dalam upaya pengurangan resiko bencana. Penelitian ini menggunakan penelitian kualitatif deskriptif, dengan pendekatan studi kasus, serta teknik pengambilan data didasarkan atas hasil indepth interview terhadap informan menggunakan teknik tringulasi. Berdasarkan hasil penelitian bahwa entitas pemaknaan masyarakat terhadap fenomena bencana dengan berorientasikan pada nilai kultural secara efektif berimplikasi pada pengurangan resiko bencana. Kondisi demikian ditunjukkan dengan rendahnya jumlah korban jiwa pada masyarakat Dusun Bayan, Desa Sukadana, Kecamatan Bayan, Kabupaten Lombok Utara.

  • Kusuma Dewi Kusuma Dewi

Sitiarjo merupakan salah satu desa rawan bencana banjir di Kabupaten Malang. Sitiarjo memiliki profil wilayah yang rendah dibandingkan daerah sekitarnya, terdapat dua sungai, dan terdampak air pasang laut. Kondisi tersebut menjadi faktor mendasar terjadinya banjir bandang di Sitiarjo. Disamping faktor itu terdapat faktor lainnya yang menyebabkan bencana banjir tersebut. Berbagai faktor menjadi pendukung banjir bandang Sitiarjo, dimana periode kebencanaannya semakin memendek dari tahun ke tahun. Melihat hal tersebut, masyarakat Sitiarjo memiliki pengalaman yang dihasilkan dari proses adaptasi lingkungan. Pengalaman itu merupakan mitigasi bencana banjir bandang berbasis kearifan lokal. Penelitian ini bertujuan mengidentifikasi mitigasi banjir bandang berbasis kearifan lokal masyarakat Sitiarjo. Penelitian ini menggunakan metode penelitian kualitatif dengan pendekatan historis. Teknik pengumpulan data dilakukan dengan studi literatur, observasi, wawancara, dokumentasi, dan analisis trianggulasi. Pengambilan sampel menggunakan teknik purposive sampling. Teknik analisis yang digunakan yaitu analisis deskriptif. Hasil penelitian menunjukkan mitigasi masyarakat Sitiarjo terdiri dari mitigasi non-struktural dan struktural. Mitigasi non-struktural meliputi dimensi pengetahuan, nilai, solidaritas kelompok, dan mekanisme pengambilan keputusan. Sedangkan mitigasi struktural masyarakat dapat dilihat berdasarkan dimensi mitigasi mekanik. Mitigasi bencana berbasis kearifan lokal masyarakat Sitiarjo berkontribusi dalam meminimalisir risiko bencana banjir bandang. Namun lambat laun kearifan lokal masyarakat mulai memudar. Melihat hal tersebut, perlu adanya penguatan nilai kearifan lokal masyarakat dari berbagai belah pihak. Diharapkan agar dapat menjadi upaya mitigasi bencana banjir bandang yang efektif oleh masyarakat lokal.

Currently, desertification is a major problem in the western desert of Iraq. The harsh nature, remoteness, and size of the desert make it difficult and expensive to monitor and mitigate desertification. Therefore, this study proposed a comprehensive and cost-effective method, via the integration of geographic information systems (GISs) and remote sensing (RS) techniques to estimate the potential risk of desertification, to identify the most vulnerable areas and determine the most appropriate sites for rainwater conservation. Two indices, namely, the Normalized Differential Vegetation Index (NDVI) and Land Degradation Index (LDI), were used for a cadastral assessment of land degradation. The findings of the combined rainwater harvesting appropriateness map, and the maps of NDVI and LDI changes found that 65% of highly suitable land for rainwater harvesting lies in the large change and 35% lies in the small change of NDVI, and 85% of highly suitable land lies in areas with a moderate change and 12% lies in strong change of LDI. The adoption of the weighted linear combination (WLC) and Boolean methods within the GIS environment, and the analysis of NDVI with LDI changes can allow hydrologists, decision-makers, and planners to quickly determine and minimize the risk of desertification and to prioritize the determination of suitable sites for rainwater harvesting.

Mangroves are biologically important and productive ecosystems endowed with diverse flora and fauna. Despite their economic and ecological services, mangroves face threats from anthropogenic as well as coastal hazards. Assessment and monitoring of this critical and vulnerable habitat of the coastal ecosystem could play a major role in implementing conservation and management plan compatible with Sustainable Development Goals (SDGs). Mangroves by their geographic confinement in coastal/marshy areas are well suited to study with RS & GIS tools given the difficulty to conduct extensive field trials. Developments in the field of remote sensing and Geographic Information System (GIS) in the last three decades have substantially facilitated smart and efficient use of field surveys for assessing different parameters of mangrove ecosystem such as mapping, monitoring the health of mangrove cover, assessing their diversity, characterization of their biophysical and biochemical properties, as well as monitoring the conservation and restoration activities. Recent advancements in sensor technologies, providing very high spatial resolution multispectral, hyperspectral, microwave, and LiDAR data have substantially improved characterization and monitoring of mangroves. Contemporary Data Science methods on storage, geospatial data analytics, and advanced automated algorithms in handling the BIG Data available (archive and real-time data) facilitate a better understanding and assessment of spatio-temporal behaviour of the mangrove ecosystem. This manuscript presents an overview of how the RS and GIS technologies being evolved in the context of their use for scientific and quantitative studies on mangroves.

  • Natalya S. Reshetilo
  • Elena P. Khlebnikova

The article discusses the use of Earth remote sensing methods. The analysis and mapping of changes in the boundaries of the Iyariver in the city of Tulun, Irkutsk region, was carried out using the Erdas Imagine 2015 software package.

  • Wilver Auccahuasi
  • Percy Castro
  • Orlando Aiquipa
  • Nabiltmoggiano

The analysis and processing of data is important in different areas, and we must pay more attention when it comes to the health of people, in the development of the protocol to prevent the outbreak of vectors transmitting tropical diseases with an emphasis on the mosquito " AedesAegypti ", being able to control its reproduction is of vital importance, and is one of the objectives of the protocol, understanding the reproduction times corresponds to the times where we must take necessary actions to be able to cut its reproduction cycle, within the mechanisms Technological we indicate the use of meteorological information to be able to analyze and predict the favorable conditions so that the mosquito can reproduce, added to the valuable information provided by earth observation satellites, in their access to satellite images, which will provide us with Current images of the area of interest, for rapid detection of bodies of water that will be the future nests of the mosquitoes, the heterogeneous processing is characterized by the analysis of the meteorological data in the CPU and the processing of the satellite images in the GPU both running in parallel processes in the same computer, with which we optimize the use of resources available in applications dedicated to health care.

  • Agung Kurniawan Agung Kurniawan

The development of remote sensing technology allows humans to acquire and process data remotely and temporally. Changes in the flow of the Progo river from the last few years are significant, this can be caused by natural factors and human factors. The influence of the intensity of flow and the level of sedimentation in the Progo river causes a massive flow pattern change in the Progo river body. The data used in this research is Medium Spatial Resolution Satellite Imagery, Landsat 5 satellite imagery acquired in 1995 and Landsat 8 acquired in 2017. Monitoring of changes in river flow pattern is generally done by using the method of terrestrial or conventional measurement, which takes a long time, for that the use of methods and remote sensing data can be used to save time. The method used is multispectral classification approach with maximum likelihood algorithm. The results of extraction using digital classification method (maximum likelihood) resulted in the appearance of flow pattern quickly and representative, so this method is suitable for the purpose of rapid detection of changes in flow pattern. The results obtained from the extraction of the Progo river flow pattern show an intricate river flow pattern with many river rubbers on the image appearance of 1995, whereas in the image extraction results in 2017 the river banks and turns do not look dominant, it shows that erosion and sedimentation activities continue to occur massively.

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