scholarly journals Using EPM Model and GIS for Estimation of Soil Erosion in Souss Basin, Morocco

2019 ◽  
Vol 7 (8) ◽  
pp. 1228 ◽  
Author(s):  
Argaz Ahmed ◽  
Darkaoui Adil ◽  
Bikhtar Hasna ◽  
Ayouch Elbachir ◽  
Ramdan Lazaar
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Potential Model ◽  
Soil Protection ◽  
Landsat 8 ◽  
Digital Elevation ◽  
Elevation Model ◽  
Data Layers ◽  
Gis Software ◽  
Basin Area

The study is aimed at predicting soil erosion and investigate its spatial distribution in Souss basin area used EPM (erosion potential model), also known as Gavrilovic method, incorporating into GIS (geographic information system) software. The spatial distribution of soil erosion shows three main zones in the studied area (very slight, slight to moderate). The main factors in the EPM (soil erodibility, soil protection, slope, temperature and rainfall) were evaluated using GIS software. Data layers used in this study were created from digital elevation model (DEM), lithology maps, landsat 8 oli digital images, the highest amount of erosion occurred in the northeast regions, Results showed that about 87.84% of the study area is classified in low and very low to destructive erosion intensify, 12.15% of the study area was moderate potential soil losses.

Spatial and Temporal Variation of Soil Erosion in Guangxi in Recent 20 Years

2013 ◽  
Vol 421 ◽  
pp. 787-791
Author(s):  
Yan Li Chen ◽  
Shi Quan Zhong ◽  
Jian Fei Mo ◽  
Yong Ming Luo
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Temporal Variation ◽  
Digital Elevation Model ◽  
Spatial And Temporal Variation ◽  
Upward Trend ◽  
The Past ◽  
Digital Elevation ◽  
Elevation Model ◽  
Light Medium

TM/ETM data as the base information combined with a digital elevation model are used to analyze the spatial distribution and temporal variation of soil erosion in Guangxi. The results shows that light, medium and strong are the main three levels of soil erosion in Guangxi. The proportions of light and medium soil erosion are higher which are 6.18% and 4.76% respectively. The total area of soil erosion and its degrees exhibit an upward trend since the 1980s. The area of soil erosion in Guangxi increases 4% in the past 20 years. The five levels of soil erosion performance an upward trend mostly. Medium soil erosion is of the biggest change with an increase of 1.29% while acute soil erosion exhibits a smallest change with an increase of 0.49%.

scholarly journals Terrain-Based Shadow Correction Method for Assessing Supraglacial Features on the Greenland Ice Sheet

2021 ◽  
Vol 2 ◽  
Author(s):  
Sasha. Z. Leidman ◽  
Åsa K. Rennermalm ◽  
Richard G. Lathrop ◽  
Matthew. G. Cooper
Keyword(s):  
Land Surface ◽  
Greenland Ice Sheet ◽  
Correction Method ◽  
Correction Coefficient ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Sediment Cover ◽  
Elevation Model ◽  
Uav Images ◽  
Gis Software

The presence of shadows in remotely sensed images can reduce the accuracy of land surface classifications. Commonly used methods for removing shadows often use multi-spectral image analysis techniques that perform poorly for dark objects, complex geometric models, or shaded relief methods that do not account for shadows cast on adjacent terrain. Here we present a new method of removing topographic shadows using readily available GIS software. The method corrects for cast shadows, reduces the amount of over-correction, and can be performed on imagery of any spectral resolution. We demonstrate this method using imagery collected with an uncrewed aerial vehicle (UAV) over a supraglacial stream catchment in southwest Greenland. The structure-from-motion digital elevation model showed highly variable topography resulting in substantial shadowing and variable reflectance values for similar surface types. The distribution of bare ice, sediment, and water within the catchment was determined using a supervised classification scheme applied to the corrected and original UAV images. The correction resulted in an insignificant change in overall classification accuracy, however, visual inspection showed that the corrected classification more closely followed the expected distribution of classes indicating that shadow correction can aid in identification of glaciological features hidden within shadowed regions. Shadow correction also caused a substantial decrease in the areal coverage of dark sediment. Sediment cover was highly dependent on the degree of shadow correction (k coefficient), yet, for a correction coefficient optimized to maximize shadow brightness without over-exposing illuminated surfaces, terrain correction resulted in a 49% decrease in the area covered by sediment and a 29% increase in the area covered by water. Shadow correction therefore reduces the overestimation of the dark surface coverage due to shadowing and is a useful tool for investigating supraglacial processes and land cover change over a wide variety of complex terrain.

scholarly journals A Probabilistic Assessment of Soil Erosion Susceptibility in a Head Catchment of the Jemma Basin, Ethiopian Highlands

Geosciences ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 248 ◽  
Author(s):  
Mariaelena Cama ◽  
Calogero Schillaci ◽  
Jan Kropáček ◽  
Volker Hochschild ◽  
Alberto Bosino ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Remote Sensing Data ◽  
Gully Erosion ◽  
Entropy Model ◽  
Global Issues ◽  
Susceptibility Maps ◽  
Digital Elevation ◽  
Elevation Model ◽  
Color Composite

Soil erosion represents one of the most important global issues with serious effects on agriculture and water quality, especially in developing countries, such as Ethiopia, where rapid population growth and climatic changes affect widely mountainous areas. The Meskay catchment is a head catchment of the Jemma Basin draining into the Blue Nile (Central Ethiopia) and is characterized by high relief energy. Thus, it is exposed to high degradation dynamics, especially in the lower parts of the catchment. In this study, we aim at the geomorphological assessment of soil erosion susceptibilities. First, a geomorphological map was generated based on remote sensing observations. In particular, we mapped three categories of landforms related to (i) sheet erosion, (ii) gully erosion, and (iii) badlands using a high-resolution digital elevation model (DEM). The map was validated by a detailed field survey. Subsequently, we used the three categories as dependent variables in a probabilistic modelling approach to derive the spatial distribution of the specific process susceptibilities. In this study we applied the maximum entropy model (MaxEnt). The independent variables were derived from a set of spatial attributes describing the lithology, terrain, and land cover based on remote sensing data and DEMs. As a result, we produced three separate susceptibility maps for sheet and gully erosion as well as badlands. The resulting susceptibility maps showed good to excellent prediction performance. Moreover, to explore the mutual overlap of the three susceptibility maps, we generated a combined map as a color composite where each color represents one component of water erosion. The latter map yields useful information for land-use managers and planning purposes.

scholarly journals MORPHOMETRIC CHARACTERIZATION OF THE HYDROGRAPHIC BASIN OF JAUQUARA RIVER IN THE TRANSITION BETWEEN THE CERRADO AND AMAZON BIOMES IN MATO GROSSO-BRAZIL

FLORESTA ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 325
Author(s):  
Gabriel Americo Cassettari ◽  
Tadeu Miranda De Queiroz
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Mato Grosso ◽  
Digital Elevation ◽  
Circularity Index ◽  
Elevation Model ◽  
Basin Area ◽  
Morphometric Characterization ◽  
Effective Water ◽  
Unpublished Information

This study aimed to perform the Jauquara river watershed morphometric characterization. To watershed delimitation was used SRTM 30 type Digital Elevation Model (Shuttle Radar Topography Mission, with spatial resolution of 30 m) provided by USGS Earth Explorer platform. The geographic information system used to watershed delimitation process and maps generation was ArcGIS 10.1 from ESRI®. The morphometric variables calculus was based on classic methodologies of Applied Hydrology. The watershed has an area of 1408,03 km2 and perimeter of 288,43 km with compactness coefficient and circularity index of Kc = 2.15 and Ic = 0.21, respectively, which show an elongated shape. The drainage was classified as 5th order, reinforcing the configuration of the drainage network with a wide hydric distribution. The predominant altitude range is between 368 and 552 m, which corresponds to an area of 478.10 km2. It was observed that there is a predominance of smooth-wavy and undulated reliefs (3-8%, 8-20% slope), which correspond to 38,05% and 23,04% of the total basin area respectively. The morphometric characterization of the basin made it possible to obtain unpublished information that contributes to the decision making regarding the effective water management in the studied area, being this a guiding study for other works

scholarly journals Soil Moisture Estimation Using Citizen Observatory Data, Microwave Satellite Imagery, and Environmental Covariates

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2160
Author(s):  
Daniel Kibirige ◽  
Endre Dobos
Keyword(s):  
Soil Moisture ◽  
Expert Knowledge ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Regression Kriging ◽  
Environmental Covariates ◽  
Observatory Data ◽  
Digital Elevation ◽  
Elevation Model

Soil moisture (SM) is a key variable in the climate system and a key parameter in earth surface processes. This study aimed to test the citizen observatory (CO) data to develop a method to estimate surface SM distribution using Sentinel-1B C-band Synthetic Aperture Radar (SAR) and Landsat 8 data; acquired between January 2019 and June 2019. An agricultural region of Tard in western Hungary was chosen as the study area. In situ soil moisture measurements in the uppermost 10 cm were carried out in 36 test fields simultaneously with SAR data acquisition. The effects of environmental covariates and the backscattering coefficient on SM were analyzed to perform SM estimation procedures. Three approaches were developed and compared for a continuous four-month period, using multiple regression analysis, regression-kriging and cokriging with the digital elevation model (DEM), and Sentinel-1B C-band and Landsat 8 images. CO data were evaluated over the landscape by expert knowledge and found to be representative of the major SM distribution processes but also presenting some indifferent short-range variability that was difficult to explain at this scale. The proposed models were evaluated using statistical metrics: The coefficient of determination (R2) and root mean square error (RMSE). Multiple linear regression provides more realistic spatial patterns over the landscape, even in a data-poor environment. Regression kriging was found to be a potential tool to refine the results, while ordinary cokriging was found to be less effective. The obtained results showed that CO data complemented with Sentinel-1B SAR, Landsat 8, and terrain data has the potential to estimate and map soil moisture content.

Soil Erosion Research Based on RS and USLE in Great Khinggan

2013 ◽  
Vol 864-867 ◽  
pp. 2799-2803
Author(s):  
Wei Li ◽  
Wen Yi Fan ◽  
Xue Gang Mao ◽  
Lin Zhao
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Grid Cell ◽  
Strength Distribution ◽  
Space Distribution ◽  
Digital Elevation ◽  
Erosion Area ◽  
Elevation Model ◽  
Volume Estimates ◽  
Cell Data

Uses 2011 years TM/ETM images classification were land uses/cover type figure, combination Great Khinggan area digital elevation model (DEM), and soil type distribution figure and research regional rainfall information, we got all factors values of space distribution in the USLE model, got soil erosion volume estimates data and soil erosion strength distribution figure based on grid cell data. Result indicate that the micro-absolute percentage of erosion throughout the study area, with increasing slope, area of erosion and erosion gradually reduce trend increases with the elevation increases, reduced erosion area after, generally good soil and water conservation in the region.

scholarly journals LANDSLIDE SUSCEPTIBILITY MODELLING IN SELECTED STATES ACROSS SE. NIGERIA

2020 ◽  
Vol 4 (1) ◽  
pp. 23-27
Author(s):  
R. O. E. Ulakpa ◽  
V.U.D. Okwu ◽  
K. E. Chukwu ◽  
M. O. Eyankware
Keyword(s):  
Landslide Susceptibility ◽  
Landsat Imagery ◽  
Control Measures ◽  
Landslide Risk ◽  
Susceptibility Map ◽  
Landsat 8 ◽  
Aerial Photos ◽  
Anambra State ◽  
Digital Elevation ◽  
Elevation Model

Identification and mapping of landslide is essential for landslide risk and hazard assessment. This paper gives information on the uses of landsat imagery for mapping landslide areas ranging in size from safe area to highly prone areas. Landslide mitigation largely depends on the understanding of the nature of the factors namely: slope, soil type, lineament, lineament density, elevation, rainfall and vegetation. These factors have direct bearing on the occurrence of landslide. Identification of these factors is of paramount importance in setting out appropriate and strategic landslides control measures. Images for this study was downloaded by using remote sensing with landsat 8 ETM and aerial photos using ArcGIS 10.7 and Surfer 8 software, while Digital Elevation Model (DEM) and Google EarthPro TM were used to produce slope, drainage, lineament and elevation. From the processed landsat 8 imagery, landslide susceptibility map was produced, and landslide was category into various class; low, medium and high. From the study, it was observed that Enugu and Anambra state ranges from high to medium in terms of landslide susceptibility, Imo state ranges from medium to low.

scholarly journals Soil use and occupation in Caracol Settlement: a multitemporal assessment using remote sensing and geoprocessing techniques

2020 ◽  
Vol 9 (12) ◽  
pp. e30891211029
Author(s):  
Odemir Coelho da Costa ◽  
José Francisco dos Reis Neto ◽  
Ana Paula Garcia Oliveira
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Soil Cover ◽  
The United States ◽  
United States Geological Survey ◽  
Vegetation Landscape ◽  
Digital Elevation ◽  
Elevation Model ◽  
Gis Software

This study focused on the application of remote sensing and geoprocessing techniques to quantify the agroecological use of Caracol settlement area in order to quantify the vegetated areas, as well as the use and occupation of the soil in the years 2000, 2010 and 2020, in the months of May of each year. To achieve the objectives, computational tools (Quantum GIS software) were used, as well as data from Landsat 5 and 8 satellites, bands 3 and 4, 4 and 5 respectively. Vector data from the database of the Brazilian Institute of Geography and Statistics (IBGE), a Digital Elevation Model (DEM), from the United States Geological Survey (USGS/NASA) for evaluation of the watersheds were also used. For vegetation analysis, as well as temporal evolution, the Normalized Difference Vegetation Index (NDVI) was used, with this it was possible to evaluate by means of thematic maps and tables containing the quantification and classification of vegetation and soil cover. It was evident in the present study that there were significant changes in the vegetation landscape over two decades, through anthropic activity by settled families, that were responsible for such changes in the use and soil cover of Caracol settlement.

scholarly journals Identification and mapping of soil erosion areas in the Blue Nile-Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model

2010 ◽  
Vol 7 (1) ◽  
pp. 135-177
Author(s):  
M. El Haj Tahir ◽  
A. Kääb ◽  
C.-Y. Xu
Keyword(s):  
Soil Erosion ◽  
Thermal Emission ◽  
Land Use Changes ◽  
Shuttle Radar Topography Mission ◽  
Arid Ecosystems ◽  
Spatial And Temporal Variability ◽  
Blue Nile ◽  
Digital Elevation ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Elevation Model

Abstract. This paper is part of a set of studies to evaluate the spatial and temporal variability of soil water in terms of natural as well as land-use changes as fundamental factors for vegetation regeneration in arid ecosystems in the Blue Nile-Sudan. The specific aim is to indicate the spatial distribution of soil erosion caused by the rains of 2006. The current study is conducted to determine whether automatic classification of multispectral Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) imagery could accurately discriminate erosion gullies. Shuttle Radar Topography Mission (SRTM) is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gullies, Flat_Land, Mountains and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007, and using drainage network analysis of SRTM digital elevation model. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently the results were up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS) images of the same dates. Because the selected study site is representative of the wider Blue Nile province, it is expected that the approach presented could be applied to larger areas.

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