scholarly journals Applicability of Satellite Remote Sensing for Mapping Hazardous State of Land Degradation by Soil Erosion on Agricultural Areas

2015 ◽  
Vol 24 ◽  
pp. 29-34 ◽  
Author(s):  
Satoshi Uchida
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Land Degradation ◽  
Satellite Remote Sensing ◽  
Agricultural Areas ◽  
Hazardous State

scholarly journals MODELLING AND MAPPING OF SOIL EROSION ON THE OUED EL MALLEH CATCHMENT USING REMOTE SENSING AND GIS

2013 ◽  
pp. 302-307
Author(s):  
Omar El Aroussi
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Land Degradation ◽  
Soil Loss ◽  
Land Use Changes ◽  
Field Studies ◽  
Water Volume ◽  
Water Storage Capacity ◽  
Rusle Model

In Morocco, the spectacular expansion of erosive processes shows increasingly alarming aspects. Due to the considerable costs of detailed ground surveys for studying this phenomenon, remote sensing is an appropriate alternative for analyzing and evaluating the risks of the expansion of soil degradation. According to an FAO study (2001), Erosion threatens 13 million ha of cropland and rangeland in northern Morocco and induces an estimated average water storage capacity loss of 50 million m3 each year through dam silting. The lost water volume could potentially be used to irrigate 5000 to 6000 ha / year. This study analyses soil erosion on the Oued El Malleh catchment, a 34 km2 catchment located in the north of Fez (Morocco). This contribution aims at mapping the spatio-temporal evolution of land use and modelling the erosion and sedimentation processes using the well known RUSLE model. Land use changes were assessed using Landsat-5 TM and Landsat-7 ETM+ images, from the 1987-2011 periods which were validated by field studies. The images were first georeferenced and projected into the Moroccan coordinate system (Merchich North) then processed to evaluate soil loss through a GIS package (Idrisi Andes Software). These static assessments of soil loss were then used in a deposition/sedimentation algorithm to model soil loss propagation to the downstream. The soil loss averages determined by the model vary between 1.09 t/ha/yr as a minimum value for the reforested lands and 169.4 t/ha/yr as a maximum value for the uncultivated lands (badlands). The latter generally correspond to Regosols or low protected soils located on steep slopes. In comparison with RUSLE, the sedimentation model yields lower values of soil losses; only 97.3 t/h/year for the uncultivated lands, and -0.34 t/ha/year in the reforested land, indicating an on-going sedimentation process. By taking into account the temporal variability of erosion and deposition jointly lower values of soil erosion are calculated by the RUSLE model. However, despite this decline, land degradation problems are still important due to the combination of land use and local lithology. The results of this study were used to indentify areas where interventions are needed to limit land degradation processes.

Assessment and Monitoring of Soil Erosion Risk and Land Degradation in Arable Land Combining Remote Sensing Methodologies and RUSLE Factors

2021 ◽  
pp. 704-716
Author(s):  
Biagio Tucci ◽  
Gabriele Nolè ◽  
Antonio Lanorte ◽  
Valentina Santarsiero ◽  
Giuseppe Cillis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Land Degradation ◽  
Arable Land ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Assessment And Monitoring

A METHODOLOGY FOR MAPPING AND MONITORING CROPLAND SOIL EROSION

1987 ◽  
Vol 67 (3) ◽  
pp. 433-444 ◽  
Author(s):  
JOSEF CIHLAR
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Satellite Remote Sensing ◽  
Field Evaluation ◽  
Rill Erosion ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Long Term Trends ◽  
Remote Sensing Techniques

A methodology is described for mapping and monitoring the erosion of soil by water, using remote sensing techniques and the universal soil loss equation as the primary tools. Four aspects are covered: mapping baseline sheet and rill erosion, monitoring actual rill and gully erosion, estimating changes in potential sheet and rill erosion, and determining long-term trends. A successful field evaluation of the methodology was undertaken in a potato-growing area of New Brunswick. The implementation of the procedure using state-of-the-art microcomputer and satellite remote sensing technology is proposed. Key words: Soil erosion, remote sensing, geographic information systems

scholarly journals IDENTIFICATION AND MAPPING OF HOT SPOT AREAS SUSCEPTIBLE TO SOIL EROSION IN ERAK AL KARAK AREA USING GEOINFORMATICS

2018 ◽  
Vol 6 (6) ◽  
pp. 246-259
Author(s):  
Safa Mazahreh ◽  
Mohammad Alkharabsheh ◽  
Majed Bsoul ◽  
Doaa Abu Hammor ◽  
Lubna Al Mahasneh
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Degradation ◽  
Land Use Planning ◽  
Soil Loss ◽  
Hot Spot ◽  
Gis Tools ◽  
Areas Of Interest ◽  
Agricultural Areas ◽  
The Impact

Jordan is a country dominated by arid climate and fragile ecological system, where 91% is classified as arid land with annual average rainfall rarely exceeds 200 mm/y. Therefore, land degradation, soil erosion and desertification are important areas of interest, where soil erosion is considered one of the major causes for land degradation in Jordan. The main objective of this study is to create an erosion hazard map and identify the areas susceptible to soil erosion in Erak Al karak watershed in southern part of Jordan. Soil erosion model RUSLE with the integration of GIS tools has been developed to estimate the annual soil loss. The estimated mean annual soil loss is (38.7 ton/ ha/year). The erosion map produced highlighted the hot spot areas susceptible to soil erosion. A relationship was obvious between terraces land use and soil loss, where 22% of the soil loss was reduced by applying soil conservation technique (terraces). According to this model, most of the hot spot areas are located in the rangeland 63% while the agricultural areas are responsible for 14% of the hot spot areas. The results emphasis the importance of urgent land use planning and conservation practices to reduce the impact of soil erosion.

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