Mapping bare ground in New Zealand hill-country agriculture and forestry for soil erosion risk assessment: An automated satellite remote-sensing method

2022 ◽  
Vol 301 ◽  
pp. 113812
Author(s):  
Heather North ◽  
Alexander Amies ◽  
John Dymond ◽  
Stella Belliss ◽  
David Pairman ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Risk Assessment ◽  
New Zealand ◽  
Soil Erosion ◽  
Satellite Remote Sensing ◽  
Bare Ground ◽  
Erosion Risk ◽  
Hill Country ◽  
Soil Erosion Risk

scholarly journals Terrain Characterization and Soil Erosion Risk Assessment for Watershed Prioritization Using Remote Sensing and GIS (A case study of Nawagaon Maskara Rao Watershed, Saharanpur, India)

2009 ◽  
Vol 23 (1) ◽  
pp. 86
Author(s):  
Beny Harjadi
Keyword(s):  
Remote Sensing ◽  
Risk Assessment ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Remote Sensing And Gis ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Conservation Measures

Soil erosion is crucial problem in India where more than 70% of land in degraded. This study is to establish conservation priorities of the sub watersheds across the entire terrain, and suggest suitable conservation measures. Soil conservation practices are not only from erosion data both qualitative SES (Soil Erosion Status) model and quantitative MMF (Morgan, Morgan and Finney) model erosion, but we have to consider LCC (Land Capability Classification) and LULC (Land Use Land Cover). Study demonstrated the use of RS (Remote Sensing) and GIS (Geographic Information System) in soil erosion risk assessment by deriving soil and vegetation parameters in the erosion models. Sub-watersheds were prioritized based on average soil loss and the area falls under various erosion risk classes for conservation planning. The annual rate of soil loss based on MMF model was classified into five soil erosion risk classes for soil conservation measures. From 11 sub watersheds, for the first priority of the watershed is catchment with the small area and the steep slope. Recommendation for steep areas (classes VI, VII, and VIII) land use allocation should be made to maintain forest functions.

scholarly journals Soil Erosion Estimation Using Remote Sensing Techniques in Wadi Yalamlam Basin, Saudi Arabia

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Jarbou A. Bahrawi ◽  
Mohamed Elhag ◽  
Amal Y. Aldhebiani ◽  
Hanaa K. Galal ◽  
Ahmad K. Hegazy ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Saudi Arabia ◽  
Soil Erosion ◽  
Decision Support Tool ◽  
Data Availability ◽  
Productive Capacity ◽  
Support Tool ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Key Aspects

Soil erosion is one of the major environmental problems in terms of soil degradation in Saudi Arabia. Soil erosion leads to significant on- and off-site impacts such as significant decrease in the productive capacity of the land and sedimentation. The key aspects influencing the quantity of soil erosion mainly rely on the vegetation cover, topography, soil type, and climate. This research studies the quantification of soil erosion under different levels of data availability in Wadi Yalamlam. Remote Sensing (RS) and Geographic Information Systems (GIS) techniques have been implemented for the assessment of the data, applying the Revised Universal Soil Loss Equation (RUSLE) for the calculation of the risk of erosion. Thirty-four soil samples were randomly selected for the calculation of the erodibility factor, based on calculating theK-factor values derived from soil property surfaces after interpolating soil sampling points. Soil erosion risk map was reclassified into five erosion risk classes and 19.3% of the Wadi Yalamlam is under very severe risk (37,740 ha). GIS and RS proved to be powerful instruments for mapping soil erosion risk, providing sufficient tools for the analytical part of this research. The mapping results certified the role of RUSLE as a decision support tool.

Integration of Remote Sensing and GIS for Evaluating Soil Erosion Risk in Northwestern Zhejiang, China

2012 ◽  
Vol 78 (9) ◽  
pp. 935-946 ◽  
Author(s):  
Jianqin Huang ◽  
Dengsheng Lu ◽  
Jin Li ◽  
Jiasen Wu ◽  
Shiquan Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Remote Sensing And Gis ◽  
Erosion Risk ◽  
Soil Erosion Risk

scholarly journals Erosion Modelling In A Mediterranean Subcatchment Under Climate Change Scenarios Using Pan-European Soil Erosion Risk Assessment (PESERA)

2015 ◽  
Vol XL-7/W3 ◽  
pp. 359-365 ◽  
Author(s):  
A. Cilek ◽  
S. Berberoglu ◽  
M. Kirkby ◽  
B. Irvine ◽  
C. Donmez ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Land Use ◽  
Soil Erosion ◽  
Mediterranean Region ◽  
Geographical Information ◽  
Climate Change Scenarios ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
The Mediterranean

The Mediterranean region is particularly prone to erosion. This is because it is subject to long dry periods followed by heavy bursts of erosive rainfall, falling on steep slopes with fragile soils, resulting in considerable amounts of erosion. In parts of the Mediterranean region, erosion has reached a stage of irreversibility and in some places erosion has practically ceased because there is no more soil left. With a very slow rate of soil formation, any soil loss of more than 1 t ha<sup>−1</sup> yr<sup>−1</sup> can be considered as irreversible within a time span of 50-100 years. The objectives of this study were i) to estimate the temporal and spatial distribution of soil erosion under climate change scenarios in study area ii) to assess the hydrological runoff processes. <br><br> In this study, climate data, land use, topographic and physiographic properties were assembled for Egribuk Subcatchment at Seyhan River Basin in Turkey and used in a process-based Geographical Information System (GIS) to determine the hydrological sediment potential and quantify reservoir sedimentation. The estimated amount of sediment transported downstream is potentially large based on hydrological runoff processes using the Pan-European Soil Erosion Risk Assessment (PESERA) model. The detailed model inputs included 128 variables derived mainly from, soil, climate, land use/cover, topography data sets. The outcomes of this research were spatial and temporal distribution of erosion amount in t ha<sup>−1</sup> yr<sup>−1</sup> or month<sup>−1</sup>.

Sign in / Sign up

Export Citation Format

Share Document