Paper
26 October 2013 Quantitative assessment of soil erosion in Shanchonghe watershed supported by RS and GIS
Author Affiliations +
Proceedings Volume 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 89210P (2013) https://doi.org/10.1117/12.2031361
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
The paper gives a quantitative analysis on soil erosion in Shanchonghe watershed. The quantitative analysis is based on a revised universal soil loss equation (RUSLE), supported by geographic information system (GIS) and remote sensing (RS) technology, and according to the landform, rainfall, vegetation data, etc., in Shanchonghe watershed, which are obtained from interpreted data of Shanchonghe watershed RS image and it’s statistics data. The results showed that the annual soil erosion modulus in Shanchonghe watershed is 19.05 t / (hm2*a), the annual soil erosion amount is 2744.23 t/a. The soil erosion spatial distribution is very different. These areas have strong soil erosion, which height is more than 2000 meters above sea level, or which slope is bigger than 25 degree, or bare surfaces, or sloping farmlands. These are the focus areas of governance of soil erosion in Shanchonghe watershed. The study provides scientific basis to water and soil conservation work in Shanchonghe watershed.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuanfeng Zhu and Runyuan Kuang "Quantitative assessment of soil erosion in Shanchonghe watershed supported by RS and GIS", Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89210P (26 October 2013); https://doi.org/10.1117/12.2031361
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Soil science

Vegetation

Remote sensing

Geographic information systems

Soil contamination

Calibration

Quantitative analysis

Back to Top