Paper
1 September 2005 Assessment of gully erosion in a semi-arid catchment of the Loess Plateau, China using photogrammetric techniques
Author Affiliations +
Abstract
The semi-arid catchment of the Loess Plateau of China is severely affected by soil erosion as it is revealed by the commonly occurring deep and wide gullies. Recent studies in the loess hill-gully terrain area show Gully erosion have a very significant contribution to total soil loss. Traditionally, gully erosion had been measured using a combination of field survey techniques and analogue, the advances in computing powering digital photogrammatric solution are now offering an affordable and cost effective way of estimating the gully erosion. This paper uses the digital elevation models (DEMs), which constructed from multi-date (1959,1981 and 1999) aerial photographs (1:55000, 1:20000 and 1:35000) as a tool to computing the sediment yield by gully erosion in a small catchment of 9.06 km2 located in the Loess Plateau of China. The High-resolution DEMs (2 m grid) were derived from stereo image pairs separately and analyzed by means of geographical information system techniques. Gully breaklines and borderlines were positioned to measure the gully dynamics and soil loss was estimated from computed gully volumes using soil bulk density, and DEM-measured gully degradation rate was discussed as well. DEM-measurement techniques integrates the soil loss due to overland flow and mass movements and gully deepening, and put forward an improvement to locate the areas within the gullies with higher erosion possibility.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wensheng Hu, Jiyuan Liu, Qiangguo Cai, and Zhiqiang Gao "Assessment of gully erosion in a semi-arid catchment of the Loess Plateau, China using photogrammetric techniques", Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 58841Q (1 September 2005); https://doi.org/10.1117/12.628711
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Digital photography

Soil science

Photography

Head

Data modeling

Geographic information systems

Remote sensing

Back to Top