Vegetation Coverage Monitoring in Mu-us Sandy Land Based on Multiscale Remote Sensing Data-A Case Study of Yanchi County, Ningxia
Zhen Bian, Wanxue You, Dian Yu, Kebin Zhang, Limeng Meng, Jin Chang
Available Online July 2016.
- https://doi.org/10.2991/iccia-17.2017.73How to use a DOI?
- Digital image, Multiscale remote sensing data, Vegetation coverage, and Dynamic monitor.
- Due to the sparse and irregular distribution of vegetation in desertification area, the Low inversion precision of vegetation coverage and its change using single satellite remote sensing data become the bottleneck of further exploration of ecological evolution in this region. In order to improve the retrieval accuracy of vegetation coverage in desertification area, this article inverses and dynamic monitors the vegetation coverage of Mu Us Sandy Land in north of Yanchi County combining multi-source data include digital image, Landsat TM and MODIS-NDVI using scale conversion and two pixel model. The results showed that: (1) Vegetation information based on NDVIDC (normalized difference vegetation index based on digital camera) was accurately extracted with the classification accuracy up to 94.3%, which provided a convenient and accurate method for ground survey and remote sensing revise of the vegetation coverage. (2) Vegetation coverage significantly increased after grain to green program and grazing prohibition measures in Yanchi county since the beginning of 2000-2002. (3) The method of vegetation coverage inversion based on multi-source remote sensing information provides a new reference for rapid and efficient vegetation monitoring in desertification areas.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Zhen Bian AU - Wanxue You AU - Dian Yu AU - Kebin Zhang AU - Limeng Meng AU - Jin Chang PY - 2016/07 DA - 2016/07 TI - Vegetation Coverage Monitoring in Mu-us Sandy Land Based on Multiscale Remote Sensing Data-A Case Study of Yanchi County, Ningxia BT - 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/iccia-17.2017.73 DO - https://doi.org/10.2991/iccia-17.2017.73 ID - Bian2016/07 ER -