Remote sensing monitoring of grass growing in grassland ecosystems of China

Liping Lu; Zhihao Qin; Bin Xu; Weiguo Tao; Lipeng Jiang

doi:10.1117/12.760772

26 July 2007 Remote sensing monitoring of grass growing in grassland ecosystems of China

Liping Lu, Zhihao Qin, Bin Xu, Weiguo Tao, Lipeng Jiang

Proceedings Volume 6752, Geoinformatics 2007: Remotely Sensed Data and Information; 675225 (2007) https://doi.org/10.1117/12.760772
Event: Geoinformatics 2007, 2007, Nanjing, China

Abstract

Grassland degradation in grassland ecosystems of China has been highly concerned in recent decades. Grassland growing is an important element for identification of grassland degradation. In this paper we intend to develop an applicable method for grassland growing monitoring in China using the EOS/MODIS data. Firstly the normalized difference of vegetation index (NDVI) can be calculated from April to October within grassland growing period in 2005 and 2006. In order to evaluate the grassland growing, vegetation index R was proposed, which was calculated from the NDVI value difference of the two years 2006 and 2005. According to the R value, five grades (from grade1 to grade5) were obtained: worse, slightly worse, balance, slightly better and better. Grassland region in China can be divided into a number of small sub-regions for determination of different regions and grassland types. Our results indicate that grassland growing was better in 2006 than in 2005. The grassland with balance, slight better and better growing accounted for 71.43% of the total grassland area, the area is 251.42 thousand KM². The overall growing of 2006 is: Grade3>Grade4>Grade2>Grade5>Grade1.Valuation of the grassland growing is thus urgently required for better administration of the grassland ecosystem for sustainable development.

Citation Download Citation

Liping Lu, Zhihao Qin, Bin Xu, Weiguo Tao, and Lipeng Jiang "Remote sensing monitoring of grass growing in grassland ecosystems of China", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 675225 (26 July 2007); https://doi.org/10.1117/12.760772

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