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Proceedings Paper

Applications of 3S technologies for estimating grassland yields in China
Author(s): Jianlong Li; Tiangang Liang; Ping Jiang
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Paper Abstract

Using green herbage yields, environment and remote sensing (RS) data observed in different grassland types in Fukang County, Xinjiang from 1994 to 1997, the correlation analysis, and estimating grassland yield methods were studied by RS technology and global positioning system (GPS) and geographic information system (GIS) integration (3S). The methods of processing images, analyzing information and linking of RS data with ground grassland data were explored in the paper. The results showed that there existed an obvious correlation between fresh or dry herbage yields and ratio vegetation index (RVI) and normalized difference vegetation index (NDVI) (P less than 0.01) in four grassland types, the correlation coefficients (r) were above 0.679 and passed the F and accuracy test. The results also found that the correlation between fresh or dry grassland yields, and RVI were better than those by NDVI in type II, III and IV, and on the contrary in type I. The optimum nonlinear optical and satellite remote sensing estimating, and forecasting yield models were made from six curve types, the estimating yield accuracies using nonlinear models were better than those using linear models (r equals 0.679 to approximately 0.984 VS r equals 0.479 to approximately 0.722), and the effects were checked by the real observing yields and statistics, the ecological interpretations of the results were given, the total accuracies of the 3S estimating and forecasting green yields were above 75% over large areas, and the objectives were realized by the 3S and grassland expert system integration.

Paper Details

Date Published: 19 August 1998
PDF: 11 pages
Proc. SPIE 3504, Optical Remote Sensing for Industry and Environmental Monitoring, (19 August 1998); doi: 10.1117/12.319519
Show Author Affiliations
Jianlong Li, Lanzhou Univ. (China)
Tiangang Liang, Gansu Grassland Ecological Research Institute (China)
Ping Jiang, Xinjiang Normal Univ. (China)


Published in SPIE Proceedings Vol. 3504:
Optical Remote Sensing for Industry and Environmental Monitoring
Upendra N. Singh; Huanling Hu; Gengchen Wang, Editor(s)

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