Share Email Print
cover

Proceedings Paper

Study on models for monitoring of above ground biomass about Bayinbuluke grassland assisted by remote sensing
Author(s): Anming Bao; Xiaoming Cao; Xi Chen; Yun Xia
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Using the CBERS data in August,2005 and the corresponding measured grass yield data from 15 samples in the region of Bayinbuluke grassland, we established the monadic linear regression models the non-linear regression models and the logarithm models to express the relationship between grassland aboveground biomass and the Vegetation Index(VI). The results showed that: 1)there were close relation between the VI and grassland aboveground biomass: 2) the comparison of different forms showed that the logarithm equation was the best one in terms of the suitability of use in study area: 3) the results from the non-linear regression analysis showed that the order was MSAVI NDVI LAI and SAVI in terms of the fitting accuracy between these VI and grassland aboveground biomass data: 4) the non-linear regression Y=-1242.2MSAVI3+6254.1MSAVI2-10044MSAVI+5267 was the best model which could be used in monitoring grassland biomass based on the VI Bayinbuluke grassland.5) the calculated results were as follows: the total aboveground biomass of Bayinbuluke in 2005 was 1.23x104t; the total biomass of high grass was 8.82×103t and the density was 116.14g/m2;the total biomass of low grass was 2.04x103t and the density was 70.33g/m2 the total biomass of swampland was 1.30x103t and the density was 122.36g/m2 Keywords Remote Sensing, vegetation index(VI), grassland, aboveground biomass, Bayinbuluke

Paper Details

Date Published: 10 September 2008
PDF: 9 pages
Proc. SPIE 7083, Remote Sensing and Modeling of Ecosystems for Sustainability V, 70830R (10 September 2008); doi: 10.1117/12.791724
Show Author Affiliations
Anming Bao, Beijing Normal Univ. (China)
Xinjiang Institute of Ecology and Geography (China)
Xiaoming Cao, Xinjiang Institute of Ecology and Geography (China)
Graduate School, Chinese Academy of Sciences (China)
Xi Chen, Xinjiang Institute of Ecology and Geography (China)
Yun Xia, Xinjang Institute of Ecology and Geography (China)
Graduate School, Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 7083:
Remote Sensing and Modeling of Ecosystems for Sustainability V
Wei Gao; Hao Wang, Editor(s)

© SPIE. Terms of Use
Back to Top