The re-normalized differential vegetation index (RNDVI) and ratio vegetation index (RVI) were calculated by using the Landsat 5 TM image data processed with geometric, atmospheric and radiometric calibrations. The natural grassland productivity GIS regression retrieval model was then established by using the above calculated indexes combined with the natural grassland biomass data from field work in the Zulihe River Basin. The accuracy of the indexes were assessed through the model. The results showed the RNDVI had a higher accuracy than RVI, with a correlation coefficient R2=0.939 (P=0.00). The spatial distribution of the natural grassland biomass was uneven across the Zulihe River Basin according to the RNDVI and the retrieved distribution. The vegetation biomass was apparently higher in the southern region than that in the north part. From the perspective of forage availability analysis, the unusable grassland accounted for 53.16% of the total grassland in the Basin while the usable grassland accounted for only 18.16%. The rest of the grassland, accounted for 28.67%, was restrictive usable. The animal husbandry would be limited by the natural grassland productivity and need to rely on livestock breeding to improve the population.
XU Bao-quan
,
LIANG Chang-li
,
CHAI Ding-jian
,
SHI Wen-qun
,
SUN Guo-jun
. Inversion of Natural Grassland Productivity from Remote Sensor Imagery in Zulihe River Basin[J]. Arid Zone Research, 2014
, 31(6)
: 1147
-1152
.
DOI: 10.13866/j.azr.2014.06.25
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