Spatiotemporal evolution of environment based on integrated remote sensing indexes in arid inland river basin in Northwest China.
Arid inland river basin has been regarded as environmental vulnerable and an important protective area in northwest China. Shiyang River Basin (SRB) is one of the most typical areas in arid inland rivers basin in China. The environmental quality evaluation of different periods is significant for environmental control and management of SRB. In this paper, the normalized differential vegetation index (NDVI), wetness index (WI), albedo, index-based built-up index (IBI), salinization index (SI), and land surface temperature (LST) were obtained through Landsat TM and OLI images in 1995, 2000, 2005, 2010, and 2016. Besides, three methods including spatial principal component analysis (SPCA), analytic hierarchy process (AHP), and remote-sensing spatial distance model (RSSDM) were compared to select a reasonable method for environmental evaluation. The AHP method was determined as the final method for objectively evaluating spatiotemporal changes of environment from 1995 to 2016 in SRB. The results showed that the environment deteriorated in 1995-2000 and improved in 2000-2016. The effect of environmental governance was significant in 2010-2016 because of the longtime environmental management between multiple departments. The results indicated that the environmental quality of SRB was generally improved from 1995 to 2016. We found that the improvement areas were mainly concentrated in the oasis and marginal areas, while environmental damage areas were mainly distributed in the urban regions. However, in most areas of the SRB, the environment was still below average level of China, and the roads of the environment management still had a long way to go. We found that spatiotemporal pattern analysis of the environment was of great importance for the formulation of plans for development of this basin and environmental protection measures.
['Wei|Wei|W|', 'Guo|Zecheng|Z|', 'Xie|Binbin|B|', 'Zhou|Junju|J|', 'Li|Chuanhua|C|']
D002681:China D003247:Conservation of Natural Resources D058998:Remote Sensing Technology D045483:Rivers
Environment AHP Spatiotemporal changes Remote-sensing indexes The middle-lower of SRB