Abstract

Eco-environment change, as one of the key impacts of the urbanization and economy development, has taking place at an unprecedented rate around China in the past few decades. This paper explores the method of comprehensive assessment of extracted eco-environmental factors and sets up an assessment model applying the eco-environment assessment method. Understanding the change of eco-environment on county level city is crucial for improving the ecology and sustainability for Jiangxi province, in the undeveloped areas in central China. With the aid of an integrated GIS/RS-based approach, this study investigated how many ecological factors would affect eco-environmental change in the Ruijin, a county level city in the region of Jiangxi province, based on the analysis of land surface temperature (LST), normalized difference vegetation index (NDVI), vegetation fraction (Fv), tasseled cap brightness (TCB) considered as soil brightness, tasseled cap wetness (TCW) considered as soil wetness, DEM and Slope. Three Landsat TM images acquired on November 2, 2000, November 3, 2006 and January 14, 2010 were used to estimate LST, NDVI, Fv, TCB and TCW. These data in the new form were then combined with the extracted eco-environment key factors by way of re-projection to form comprehensive image.Our results have showed that, although there are significant variations in LST at a given fraction of vegetation on a per-pixel basis, NDVI, Fv, TCB and TCW are all good predictors of eco-environment on the regional scale. In north, southeast of the study area, the quality of eco-environment assessment is generally better than the other region, such as central and west directions. Meanwhile the place out of the central urban area, special in the northwest, due to the high altitude, less human intervention, eco-environment in most of these regions is good. Thus, it shows that quality of the eco-environment assessment in Ruijin city is conformable with the actual situation and feasible. Finally, the quality of eco-environment assessment in Ruijin city was extracted through an RS-based model in the terms of maps and tables.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call