Research on Vegetation Ecologic Quality Index of Rocky Desertification in Karst Area of Guangxi Province Based on NPP and Fractional Vegetation Cover Since 2000
Karst rocky desertification is a kind of special and complicated surface form. Study established the Net primary productivity (NPP) estimation model based on the use of solar energy utilization of remote sensing data model in rocky desertification region of Guangxi province and the fractional vegetation cover (VFC) is obtained by the method of sub-pixel decomposition model. The comprehensive analysis method was used to establish vegetation ecologic quality index by using NPP and fractional vegetation cover to monitor the Rocky Desertification in the study area from 2000 to 2016, and mapping vegetation ecologic quality index grade classification. Results show that: (1) In 2016, vegetation ecologic quality index in rocky desertification region of Guangxi province is 87.6, the highest since 2000. Hechi city is the best in Guangxi Province. (2) From 2000 to 2016, vegetation ecologic quality index annual growth has a 1.04, the highest is 87.6 (in 2016) and the lowest is 63 (in 2004). The ecological restorations and environmental control projects have achieved remarkable results. (3) Great grade, Good grade and normal grade areas can account for 94.5%. And vegetation ecologic quality index decreased obviously in some relative development regions, such as Guilin city and Hezhou city.
KeywordsKarst rocky desertification Vegetation ecologic quality index NPP Fractional vegetation cover
This research was supported by Special Fund for meteorological scientific Research in the Public Interest (GYHY201506017). Sincerely thanks are also due to Guangxi Climate center and National Satellite Meteorology Center for providing the data for this study.
- Chhabra, A., Dadhwal, V.K.: Estimating terrestrial net primary productivity over India using satellite data. Curr. Sci. 86(2), 269 (2004)Google Scholar
- Foster, I., Kesselman, C.: The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (1999)Google Scholar
- Kumar, M., Monteith, J.L.: Remote sensing of crop growth. In: Smith, H. (ed.) Plants and the Daylight Spectrum, pp. 133–144. Academic Press, London (1981)Google Scholar
- Nemani, R., Running, S.W., Band, L.E., Peterson, D.L.: Regional hydroecological simulation system: an illustration of the integration of ecosystem models in a GIS. In: Goodchild, M.F., Parks, B.O., Steyaert, L.T. (eds.) Environmental modeling with GIS, pp. 296–304. Oxford University Press, New York (1993)Google Scholar
- Panigrahy, R.K., Panigrahy, S., Parihar, J.S.: Spatiotemporal pattern of agro ecosystem net primary productivity of India: a preliminary analysis using spot VGT data. In: International Symposium on Geospatial Databases for Sustainable Development, Goa, vol. 36, part 4, pp. 724–729 (2004)Google Scholar
- Sabbe, H., Veroustraete, F.: Estimation of net primary and net ecosystem productivity of European terrestrial ecosystems by means of the C-Fix model and NOAA/AVHRR data. In: VEGETATION 2000 Conference, 2 Years of Operation to Prepare the Future, pp. 95–99. Space Application Institute, Joint Research Center, 21020 Ispra, Varese-Italy (2000)Google Scholar