摘要
Aiming at alleviating the serious soil erosion, the Chinese government initiated the Sloping Land Conversion Program （SLCP） in 1999. Now; after 8 years of project implementation, the ecological recovery effects of the SLCP have become the hot issue of academic circle. This paper; raking the loess hill and gully area of northern Shaanxi as an example, presents a methodology for assessing the vegetation restoration effect of SLCP with normalized difference vegetation index （NDVI）. The key components include calculation of the Growing Season NDVI （GSNDVI）, and estimation of the NVDI change induced by climate and SLCP, respectively. Based on the method, the NDVI change between 2000 and 2006 was obtained using the GSNDVI that excluded the noise from snow and ice. After the part of total NDVI change caused to： climate variation was estimated using empiric formulae, we obtained the part induced by human factors, i.e. the SLCP The human induced part of ND VI change was considered as an approximation indicating the effect of the SLCP on the vegetation. Finally, we analyzed the ND VI change characters of the whole study area, different slope lands and different land use types by spatial statistics method. Results show that the vegetation condition is significantly improved by the SLCP, particularly land types that directly involved in the SLCP, such as steeply slope farmlands, degraded grasslands, etc.
Aiming at alleviating the serious soil erosion, the Chinese government initiated the Sloping Land Conversion Program (SLCP) in 1999. Now, after 8 years of project implementation, the ecological recovery effects of the SLCP have become the hot issue of academic circle. This paper, taking the loess hill and gully area of northern Shaanxi as an example, presents a methodology for assessing the vegetation restoration effect of SLCP with normalized difference vegetation index (NDVI). The key components include calculation of the Growing Season NDVI (GSNDVI), and estimation of the NVDI change induced by climate and SLCP, respectively. Based on the method, the NDVI change between 2000 and 2006 was obtained using the GSNDVI that excluded the noise from snow and ice. After the part of total NDVI change caused by climate variation was estimated using empiric formulae, we obtained the part induced by human factors, i.e. the SLCP. The human induced part of NDVI change was considered as an approximation indicating the effect of the SLCP on the vegetation. Finally, we analyzed the NDVI change characters of the whole study area, different slope lands and different land use types by spatial statistics method. Results show that the vegetation condition is significantly improved by the SLCP, particularly land types that directly involved in the SLCP, such as steeply slope farmlands, degraded grasslands, etc.
基金
supported by National Natural Science Foundation of China (Grant No.40671007)
Major Projects of Knowledge In-novation Program of the Chinese Academy of Sciences (Grant No.KZCX2-YW-421)
