Abstract:

Changting County in Fujian Province is a typical reddish soil erosion region in southeastern China. The county has been called the flame mountains area due to severe soil erosion on barren terrains. After years of ecological restoration, the local ecosystem has been improved remarkably and the barren lands are now covered with forests. This paper used remote sensing techniques to study the fractional vegetation cover (FVC) changes and quantitatively evaluated the effects of ecological restoration in Changting during the period from 2001 to 2013 by using the remote sensing ecological index (RSEI). Two remote-sensing based models for estimating FVC have been compared in order to select a suitable model for the retrieval of the FVC in the study area. One is the commonly-used Linear Spectral Mixture Analysis (LSMA) model, and the other is the LSMA_M model. The LSMA_M is based on the LSMA but with a Normalized Difference Mountain Vegetation Index (NDMVI) derived band added into the model. The comparative analysis confirms that the LSMA_M model has higher accuracy than the LSMA model, indicated by its lower root mean square error and higher correlation with referenced FVC data because the addition of the NDMVI band into the model could eliminate shadow problem caused by topographic relief in the mountainous areas. Therefore, the LSMA_M model was selected to retrieve the FVC in this study. The result indicates that the 13-year effort for treatment of the soil loss in the county has led to a notable increase in county's FVC from 75.1% (2001) to 86.5% (2013). Meanwhile, the RSEI- based analysis also indicates a significant improvement of the county's ecological quality during the same period, because of the increase in RSEI value from 0.750 to 0.787, along with an increase in high-RSEI-level area from 85.83% to 90.59%. Regression analysis between FVC and RSEI suggests that each 10% increment in FVC could raise the RSEI by 10%. This clearly indicates a significant effect of FVC on county's ecological quality.

Key words: fractional vegetation cover, RSEI, Linear Spectral Mixture Analysis, remote sensing, Changting