The potential of spectral indices in detecting various stages of afforestation over the Loess Plateau Region of China

Abstract

China has the greatest afforestation area in the world, mainly due to the implementation of various ecological restoration projects, which have taken place over several decades. However, the progress of these restoration projects has rarely been evaluated through sapling growth monitoring. In this research, we assessed the potential of eighteen spectral indices derived from time-series Landsat data to characterize the different stages of afforestation over the Loess Plateau region. First, we obtained data for the afforestation area from 1997 to 2010. Then we estimated the average year of afforestation that could be uniquely identified and the sensitivity to growth exhibited by each of the indices. The results show that the first shortwave infrared band (SWIR1) of the Landsat Thematic Mapper and the Brightness index from the tasseled cap transformation (TCB) had the fastest response to sapling growth. It takes 4.2 and 4.3 years on average for the saplings to be detected as forest by SWIR1 and TCB, respectively. However, these two indices saturate too soon to allow better distinction of the various stages of sapling growth but are better for monitoring the over-reporting situation. By contrast, the disturbance index (DI), and the normalized burnt ratio (NBR) and the normalized burnt ratio 2 (NBR2) respond slowly to sapling growth and can detect forest at 7.4 years on average. Unlike SWIR1 and TCB, these indices do not saturate early and can provide more detail on the level and structural condition of sapling growth.