Mapping leaf area index for the urban area of Nanjing city, China using IKONOS remote sensing data

The Leaf Area Index (LAI) is key feature to describe the forest ecophysiological processes. In previous studies, LAI was retrieved using remote sensing data mostly in rural areas. The objective of this study was to investigate the possibility of mapping LAI in the urban areas of Nanjing, China using high resolution remote sensing data. LAI measured with the TRAC instruments was used in conjunction with processed IKONOS remote sensing data to develop the empirical function for mapping regional LAI. Among four vegetation index (NDVI, SR, ARVI and SAVI), NDVI is the best predictor of LAI in the study areas. The generated LAI map demonstrated a distinct spatial pattern of LAI, with LAI being high in Zijin mountain, Qingliang mountain, and Yuhua Tai. Streets with aged trees also have relatively high LAI values. This study indicate that the feasibility of mapping LAI in urban areas with high resolution remote sensing data.