Characterization of forest types in Northeastern China, using multi-temporal SPOT-4 VEGETATION sensor data

Abstract

In this study, we explored the potential of multi-temporal SPOT-4 VEGETATION (VGT) sensor data for characterization of temperate and boreal forests in Northeastern China. As the VGT sensor has a short-wave infrared (SWIR) band that is sensitive to vegetation, soil moisture and leaf water content, the Normalized Difference Water Index (NDWI) was calculated in addition to the Normalized Difference Vegetation Index (NDVI). A forest map of Northeast China was generated from an unsupervised classification of 25 10-day VGT composite data (NDVI and NDWI) over the period of March 11–20, 1999 to November 11–20, 1999. Seven different forest categories were distinguished from the 1-km spatial resolution VGT data. The VGT forest map was compared to estimates of forest area derived from Landsat 7 Enhanced Thematic Mapper (ETM+) images. There was a good agreement on spatial distribution and area of forest between the VGT product and the TM product, however, the VGT product provided additional information on forest type. Analysis of NDVI and NDWI over the plant growing season allows for the identification of distinct growth patterns between the different forest types. It is evident that VGT data can be used to provide timely and detailed forest maps with limited ancillary data needed. The VGT-derived forest maps could be very useful as input to biogeochemical models (particularly carbon cycle models) that require timely estimates of forest area and type.