Monitoring of desertification in central Asia and western China using long term NOAA-AVHRR NDVI time-series data

Abstract

Taking place and development of desertification in the arid and semiarid regions directly influence the density and growth status of vegetation, making surface vegetation a most important indicator for desertification assessment. The primary purpose of this study was to assess the condition of desertification in central Asia and western China located in arid and semiarid regions. Remote sensing data used in this study were a time-series of 10-day maximum Normalized Difference Vegetation Index (NDVI) composites derived from Global Area Coverage of Advanced Very High Resolution Radiometer (AVHRR) from 1982 to 2000. The coefficient of variation (CoV) of the monthly NDVI (maximum-value composite) was used as a parameter to characterize the changes of vegetation in this work. The CoV can be used to compare the amount of variation in different sets of sample data. Changes in the value of the pixel-level CoV over time can be interpreted as a measure of vegetative biomass change over that time. The method to detect and quantify changes in CoV values for each pixel over a 20-year period for which data were available is based on linear regression. If the CoV values exhibit a statistically significant decrease over time, it is possible to conclude that the area imaged in that pixel is under desertification. The result was validated by comparison of the theoretical results to land cover maps in different years. This experiment demonstrated the feasibility of applying the CoV regression methodology and long term NOAA-AVHRR NDVI time-series data for desertification monitoring in central Asia and western China.