Monitoring rangeland ground cover vegetation using multitemporal MODIS data

Abstract

The aim of the present research is to monitor changes in herbage production during the grazing season in the Semirom and Brojen regions, Iran, using multitemporal Moderate Resolution Imaging Spectroradiometer (MODIS) data. At first, various preprocessing steps were applied to a topography map. The atmospheric and topographic corrections were applied using subtraction of the dark object method and the Lambert method. Image processing, including false-color composite, principal component analysis, and vegetation indices were employed to produce land use and pasture production maps. Vegetation sampling was carried out over a period of 4 months during June–September 2008, using a stratified random sampling method. Twenty random sampling points were selected, and herbage production was estimated and verified with the double-checking method. Four MODIS data sets were used in this study. The models for image processing and integrating ground data with satellite images were processed, and the resulting images were categorized into seven classes. Finally, the land covers were verified for accuracy. A postclassification analysis was carried out to verify the seven class change detections. The results confirmed that Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) maps had a close relationship with the field data. The indices produced with shortwave infrared bands had a close relationship with field data where the ground cover and yields were high. The R 2 value observed was 0.85. The changes in the pasture vegetation were high during the growing season in more than 90 % of the pastures. During the growing season, most changes in the pastures belonged to class 5 and 2 in the NDVI and SAVI index maps, respectively.