OBTAINING SPATIAL AND TEMPORAL VEGETATION DATA FROM LANDSAT MSS AND AVHRR/NOAA SATELLITE IMAGES FOR A HYDROLOGIC MODEL

Abstract

This research describes how to obtain spatial and temporal vegetation data over a watershed from satellite images for use in a hydrologic model. Spatial vegetation data were obtained by classifying Landsat Multispectral Scanner (MSS) images into vegetation types. Temporal vegetation data were obtained by a series of Normalized Difference Vegetation Index (NDVI) images from Advanced Very High Resolution Radiometer/National Oceanic and Atmospheric Administration (AVHRR/NOAA) satellite images. An empirical vegetation model was developed to relate vegetation parameter Leaf Area Index (LAI) to the NDVI data. The obtained spatial and temporal vegetation data were used in a hydrologic model to model hydrologic processes of the Mud Creek watershed in south-central Oklahoma. The research results show that the vegetation data obtained from the satellite imagery are more realistic than those obtained from a crop growth model. The accuracy of modeled monthly and annual runoff using vegetation data from the satellite images is improved by about 13 and 5 percent, respectively, compared with the hydrology using the crop growth model.