Land-cover characterization and change detection using multitemporal MODIS NDVI data

Abstract

Land-cover (LC) composition and conversions are important factors that affect ecosystem condition and function. These data are frequently used as a primary data source to generate landscape-based metrics to assess landscape condition at multiple assessment scales. The use of satellite-based remote sensor data has been widely applied to provide a cost-effective means to develop LC coverages over large geographic regions. Past and ongoing efforts for generating LC data for the United States have been implemented using an interagency consortium to share the substantial costs associated satellite data acquisition, processing and analysis. The first moderate resolution National Land-Cover Data (NLCD) set was developed for the conterminous United States using Landsat Thematic Mapper (TM) imagery collected between1991-1992 (Vogelmann et al., 1998). Currently, the 2001 NLCD is under development for all 50 States and the Commonwealth of Puerto Rico (Homer et al., 2004). The 2001 effort, building on the lessons learned from the 1991 NLCD, promises to provide a relatively high quality baseline LC product.