U.S. Department of the Interior U.S. Geological Survey USGS/EROS Data Center Global Land Cover Project – Experiences and Research Interests GLC2000-JRC March 2001

U.S. Department of the Interior U.S. Geological Survey The USGS/IGBP Global Land Cover Database

U.S. Department of the Interior U.S. Geological Survey USGS/IGBP Global Land Cover Database Strategy

U.S. Department of the Interior U.S. Geological Survey Classification Methods l Flexible land cover database l Unsupervised multi-temporal classification of AVHRR NDVI data l Classification implemented on a continent by continent basis l Team interpretation to encourage consistency l External peer review of draft results l Validated IGBP land cover layer

U.S. Department of the Interior U.S. Geological Survey Continents to World – Combine Maps l Set rules for top and middle level classification systems l Describe land cover, vegetation seasonality, structure, and leave longevity consistently l Hold frequent project meetings to review consistency l Accuracy measured separately for each mapping area

U.S. Department of the Interior U.S. Geological Survey Quality of Reference Data is an Important Factor

U.S. Department of the Interior U.S. Geological Survey Global Forest Cover Mapping EROS Data Center FRA % FOREST 100% AG DARK MODEL BRIGHT MODEL Channel 2 (NIR) 100% FOREST AVHRR Channel 1 (Visible) Canopy Density Model

U.S. Department of the Interior U.S. Geological Survey EDC FRA2000 Project: — Estimating density of forest canopy cover …

U.S. Department of the Interior U.S. Geological Survey A New Global Forest Cover Map Improved USGS global land cover database

U.S. Department of the Interior U.S. Geological Survey Current and Future R&D Interests Continue global land cover database research using new coarse/moderate resolution sensors Test new techniques/algorithms Integrate satellite imagery with sampling-based field data Sampling-based field data Focus on attributes, themes that are useful for both science and land management

U.S. Department of the Interior U.S. Geological Survey Land Cover Techniques at EDC Unsupervised classification Decision-tree models Spectral mixture analysis Experimental: Co-kriging, KNN, NN Continued emphasis on database strategy and its improvement Stratification before and after clustering

U.S. Department of the Interior U.S. Geological Survey Example of Tree Canopy Density 0 100%

U.S. Department of the Interior U.S. Geological Survey Spatial Modeling Techniques for Satellite Imagery-Field Data Integration = Spatial models such as KNN, Co-kriging are nonparametric spatial statistics Potential tool for extending field measurements to image data/maps Mapping vegetation structure measured on permanent plots Sample1: U1, V1 at (x1, y1) Sample2: U2, V2 at (x2, y2) Sample3: V3 at (x3, y3) Calculate U0 at (x0, y0)

U.S. Department of the Interior U.S. Geological Survey Key Experimental Vegetation Type and Structure Variables l Biomass l Net primary productivity l Canopy density l Canopy height l Age l Size class l DBH l Vegetation species, types, associations

U.S. Department of the Interior U.S. Geological Survey Summary EDC is committed to continuing its global land cover R&D Working with partners is important for USGS