PE&RS September 1999

Cover Image

The first validated 1-km global land-cover database was developed from satellite remotely sensed data on a continent-by-continent basis using 1992-1993 Advanced Very High Resolution Radiom-eter (AVHRR) data. The global land-cover database, named DISCover, was developed under the auspices of the International Geosphere Biosphere Program by an international team of collaborators, for the purpose of improving the reliability of global-scale environmental assessments. An accuracy assessment of the global map was conducted using a stratified random sample with the interpretation of high-resolution satellite imagery to determine “true” land cover. The results of the accuracy assessment are the focus of this special issue. The special issue cover presents the various elements of the proiect; the DISCover global land-cover product presented in the Goodes Interrupted Homolosine projection, the North America continental land-cover classification, and Landsat Thematic Mapper data corresponding to selected North America validation samples. The land-cover maps were produced by researchers at the U.S. Geological Survey, EROS Data Center (contact Tom Loveland at loveland@usgs.gov). The validation data sets and cover design were prepared by researchers at the University of California, Santa Barbara, Remote Sensing Research Unit (contact Joe Scepan at scepan@geog.ucsb.edu). Project data sets are available at http://lpdaac.usgs.gov/glcc/glcc.asp

Peer-Reviewed Articles (Click the linked titles to see the full abstract)

1011 Introduction to Special Issue (Adobe PDF 421Kb)
Thomas R. Loveland, John E. Estes, and Joseph Scepan

1013 The IGBP-DIS Global 1-Km Land-Cover Data Set DISCover:  A Project Overview
Alan S. Belward, John E. Estes, and Karen D. Kline

The history of the DISCover version 1.0 implementation is described. 

1021 An Analysis of the IGBP Global Land-Cover Characterization Process
Thomas P. Loveland, Zhiliang Zhu, Donald 0. Ohlen, Jessyln F Brown, Bradley C. Reed, and Limin Yang

The methodology, based on unsupervised classification with extensive postclassification refinement, yielded a multi-layer database consisting of eight land-cover data sets, descriptive attributes, and source data. 

1033 Landsat Thematic Mapper Registration Accuracy and its Effects on the IGBP Validation
Gregory J. Husak, Brian C. Hadley, and Kenneth C. McGwire

Research associated with the DISCover validation exercise revealed possible registration errors in the high-resolution data employed. 

1041 Image Interpretation Keys for Validation of Global Land-Cover Data Sets
Melissa Kelly, John E. Estes, and Kevin A. Knight

Research included determination of the most effective band combination, signataure development and application, consistent implementation of a minimum mapping unit, use of signature elements in the evaluation of key use, and development of a product useful for cross applications. 

1051 Thematic Validation of High-Resolution Global Land-Cover Data Sets
Joseph Scepan

Issues of data set sampling design, image geometry and registration, and core sample interpretation procedures are addressed. 

1061 The IGBP DiSCover Confidence Sites and the System for Terrestrial Ecosystem Parameteriza-tion: Tools for Validating Global Land-Cover Data
Douglas Muchoney, Alan Strahler, John Hodges, and Janet LoCastro

The confidence site database has three primary applications: as a set of validation benchmarks for alternate regional or global land-cover classifications emphasizing vegetation attributes, as a secondary information source for studying core sample accuracy issues, and as a source of training and test sites for regional and global supervised classification of coarse-resolution satellite imagery. 

1069 The Global Land-Cover Characteristics Data-base: The Users’ Perspective
Jesslyn F Brown, Thomas R. Loveland, Donald 0.Ohlen, and Zhi-liang Zhu

User suggestions have lead to revision in the database, including label changes, alternative classification schemes, and additional projections for the data.  

1075 The DISCover Validation Image Interpretation Process
Joseph Scepan, Gunter Menz, and Matthew C. Hansen

This exercise demonstrates that Landsat TM and SPOT imagery can be efficiently used to validate high-resolution global land-cover products.

1083 Implications of Land-Cover Misclassification for Parameter Estimates in Global Land-Surface Models: An Example from the Simple Biosphere Model (SiB2)
R.S. DeFries and S.O. Los

The results illustrate that misclassification errors are most meaningfully viewed in the context of the application of the land-cover information.  

1089 The Way Forward
John Estes, Alan Bel ward, Thomas Loveland, Joseph Scepan, Alan Strahler, John Townshend, and Chris Justice

Issues include database and data product development, classification legend definitions, processing and analysis techniques, and sampling strategies  

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1001 Grids & Datums — Moçambique
1006 Eulogy of William D. French

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