Coordinating methodologies for scaling landcover classifications from site-specific to global: Steps toward validating global map products

The MODIS sensor to be launched on tho EOS-AM platform will be the most imp ortant sensor for global vegetation mapping. Among the programmatic goals f or the MODIS sensor are to assess and track changes in land use/landcover, leaf area index (LAI), and net primary productivity (NPP). For these produc ts to be used in global models, they must be rigorously validated with site -specific data products. This article presents a review of some of the prob lems facing a regional- to global-scale validation effort and presents stra tegies for coordinating the land-cover classification process across multip le sites. We suggest the Enhanced Thematic Mapper (ETM+) as the source of r emotely sensed data for validation, and that the IGBP 17-class land-cover c lassification system be used to provide a link between more complex site-sp ecific systems and global-scale data products.. We further recommend that t he best site-specific land-cover classifications be obtained using whatever ancillary data are found to be useful as a basis for validation. In additi on, we propose ways in which ambiguities in translation of classes, from sp ecific to general systems may be identified. Finally, we stress that even t hough standardization of methodology among sites may not be appropriate to the goal of obtaining the best possible land-cover prodnets, there should b e standardization of error analysis and metadata reporting. (C) Elsevier Sc ience Inc., 1999.