Abstract
Global land cover products have been created for global environmental studies by several institutions and organizations. The Global Mapping Project coordinated by the International Steering Committee for Global Mapping (ISCGM) has been periodically producing global land cover datasets asone of the eight basic global datasets. It has produced a new fifteen-second (approximately 500 m resolution at the equator) global land cover dataset – GLCNMO2013 (or GLCNMO version 3). This paper describes the method of producing GLCNMO2013. GLCNMO2013 has 20 land cover classes, and they were mapped by improved methods from GLCNMO version 2. In GLCNMO2013, five classes,which are urban, mangrove, wetland, snow/ice, and waterwere independently classified. The remaining 15 classes were divided into 4 groups and mapped individually by supervised classification. 2006 polygons of training data collected for GLCNMO2008 were used for supervised classification. In addition, about 3000 polygons of new training data were collected globally using Google Earth, MODIS Normalized Difference Vegetation Index (NDVI) seasonal change patterns, existing regional land cover maps, and existing four global land cover products. The primary data of this product were Moderate Resolution Imaging Spectroradiometer (MODIS) data of 2013. GLCNMO2013 was validated at 1006 sampled points. The overall accuracy of GLCNMO2013 was 74.8%, and the overall accuracy for eight aggregated classes was 90.2%. The accuracy of the GLCNMO2013 was not improved compared with the GLCNMO2008 at heterogeneous land covers. It is necessary to prepare the training data for mosaic classes and heterogeneous land covers for improving the accuracy.
Highlights
Several attempts to map global land cover have been made to date
This paper describes the method we produced a new global land cover dataset, GLCNMO2013 under the “Global Mapping” project
The main parts for mapping GLCNMO2013 are to: (1) improve the mapping method used in GLCNMO2008; (2) add ne w training data to those collected for the GLCNMO2008 using Google Earth, Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) seasonal change patterns, and existing regional land cover maps; and (3) modify the map based on the reports from the 19 countries participating in the Global Mapping project (Appendix A)
Summary
Several attempts to map global land cover have been made to date. Global land cover datasets is used for environmental studies. The GlobCover 2009 V2.3 global land cover map, the newest version of GlobCover, was derived from the Medium Resolution Imaging Spectrometer Instrument (MERIS) Fine Resolution (FR) surface reflectance mosaics for the year 2009 (Arino et al, 2008). The main parts for mapping GLCNMO2013 are to: (1) improve the mapping method used in GLCNMO2008; (2) add ne w training data to those collected for the GLCNMO2008 (or GLCNMO version 2) using Google Earth, MODIS Normalized Difference Vegetation Index (NDVI) seasonal change patterns, and existing regional land cover maps; and (3) modify the map based on the reports from the 19 countries participating in the Global Mapping project (Appendix A)
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