Production of global land cover data-GLCNMO
作者机构：Center for Environmental Remote Sensing(CEReS)Chiba UniversityChibaJapan College of Geographical ScienceInner Mongolia Normal UniversityHuhhotChina Geography DepartmentUniversity of JordanAmmanJordan National Authority for Remote Sensing and Space Sciences(NARSS)CairoEgypt School of Computer and Information TechnologyMongolian State University of EducationUlaanbaatarMongolia Institute of Geographical Science and TourismXinjiang Normal UniversityUrumqiChina Geographical Survey InstituteTsukubaJapan
出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)
年 卷 期：2011年第4卷第1期
页 面：22-49页
核心收录：
学科分类：0202[经济学-应用经济学] 02[经济学] 020205[经济学-产业经济学]
主 题：land cover remote sensing Digital Earth training data
摘 要：Global land cover is one of the fundamental contents of Digital *** Global Mapping project coordinated by the International Steering Committee for Global Mapping has produced a 1-km global land cover datasetGlobal Land Cover by National Mapping *** has 20 land cover classes defined using the Land Cover Classification *** them,14 classes were derived using supervised *** remaining six were classified independently:urban,tree open,mangrove,wetland,snow/ice,*** source data of this land cover mapping were eight periods of 16-day composite 7-band 1-km MODIS data of *** data for supervised classification were collected using Landsat images,MODIS NDVI seasonal change patterns,Google Earth,Virtual Earth,existing regional maps,and expert’s *** overall accuracy is 76.5%and the overall accuracy with the weight of the mapped area coverage is 81.2%.The data are available from the Global Mapping project website(http://***/).TheMODISdata used,land cover training data,and a list of existing regional maps are also available from the CEReS *** mapping attempt demonstrates that training/validation data accumulation from different mapping projects must be promoted to support future global land cover mapping.
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