http://www.globallandcover.com/ 为推动利用地理信息监测全球地表变化,应对全球挑战,促进可持续发展,自然资源部在多年努力和技术创新基础上,组织制作了2020版30米全球地表覆盖数据。2020年9月15日,在联合国成立75周年之际,自然资源部向社会发布2020版30米全球地表覆盖数据,自然资源部陆昊部长向联合国副秘书长刘振民代...
REDLANDS, Calif.-Esri, the global leader in location intelligence, today announced it is releasing for the first time ever a new high-resolution, 2020 global land cover map as part of the company'sLiving Atlas. The map was built using European Space Agency (ESA) Sentinel-2 satellite imagery...
官网:http://www.globallandcover.com/ 是一个提供全球地表覆盖数据的官方网站, 它由中国机构维护并运营, 专注于发布和分发名为GlobeLand30的高分辨率全球土地利用/覆盖数据集。这个数据集是通过遥感技术和地理信息系统(GIS)进行处理和分析得到的, 旨在支持环境监测、气候变化研究、生态系统评估、城市化进程监测以及其...
Global general Land Use and Land Cover (LUC) datasets map all land uses and covers across the globe, without focusing on any specific use or cover. This chapter only reviews those datasets available for one single date, which have not been updated over time. Seven different datasets are descr...
Over past decades, a lot of global land-cover products have been released, however, these is still lack of a global land-cover map with fine classification system and spatial resolution simultaneously. In this study, a novel global 30-m land-cover classification with a fine classification system...
Liu, H.et al. Production of global daily seamless data cubes and quantification of global land cover change from 1985 to 2020 - iMap World 1.0.Remote Sens. Environ.258, 112364 (2021). ArticleADSGoogle Scholar Abadi, M.et al. TensorFlow: A system for large-scale machine learning.OSDI(2016...
The Global Land Cover Facility (GLCF) global forest-cover and -change dataset is a multi-temporal depiction of long-term (multi-decadal), global forest dynamics at high (30-m) resolution. Based on per-pixel estimates of percentage tree cover and their associated uncertainty, the dataset current...
The world’s mega trends of land-use and landscape development are discussed, which are urbanization and land-use intensification, particularly considering their negative consequences for the ecological as well as the socio-economic environment. Trade-of
Land cover change rates derived from higher-resolution remote sensing datasets such as Hansen GFC66, ESA CCI67and MODIS68are on average about the same order of magnitude (1.1 times) as for HILDA + . In particular, the HILDA + annual change rate is on average 1.3 times greater tha...
When comparing GISA 2.0 with other global ISA datasets (Table 4), it is found that GISA 2.0 have an omission error of 6.88% in 2015, which is lower than GLC_FCS2015 (Global Land Cover Fine Classification System) (Zhang et al., 2020) and FROM_GLC2015 (Finer Resolution Observation and ...