Dataset of the mountain green cover index(SDG15.4.2)over the economic corridors of the Belt and Road Initiative for 2010-2019
作者机构：Research Center for Digital Mountain and Remote Sensing ApplicationInstitute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengduChina
出 版 物：《Big Earth Data》 (地球大数据（英文）)
年 卷 期：2022年第6卷第1期
页 面：77-89页
核心收录：
学科分类：02[经济学] 0202[经济学-应用经济学] 0201[经济学-理论经济学] 0709[理学-地质学] 0708[理学-地球物理学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant number XDA19030303) the National Key Research and Development Program of China(No.2020YFA0608700) the Youth Innovation Promotion Association of CAS(Grant 2019365).
主 题：Sustainable development goals(SDGs) mountain green cover index(MGCI) dataset Belt and Road Landsat
摘 要：Mountains are undergoing widespread changes caused by human activities and climate change.Given the importance of mountains,the protection and sustainable development of mountain ecosys-tems have been listed as the goals of the United Nations 2030 Sustainable Development Agenda.As one of the indicators,the Mountain Green Cover Index(MGCI)datasets can provide consis-tent and comparable status of green vegetation in mountainous areas,which can support the mapping of heterogeneous mountain ecosystem health and monitoring changes over time.The produc-tion of explicitly high-spatial-resolution MGCI datasets is therefore urgently needed to support the protection measures at subnational and multitemporal scales.In this paper,the MGCI datasets with 500-meter spatial resolutions,covering the economic corridors of the Belt and Road Initiative(BRI),were developed for 2010 to 2019 based on all available Landsat-8 data and the Google Earth Engine cloud computing platform.The validation of green vegeta-tion cover with the ground-truth samples indicated that the data-sets can achieve an overall accuracy of 94.06%,with well-detailed spatial and temporal variations.The archived datasets include the MGCI of each BRI economic corridor,matched to a geospatial layer denoting the economic corridor boundaries.The essential informa-tion of the datasets and their limitations,along with the production flow,were described in this paper.
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