Dataset of ecosystem services in Beijing and its surrounding areas

Tianqian Chen; Zhe Feng; Huafu Zhao; Kening Wu

Data in Brief (Apr 2020)

Dataset of ecosystem services in Beijing and its surrounding areas

Tianqian Chen,
Zhe Feng,
Huafu Zhao,
Kening Wu

Affiliations

Tianqian Chen: School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
Zhe Feng: School of Land Science and Technology, China University of Geosciences, Beijing 100083, China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100035, China; Corresponding author. School of Land Science and Technology, China University of Geosciences, Beijing 100083, China.
Huafu Zhao: School of Land Science and Technology, China University of Geosciences, Beijing 100083, China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100035, China
Kening Wu: School of Land Science and Technology, China University of Geosciences, Beijing 100083, China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100035, China

Journal volume & issue: Vol. 29

Abstract

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This data article describes the multiple ecosystem services in Beijing and surrounding areas, including grain providing, water yield, carbon sequestration, soil retention, purified water service, cultural services, and habitat quality. These data are mainly from public data sets such as the Harmonized World Soil Database. These data can be used to improve the optimization of human well-being in the social-ecological system and further achieve regional sustainable development. Keywords: Ecosystem service, NDVI, InVEST model, RUSLE, Daily carrying capacity, Beijing and its surrounding areas

Published in Data in Brief

ISSN: 2352-3409 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Science: Science (General)
Website: http://www.journals.elsevier.com/data-in-brief/

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