NDLI: Editorial for the Special Issue “Ecosystem Services with Remote Sensing”

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Editorial for the Special Issue “Ecosystem Services with Remote Sensing”

Content Provider	MDPI
Author	Gao, Jiangbo
Copyright Year	2020
Description	Ecosystem services refer to the environmental conditions and utilities provided and maintained by ecosystems, which are the basis for the survival and development of human society. The studies on ecosystem services in quantitative assessments, driving mechanisms, and correlation with human well-being, based on remote sensing, have increased in recent years. Various applications of remote sensing in ecosystem services are reported in six papers published in this Special Issue. The major research topics covered by this Special Issue include the multi-method analysis (e.g., linear regression, geographical detector, and geographically weighted regression methodology) of the normalized difference vegetation index (NDVI) to reflect ecosystem structure, the dynamic changing process of ecosystem services, and the determinants, which include a new image-analysis method based on a time series of a biophysical variable and the application of fractional vegetation cover (FVC) to analyze the spatiotemporal relationship between ecosystem structure and function and the comprehensive study on ecosystem function and service based on multi-source remote sensing data. The application of remote sensing data to ecosystem services research has the advantage of monitoring ecological structure and functions at multi-scales. Furthermore, the quantitative calculation of ecosystem services, based on remote sensing, can provide a scientific basis for enhancing land use optimization and sustainable development.
Starting Page	2191
e-ISSN	20724292
DOI	10.3390/rs12142191
Journal	Remote Sensing
Issue Number	14
Volume Number	12
Language	English
Publisher	MDPI
Publisher Date	2020-07-09
Access Restriction	Open
Subject Keyword	Remote Sensing Ecosystem Services Driving Factors and Mechanism Service Provision and Demand Land Use Optimization
Content Type	Text

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