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Remote Sensing Application in Ecological Restoration Monitoring: A Systematic Review

Authors :
Ruozeng Wang
Yonghua Sun
Jinkun Zong
Yihan Wang
Xuyue Cao
Yanzhao Wang
Xinglu Cheng
Wangkuan Zhang
Source :
Remote Sensing, Vol 16, Iss 12, p 2204 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

In the context of the continuous degradation of the global environment, ecological restoration has become a primary task in global environmental governance. In this process, remote sensing technology, as an advanced monitoring and analysis tool, plays a key role in monitoring ecological restoration. This article reviews the application of remote sensing technology in ecological restoration monitoring. Based on a comprehensive analysis of the literature in the field of ecological remote sensing, it systematically summarizes the major in-orbit spaceborne and airborne sensors and their related products. This article further proposes a series of evaluation indicators for ecological restoration from four aspects: forests, soil, water, and the atmosphere, and elaborates on the calculation methods for these indicators. In addition, this paper also summarizes the methods for evaluating the effectiveness of ecological restoration, including subjective evaluation, objective evaluation, and comprehensive evaluation methods. Finally, we analyze the challenges faced by remote sensing technology in evaluating ecological restoration effectiveness, such as issues with the precision of indicators extraction, the limitations of spatial resolution, and the diversity of evaluation methods. This review also looks forward to future ecological restoration technologies, such as the potential applications of integrated aerospace and terrestrial remote sensing, multi-data fusion, and machine learning technologies. This study reveals the effectiveness of remote sensing technology in ecological restoration monitoring, aiming to provide efficient tools and innovative strategies for future remote sensing monitoring and assessment of ecological restoration.

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.567704a76fd41308c878d53cdc9cff0
Document Type :
article
Full Text :
https://doi.org/10.3390/rs16122204