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Applications of Multi-Scale Remote Sensing and GIS Technology to Study Terrestrial Ecosystems (Second Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing for Geospatial Science".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1663

Special Issue Editors

Prof. Dr. Jiahua Zhang

E-Mail Website
Guest Editor
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (CAS), Beijing 100094, China
Interests: remote sensing of ecosystems; carbon and water cycle modelling; ecological investigation; land-use and -cover changes; vegetation dynamic; climate change and natural disasters
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Fengmei Yao

E-Mail Website
Guest Editor
University of Chinese Academy of Sciences (UCAS), Beijing 100094, China
Interests: impact of climate change on the ecosystem; ecological disaster monitoring based on remote sensing and GIS; ecological carbon and water cycle modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ecological environment is an important source of support for sustainable development and one of the leading global development drivers. Therefore, it is particularly critical to maintaining the global ecological balance. In recent years, the development of remote sensing and GIS technology has provided strong support for the study of ecological evolution and degradation, the long-term monitoring of its environmental effects, and the fine analysis of environmental change behavior.

We are pleased to publish the Special Issue on “Applications of Multi-Scale Remote Sensing and GIS Technology to Study Terrestrial Ecosystems (Second Edition)”. This Special Issue aims to integrate multi-scale remote sensing and GIS technologies to monitor the quality of the ecological environment at different spatial and temporal scales and further protect terrestrial ecology. Topics include, but are not limited to, terrestrial ecosystem services (carbon, water cycles, biochemical observations, climate change, drought, fire, heatwave, flooding, etc.) as well as spatial scales (environmental and ecological dynamics at different spatial scales) and time scales (ecological evolution from the paleoenvironment to the present).

Prof. Dr. Jiahua Zhang
Prof. Dr. Fengmei Yao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multi-scale remote sensing
  • GIS
  • terrestrial ecosystems
  • environmental dynamics
  • evolution and degradation
  • carbon
  • water cycles
  • climate change
  • natural disasters
  • land-use change

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Related Special Issue

Published Papers (2 papers)

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Research

22 pages, 8022 KB  
Article
Spatiotemporal Analysis of Vegetation Fires and Carbon Monoxide Pollution in Indonesia
by Griffin McAvoy and Krishna Vadrevu
Remote Sens. 2025, 17(19), 3275; https://doi.org/10.3390/rs17193275 - 24 Sep 2025
Viewed by 156
Abstract
Vegetation fires in Indonesia, particularly in forests and peatlands, are major drivers of air pollution, with impacts on public health, biodiversity, and climate. Using satellite-derived data from 2012 to 2024, we identified an average of 21,271 fires annually, with peak activity during the [...] Read more.
Vegetation fires in Indonesia, particularly in forests and peatlands, are major drivers of air pollution, with impacts on public health, biodiversity, and climate. Using satellite-derived data from 2012 to 2024, we identified an average of 21,271 fires annually, with peak activity during the dry season (August–October). 32.0% of total fires occurred in forests; and 21.9% in peatlands. While a seasonal Mann–Kendall trend analysis revealed a statistically significant decline in fire activity over this period (approximately 502 fewer fires per month), seasonal peaks remain persistent during the late and post-monsoon periods. Notably, fire activity increased by more than 400% during El Niño years (2015–2016, 2018–2019, 2023–2024) compared to non-El Niño years. Through geographically weighted regression (GWR), we found that fire activity is closely correlated to carbon monoxide (CO) pollution. The relationship was strongest in the forested regions of central Kalimantan, western Sulawesi, and southern Java. Our findings highlight the amplifying effects of El Niño events on fire dynamics and air quality and the urgent need for targeted, climate-responsive fire management strategies. Strengthening mitigation and adaptation efforts in tropical forests and peatlands will be critical for protecting human health and reducing emissions in the region. Full article
(This article belongs to the Special Issue Applications of Multi-Scale Remote Sensing and GIS Technology to Study Terrestrial Ecosystems (Second Edition))
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34 pages, 18194 KB  
Article
Coupling Coordination Spatial Pattern of Habitat Quality and Human Disturbance and Its Driving Factors in Southeast China
by Xiaojun Wang, Hong Jia, Shumei Xiao and Guangxu Liu
Remote Sens. 2025, 17(17), 2956; https://doi.org/10.3390/rs17172956 - 26 Aug 2025
Cited by 1 | Viewed by 685
Abstract
Assessing habitat quality and quantifying human disturbance are fundamental prerequisites for ecological conservation. However, existing studies predominantly focus on single dimensions. There is an urgent need to integrate habitat quality and human disturbance, and quantify their spatially coupled coordination relationships to address the [...] Read more.
Assessing habitat quality and quantifying human disturbance are fundamental prerequisites for ecological conservation. However, existing studies predominantly focus on single dimensions. There is an urgent need to integrate habitat quality and human disturbance, and quantify their spatially coupled coordination relationships to address the disconnect between them in current research. As a critical ecological reserve in southeastern China, Fujian Province faces threats of ecological degradation. This study employed the InVEST model to evaluate habitat quality in Fujian from 1980 to 2020, utilized a human disturbance index to quantify spatiotemporal patterns of anthropogenic activities, analyzed their changes using landscape indices, and applied coupling coordination analysis to examine their interrelationships. Machine learning and geographically weighted regression were further integrated to identify driving factors of coupling coordination patterns. The results showed that: (1) Habitat quality remained relatively high while human disturbance levels stayed low throughout 1980–2020, though both showed gradual deterioration over time, particularly during 2010–2020, with riverine and coastal eastern regions exhibiting the lowest habitat quality and highest disturbance levels. (2) Coupling coordination relationships predominantly exhibited synergy, with moderate imbalance zones concentrated in the eastern coastal areas. Temporally, regions with lower imbalance expanded significantly during 2010–2020. (3) Landscape metric analysis revealed declining dominance of high-quality habitat/low-disturbance/synergistic zones, contrasted by increased fragmentation of low-quality habitat/high-disturbance/imbalanced zones. (4) Socioeconomic factors exerted stronger influence on coupling coordination patterns than natural environmental variables, proximity to urban areas, road density, and nighttime light indices. Each driver displayed spatially variable positive/negative effects. The results enhance our understanding of human–nature sustainable development dynamics, urban expansion–ecological conservation trade-offs, and provide methodological insights for regional ecological management and achieving sustainable development goals. Full article
(This article belongs to the Special Issue Applications of Multi-Scale Remote Sensing and GIS Technology to Study Terrestrial Ecosystems (Second Edition))
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