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Remote Sensing of Ecosystem Structure and Function Dynamics Due to Climate Change and Human Activities (2nd Edition)

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

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1360

Special Issue Editors

Dr. Jun Zhai

E-Mail Website
Guest Editor
Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment of the People's Republic of China, Beijing 100094, China
Interests: ecosystem assessment and management; land use and cover change; geographic information system; satellite image analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Wei Cao

E-Mail Website
Guest Editor
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: ecosystem services; geographic information system; ecosystem monitoring
Special Issues, Collections and Topics in MDPI journals
Dr. Yuanwei Qin

grade E-Mail Website
Guest Editor
Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, USA
Interests: forest resources and ecosystem; forest carbon; agriculture; environmental remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The natural environment is being shaped and transformed by climate change and human activities, causing consequential alterations in ecosystem structure and function. These changes exhibit significant temporal and spatial variations in terms of their processes, rates, and extents. It is imperative to establish quantitative assessment indicators and technical methodologies to accurately characterize and comprehend the patterns and dynamics of ecological changes. This scientific foundation serves as a guide for making informed decisions concerning ecological protection, restoration, and management. The present era witnesses the emergence of multi-platform remote sensing technology, encompassing active and passive sensors integrated into satellites, unmanned aerial vehicles (UAVs), observation towers, and ground-based mobile devices. This technology has attained the capability to rapidly and accurately acquire key parameters pertaining to ecosystem structure and processes across continuous spatiotemporal scales. Consequently, it offers abundant data sources and diverse technical approaches for monitoring and assessing ecological status changes at various scales.

The previous volume of Ecosystem Structure and Function Dynamics Due to Climate Change and Human Activities was a great success. This new Special Issue is also intended to provide a platform for academic exchange regarding progress in assessing ecosystem structure and function changes due to climate change and human activities, utilizing remote sensing technology. Specifically, studies including, but not limited to, the following topics are welcome:

  • Ecological remote sensing assessment models and methods;
  • The inversion of key parameters of multi-scale ecosystem structure and processes through remote sensing;
  • The application of remote sensing technology in comprehensive assessment of ecosystem patterns, quality, and functions;
  • Ecological space remote sensing monitoring and assessment;
  • Ecological protection, restoration, and management;
  • The impacts of climate change on ecosystems.

Dr. Jun Zhai
Dr. Wei Cao
Dr. Yuanwei Qin
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

  • ecosystem structure
  • ecosystem function
  • ecological protection
  • biodiversity
  • nature reserves
  • carbon sequestration
  • climate change

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Related Special Issue

Published Papers (3 papers)

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Research

27 pages, 3973 KiB  
Article
Modeling the Distribution and Richness of Mammalian Species in the Nyerere National Park, Tanzania
by Goodluck Massawe, Enrique Casas, Wilfred Marealle, Richard Lyamuya, Tiwonge I. Mzumara, Willard Mbewe and Manuel Arbelo
Remote Sens. 2025, 17(14), 2504; https://doi.org/10.3390/rs17142504 - 18 Jul 2025
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Abstract
Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large [...] Read more.
Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas. Full article
(This article belongs to the Special Issue Remote Sensing of Ecosystem Structure and Function Dynamics Due to Climate Change and Human Activities (2nd Edition))
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25 pages, 7522 KiB  
Article
Quantitative Estimation of Vegetation Carbon Source/Sink and Its Response to Climate Variability and Anthropogenic Activities in Dongting Lake Wetland, China
by Mengshen Guo, Nianqing Zhou, Yi Cai, Xihua Wang, Xun Zhang, Shuaishuai Lu, Kehao Liu and Wengang Zhao
Remote Sens. 2025, 17(14), 2475; https://doi.org/10.3390/rs17142475 - 16 Jul 2025
Viewed by 223
Abstract
Wetlands are critical components of the global carbon cycle, yet their carbon sink dynamics under hydrological fluctuations remain insufficiently understood. This study employed the Carnegie-Ames-Stanford Approach (CASA) model to estimate the net ecosystem productivity (NEP) of the Dongting Lake wetland and explored the [...] Read more.
Wetlands are critical components of the global carbon cycle, yet their carbon sink dynamics under hydrological fluctuations remain insufficiently understood. This study employed the Carnegie-Ames-Stanford Approach (CASA) model to estimate the net ecosystem productivity (NEP) of the Dongting Lake wetland and explored the spatiotemporal dynamics and driving mechanisms of carbon sinks from 2000 to 2022, utilizing the Theil-Sen median trend, Mann-Kendall test, and attribution based on the differentiating equation (ADE). Results showed that (1) the annual mean spatial NEP was 50.24 g C/m2/a, which first increased and then decreased, with an overall trend of −1.5 g C/m2/a. The carbon sink was strongest in spring, declined in summer, and shifted to a carbon source in autumn and winter. (2) Climate variability and human activities contributed +2.17 and −3.73 g C/m2/a to NEP, respectively. Human activities were the primary driver of carbon sink degradation (74.30%), whereas climate change mainly promoted carbon sequestration (25.70%). However, from 2000–2011 to 2011–2022, climate change shifted from enhancing to limiting carbon sequestration, mainly due to the transition from water storage and lake reclamation to ecological restoration policies and intensified climate anomalies. (3) NEP was negatively correlated with precipitation and water level. Land use adjustments, such as forest expansion and conversion of cropland and reed to sedge, alongside maintaining growing season water levels between 24.06~26.44 m, are recommended to sustain and enhance wetland carbon sinks. Despite inherent uncertainties in model parameterization and the lack of sufficient in situ flux validation, these findings could provide valuable scientific insights for wetland carbon management and policy-making. Full article
(This article belongs to the Special Issue Remote Sensing of Ecosystem Structure and Function Dynamics Due to Climate Change and Human Activities (2nd Edition))
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24 pages, 6023 KiB  
Article
Unveiling Drivers and Projecting Future Risks of Desertification Vulnerability in the Mongolian Plateau
by Maolin Li, Buyanbaatar Avirmed, Ganbold Bayanmunkh, Yilin Liu, Yu Wang, Xinyu Yang, Yu Zhang and Qiang Yu
Remote Sens. 2025, 17(14), 2389; https://doi.org/10.3390/rs17142389 - 11 Jul 2025
Viewed by 281
Abstract
Desertification presents a significant ecological challenge in arid and semi-arid regions, posing a severe threat to regional ecological security and sustainable development. This study introduces an integrated framework for desertification vulnerability assessment, combining the MEDALUS model with the XGBoost algorithm, to evaluate desertification [...] Read more.
Desertification presents a significant ecological challenge in arid and semi-arid regions, posing a severe threat to regional ecological security and sustainable development. This study introduces an integrated framework for desertification vulnerability assessment, combining the MEDALUS model with the XGBoost algorithm, to evaluate desertification dynamics across the Mongolian Plateau from 2000 to 2020 and project future trends under four Shared Socioeconomic Pathways (SSPs) for 2030. The findings are as follows: (1) Between 2000 and 2020, desertification vulnerability was most pronounced in the southern and western regions of the plateau, with lower vulnerability observed in the northern and eastern areas. High-vulnerability zones expanded over time, highlighting the need for targeted and prioritized management efforts. (2) Climate factors—particularly temperature, wind speed, and precipitation—emerged as the dominant drivers of desertification, followed by soil characteristics and vegetation (NDVI). The influence of human activities on desertification became increasingly significant, stressing the need for improved land management and sustainable practices. (3) Future risks show that desertification vulnerability in the Mongolian Plateau will intensify under high-emission scenarios (SSP3-7.0, SSP5-8.5), with significant expansion of high vulnerability areas. Lower-emission scenarios (SSP1-2.6, SSP2-4.5) may reduce some impacts, but high vulnerability will persist, highlighting the need for urgent climate mitigation and adaptation efforts. Full article
(This article belongs to the Special Issue Remote Sensing of Ecosystem Structure and Function Dynamics Due to Climate Change and Human Activities (2nd Edition))
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