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

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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 4996

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Special Issue Editors

Dr. Jun Zhai

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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
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Dr. Wei Cao

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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
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Dr. Yuanwei Qin

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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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Remote Sensing of Ecosystem Structure and Function Dynamics Due to Climate Change and Human Activities in Remote Sensing (8 articles)

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Research

23 pages, 9602 KB

Open AccessArticle

Evolution and Attribution Analysis of the Relationship Among Soil Erosion Negative Service, Carbon Sequestration, and Water Yield in the Yellow River Basin After the Grain for Green Program

by Menghao Yang, Ming Wang, Lianhai Cao, Haipeng Zhang, Huhu Niu and Jun Liu

Remote Sens. 2025, 17(17), 3028; https://doi.org/10.3390/rs17173028 - 1 Sep 2025

Viewed by 861

Abstract

Understanding the tradeoff and synergy among ecosystem services (ESs) and their influencing factors is a prerequisite for simultaneously managing multiple ESs and holds significant importance for achieving harmonious regional development between humans and nature. Existing research predominantly focuses on the overall characteristics of tradeoff and synergy, while studies on spatially differentiated tradeoff and synergy characteristics remain limited. In addition, their driving mechanisms are not yet fully understood, especially in large-scale river basins. This study, taking the Yellow River Basin (YRB) from 2000 to 2023 as the study area, employed multi-source data and multiple models to quantify three ESs, including soil erosion negative service (indirectly reflecting the soil conservation service function), carbon sequestration, and water yield. Combining Pearson correlation analysis, a geographically weighted regression model, and optimal parameter geographical detection, we identified the spatiotemporal interaction relationships and their dominant drivers. The results indicated that soil erosion negative services decreased by 24.89%, while carbon sequestration and water yield increased by 53.30% and 38.47%, respectively. The most significant improvements in the three ESs were observed in the midstream of the YRB. Spatially, soil erosion negative service decreased from west to east. Carbon sequestration exhibited a spatial pattern of higher values in the south and east and lower values in the north and west. Water yield decreased from south to north. Tradeoff relationships existed between soil erosion negative service and carbon sequestration and between soil erosion negative service and water yield. A synergistic relationship existed between carbon sequestration and water yield. Over time, the proportion of areas showing synergy among these three ESs decreased. However, synergistic areas remained more common than tradeoff areas. This was especially evident in the relationship between carbon sequestration and water yield, where synergy consistently accounted for over 78% of the YRB. Rainfall, soil properties, and fractional vegetation cover were identified as important drivers of the tradeoff/synergy between soil erosion negative service and carbon sequestration. Rainfall, temperature, fractional vegetation cover, and elevation were significant drivers of the interactions between carbon sequestration and water yield. Population density, fractional vegetation cover, GDP density, and rainfall were the main influencing factors for the tradeoff/synergy between soil erosion negative service and water yield. Our general methodology and results provide valuable decision-making references for policymakers, highlighting the necessity of considering the spatiotemporal heterogeneity in ESs tradeoff characteristics and their underlying driving factors. 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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23 pages, 13218 KB

Open AccessArticle

Driving Analyses of the Effects of Climate Change and Human Activity on the Ecological Environmental Quality of the North China Plain

by Zefeng Wei, Shuting Wang, Yunlan Guan, Yuecan Hu, Siyao Wang and Li Shen

Remote Sens. 2025, 17(16), 2839; https://doi.org/10.3390/rs17162839 - 15 Aug 2025

Viewed by 512

Abstract

Understanding the dynamic changes in the quality of the ecological environment and its potential driving forces is essential for protecting regional ecosystems and promoting sustainable development. In this study, we developed an improved remote sensing ecological index (IRSEI) by integrating the kernel normalized difference vegetation index (kNDVI) with an abundance index (AI) and conducted a comprehensive analysis of the spatiotemporal evolution of the quality of the ecological environment in the North China Plain (NCP) from 2000 to 2020. A multistep driving analysis framework was established to identify key climatic factors via the XGBoost algorithm and to quantify the effects of climate change and human activities through partial correlation analysis and a multiple regression residual model. The results indicate the following: (1) From 2000 to 2020, the ecological quality of the NCP significantly improved, with the average IRSEI increasing from 0.41 to 0.45. The proportion of areas with “good” or “excellent” ecological quality increased, revealing a south–north gradient, with higher values in the southern part and lower values in the northern part of the NCP. (2) Among the key climatic variables, surface temperature was significantly negatively correlated with the IRSEI, whereas atmospheric pressure and evapotranspiration were significantly positively correlated. (3) Approximately 51.97% of the ecological quality changes were jointly driven by climate change and human activities, with the contribution of human activities (28.80%) exceeding that of climate change (19.23%). These findings provide a scientific basis for understanding the driving mechanisms behind ecological environment changes and support ecological restoration and coordinated human–environment development in the context of climate change. 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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27 pages, 3973 KB

Open AccessArticle

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

Viewed by 1959

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 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 KB

Open AccessArticle

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 521

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 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 KB

Open AccessArticle

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 637

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 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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