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Remote Sensing for Vegetation Dynamic Monitoring, Carbon and Ecological Assessment

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 1286

Special Issue Editors


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Guest Editor
College of Soil and Water Conservation, Nanjing Forestry University, Nanjing 210037, China
Interests: ecological monitoring and assessment; revegetation and carbon sink; urban and mine ecology

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Guest Editor
College of Forestry, Nanjing Forestry University, Nanjing 210037, China
Interests: vegetation change detection; forest disturbance; forest carbon accounting; evaluation of climate effects; ecological remote sensing
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Guest Editor
Department of Energy and Process Engineering, Norwegian University of Science and Technology, 7034 Trondheim, Norway
Interests: ecosystems and ecoservices; biodiversity and bioresources; climate change mitigation strategies

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Guest Editor Assistant
Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
Interests: revegetation monitoring and effectiveness assessment; carbon exchange between terrestrial ecosystem and the atmosphere
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Earth's terrestrial vegetation is a dynamic and critical component of the global biosphere, serving as the foundation for ecosystem services, biodiversity, and the planet's carbon cycle. In an era of unprecedented environmental change—driven by climate fluctuations, land-use transformations, and anthropogenic pressures—the precise monitoring of vegetation dynamics and the robust assessment of carbon stocks and ecosystem functions have become paramount for scientific understanding, policy formulation, and sustainable management. Recent advances in remote sensing technologies, computational methodologies, and interdisciplinary ecological modelling have fundamentally transformed our capacity to observe, analyze, and predict these complex processes across spatial and temporal scales.

This Special Issue is dedicated to showcasing cutting-edge research and innovative applications at the forefront of this rapidly evolving field. We seek to compile a comprehensive collection of contributions that leverage multi-source Earth observation data—from high-resolution satellite imagery and LiDAR to UAV-based sensors and hyperspectral platforms—to address pressing challenges and unlock new insights. The scope encompasses the development of novel algorithms for tracking vegetation phenology, structure, composition, and physiological status; the quantification of above- and below-ground carbon stocks and fluxes; and the integrated evaluation of ecosystem integrity, resilience, and service provision.

Key thematic areas of interest include, but are not limited to, the following:

  • vegetation detection;
  • afforestation and ecological functions;
  • revegetation and carbon sinks;
  • carbon cycle evaluation;
  • vegetation physiological processes inversion;
  • vegetation and environment interaction;
  • ecological restoration assessment;
  • multimodal data processing and fusion;
  • biodiversity and bioresources;
  • climate adaptation.

By bringing together diverse perspectives from remote sensing, ecology, geography, climatology, and data science, this Special Issue aims to foster interdisciplinary dialogue, highlight methodological breakthroughs, and chart future research directions. The collective knowledge presented here will be instrumental in enhancing our predictive understanding of vegetation responses to global change and in providing the evidence base necessary for effective stewardship of our planet's vital ecosystems.

Prof. Dr. Haidong Li
Dr. Wenjuan Shen
Dr. Xiangping Hu
Guest Editors

Dr. Yamei Shao
Guest Editor Assistant

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 250 words) can be sent to the Editorial Office for assessment.

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

  • vegetation dynamics
  • revegetation effectiveness
  • ecological restoration
  • carbon sinks
  • ecological monitoring
  • environmental interaction
  • biodiversity monitoring and evaluation
  • climate adaptation
  • multimodal remote sensing

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Published Papers (3 papers)

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Research

19 pages, 7082 KB  
Article
Remote Sensing Study of the Impact of Revegetation on Lake Shrinkage in a Semi-Arid Inland Lake Basin, Inner Mongolia
by Yamei Shao, Nan Wang, Lijun Zhao, Guohui Yao, Yicong Chen, Weilun Li, Hao Wang and Haidong Li
Remote Sens. 2026, 18(11), 1833; https://doi.org/10.3390/rs18111833 - 3 Jun 2026
Abstract
Revegetation serves as a critical ecological safeguard, while these interventions have added complexity to the evapotranspiration processes and water balance. Dalinor Lake basin (DLB), located in the southeast of Inner Mongolia Plateau, serves as a vital habitat for migratory birds and plays an [...] Read more.
Revegetation serves as a critical ecological safeguard, while these interventions have added complexity to the evapotranspiration processes and water balance. Dalinor Lake basin (DLB), located in the southeast of Inner Mongolia Plateau, serves as a vital habitat for migratory birds and plays an important role in the ecological security of northern China. To enhance biodiversity, numerous ecological restoration projects have been carried out in this area in recent years. Dalinor Lake, a large inland lake within the basin, has experienced persistent shrinkage. Although existing studies have explored its driving factors, the potential influence of revegetation activities on lake shrinkage remains unclear. In this study, we used remote sensing imagery, combined with supervised classification and visual interpretation methods, to extract changes in the surface areas of lakes within the DLB (i.e., Dalinor Lake and Ganggeng Lake), and analyzed the effects of total terrestrial evapotranspiration (ETt), precipitation (PPT), runoff, soil moisture content, and the vapor pressure deficit on these changes. Results showed that the Dalinor Lake’s area decreased by 18.68% from 2000 to 2020, and was mainly influenced by ETt, with the Normalized Difference Vegetation Index (NDVI) contributing the most to ETt (54.02%). In contrast, Ganggeng Lake expanded by 5.68% and was strongly driven by PPT. Compared with Ganggeng Lake, there have been more revegetation activities around Dalinor Lake, resulting in significant increases in NDVI and ETt, together with widespread declines in soil moisture in its surrounding areas, suggesting that revegetation exerted non-negligible water pressure on Dalinor Lake. These findings can provide valuable information for policymakers to balance large-scale ecological restoration with sustainable water management in semi-arid regions. Full article
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34 pages, 6624 KB  
Article
Spatiotemporal Vegetation Dynamics and Quantity-Structure Relationships on a Tropical Island: A Case Study of Hainan, China
by Xin Guo, Shengpei Dai, Hongxia Luo, Wujun Lv, Shanshan Jiang, Yuhao Yang and Yi Yang
Remote Sens. 2026, 18(10), 1615; https://doi.org/10.3390/rs18101615 - 17 May 2026
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Abstract
Vegetation serves as a critical ecological barrier on tropical islands, but conventional assessments often emphasize greening magnitude while overlooking persistence, structural quality, and scale-dependent attribution. In this study, we reconstructed a high-precision fractional vegetation cover (FVC) dataset for Hainan Island, China, covering the [...] Read more.
Vegetation serves as a critical ecological barrier on tropical islands, but conventional assessments often emphasize greening magnitude while overlooking persistence, structural quality, and scale-dependent attribution. In this study, we reconstructed a high-precision fractional vegetation cover (FVC) dataset for Hainan Island, China, covering the period from 2000 to 2024 using Google Earth Engine (GEE). We then combined trend analysis, emerging hot spot analysis (EHSA), the coupling coordination degree model (CCDM), RESTREND, and Geodetector to examine vegetation change from complementary perspectives. The results show that FVC increased overall and gradually shifted toward a more stable state over time. EHSA further revealed a distinct core-periphery pattern, with persistent hot spots concentrated in the central mountainous region, persistent cold spots distributed along the coastal urban belt, and oscillating hot spots occurring within agricultural transition zones. Regarding quantity-structure coupling, FVC and the aggregation index (AI) generally improved together across the island; however, some agricultural ecotones exhibited weaker structural improvement despite increasing vegetation cover, suggesting potential risks of homogenization and structural simplification. In the broad attribution analysis, vegetation recovery was primarily associated with the combined influence of climatic and human-related improvement. In the factor-specific analysis, land cover and slope showed the strongest explanatory power, and their interactions with other variables further enhanced spatial differentiation. These results demonstrate that greening magnitude alone is insufficient for evaluating vegetation change on tropical islands. Structural coordination and scale-dependent attribution should also be considered when interpreting ecological improvement and related management implications. Full article
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26 pages, 28964 KB  
Article
Simulating Net Ecosystem Exchange of China’s Three Staple Food Crops and Their Responses to Heatwaves
by Yanzi Sun, Shuyu Zhao, Jiayao Yu, Mengkun Zhu, Weiwei Liu, Lihua Wang, Gang Yang and Tian Feng
Remote Sens. 2026, 18(9), 1399; https://doi.org/10.3390/rs18091399 - 1 May 2026
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Abstract
Agricultural carbon sequestration is increasingly threatened by heatwaves, yet accurately simulating crop-explicit net ecosystem exchange (NEE) under heat stress remains challenging. In this study, we used a WRF–VPRM–CROP model to simulate the spatiotemporal dynamics of NEE for rice, wheat, and maize in China, [...] Read more.
Agricultural carbon sequestration is increasingly threatened by heatwaves, yet accurately simulating crop-explicit net ecosystem exchange (NEE) under heat stress remains challenging. In this study, we used a WRF–VPRM–CROP model to simulate the spatiotemporal dynamics of NEE for rice, wheat, and maize in China, quantifying the impacts of the record-breaking 2022 heatwave. Model validation against multi-source observations confirmed its reliability, with correlation coefficients (r) reaching 0.49–0.85 (p < 0.001). Results show that the cumulative summer NEE of the study region reaches 620.32 Tg C, with contributions of 274.94 Tg C from rice and 345.09 Tg C from maize, while wheat contributes 157.83 Tg C during spring. The 2022 heatwave led to substantial reductions in crop NEE, with decreases of 79.70 Tg C for rice, 33.13 Tg C for wheat, and 100.74 Tg C for maize. Total summer NEE decreased by 171.46 Tg C, with an annual reduction of 213.57 Tg C. Spatially, the most pronounced declines in NEE are concentrated in East China and North China, whereas slight increases are observed in western Heilongjiang (maize-growing areas) and parts of eastern coastal wheat-growing regions. At the provincial scale, the most severe yield losses occur in Henan (29.65 Mt) and Shandong (14.50 Mt). This study quantifies the impacts of extreme heatwaves on carbon exchange in China’s major staple crop systems, providing a scientific basis for regional agricultural climate adaptation and disaster risk mitigation. Full article
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