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Land
Special Issues
Monitoring Forest Dynamics Using Remote Sensing and Spatial Data
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Monitoring Forest Dynamics Using Remote Sensing and Spatial Data

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Systems and Global Change".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1034

Special Issue Editors

Dr. Wonhee Cho

E-Mail Website
Guest Editor
Department of Forest Science, Kongju National University, Yesan 32439, Republic of Korea
Interests: ecological modeling; remote sensing; deep learning; AI; GIS; forest ecosystems; forest resources; landscape ecology; landscape modeling; land-use land-cover change
Dr. Min Kim

E-Mail Website
Guest Editor
Department of Landscape Archtecture, Kongju National University, Yesan 32439, Republic of Korea
Interests: system dynamics modeling; landscape planning; ecological restoration, socio-ecological resilience
Dr. Bora Lee

E-Mail Website
Guest Editor
Warm-Temperate and Subtropical Forest Research Center, National Institute of Forest Science, Jeju, Republic of Korea
Interests: forest carbon dynamic model; carbon storage and sequnstration; process-based modeling; vegetation phenology; mangrove forest; coastal forest ecosystems
Special Issues, Collections and Topics in MDPI journals
Dr. Nanghyun Cho

E-Mail Website
Guest Editor
National Forest Satellite Information & Technology Center, National Institute of Forest Science, Seoul 05203, Republic of Korea
Interests: remote sensing; forest indicies; artificial intelligence; forest ecosystem modeling; phenology; drought index

Special Issue Information

Dear Colleagues,

Forest monitoring refers to the systematic observation, measurement, and assessment of forest conditions and its functionality in various spatio-temporal scales using geospatial information. Remote sensing and geospatial datasets provide an unparalleled means to quantify forest dynamics by generating consistent, repeatable, and multi-resolution observations over the forest ecosystems. These data streams are crucial for assessing forest disturbance, degradation, recovery trajectories, and evaluating long-term forestland change under accelerating climatic and anthropogenic pressures. Advanced remote sensing and spatial analysis technologies, the artificial intelligence, have greatly enhanced the capability of interpreting complex datasets to observe forest ecosystems with high spatio-temporal resolution. Proliferation of AI-based models such as U-Net, CNNs, and transformer architectures enable highly accurate detection of critical events and its impact on forest ecosystems with applying integrated multisource environmental variables. The integration of advanced remote sensing and AI-based analytics improve the early detection of forest hazards allowing agencies to deploy prevention and mitigation strategies.

This Special Issue is to collect papers (original research articles and review papers) to give insights into understanding and responding about various forest dynamics through remote sensing and spatial analysis. We seek contributions that offer methodological innovations, demonstrate applied solutions to forest management challenges, and develop frameworks for adaptive governance that respond to dynamic forest conditions and emerging threats.

This Special Issue will welcome manuscripts that link the following themes:

  • Monitoring and analysis of forest dynamics with climatic and anthropogenic factors using advanced remote sensing and spatial analysis techniques.
  • The rapid assessment methodologies for remote sensing and spatial analysis in forest hazards and recovery trajectories.
  • The land governance and policy schemes in changing the forest ecosystem.
  • The methodologies to reclaim environmental policies and implications to respond to the future forest dynamics.
  • Landscape modeling for enhancing resilience and ecological infrastructure in urban, coastal, and rural environments.
  • Climate change impacts and vulnerability assessment in forest ecosystems.

We look forward to receiving your original research articles and reviews.

Dr. Wonhee Cho
Dr. Min Kim
Dr. Bora Lee
Dr. Nanghyun Cho
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 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. Land is an international peer-reviewed open access monthly 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 2600 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

  • land degradation trajectories
  • forest dynamics under climatic and anthropogenic pressure
  • forest evaluation by remote sensing and spatial data
  • land cover dynamics in forest landscape
  • forest functionality change
  • environmental policies and implications
  • ecological resilience in crisis
  • landscape modeling

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

42 pages, 5859 KB  
Article
Clustering Urban Tree Climate Responses: A Multi-Metric Ensemble SDM Approach Across SSP Scenarios
by Jeonghye Yun, Eunbin Gang and Gwon-Soo Bahn
Land 2026, 15(4), 616; https://doi.org/10.3390/land15040616 - 9 Apr 2026
Viewed by 119
Abstract
Urban trees deliver multiple ecosystem services. However, rapid climate change may alter species-specific growth suitability, necessitating climate-informed planting and management. We developed 1 km grid-based ensemble species distribution models (ensemble SDMS) for 18 tree species widely planted in South Korean cities and projected [...] Read more.
Urban trees deliver multiple ecosystem services. However, rapid climate change may alter species-specific growth suitability, necessitating climate-informed planting and management. We developed 1 km grid-based ensemble species distribution models (ensemble SDMS) for 18 tree species widely planted in South Korean cities and projected growth suitability under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 across four future periods (2021–2040, 2041–2060, 2061–2080, 2081–2100) relative to a historical baseline (2000–2019). We quantified multidimensional redistribution signals from SDM outputs, including binary suitable area changes, centroid displacement, latitudinal boundary shifts, and mean suitability changes, using multivariate climatic predictors and complementary environmental variables. These indicators were integrated to classify species responses into four management-relevant types: Stable, Northward Expansion, Poleward Shift, Range Contraction. Model performance was generally high (AUC = 0.74–0.97). Although the median change in suitable area remained near 0%, interspecific variability increased toward later periods and under stronger forcing, with the largest dispersion under SSP3-7.0 (2041–2060). Stable type was most frequent overall (36.8–63.2%), but Northward Expansion increased to 42.1% under late-century SSP3-7.0, and Range Contraction reached 36.8% under mid-century SSP3-7.0. This indicator-based typology provides a practical basis for decision-support tools to prioritize climate-adaptive urban tree selection, replacement, and monitoring. Full article
(This article belongs to the Special Issue Monitoring Forest Dynamics Using Remote Sensing and Spatial Data)
14 pages, 12188 KB  
Article
Time-Series Satellite-Based Monitoring of Land-Use Change and Forest Loss in Bhutan: Implications for Forest Carbon Measurement, Reporting, and Verification
by Mina Hong, Hangnan Yu, Yongho Song, Minkyung Song, Kyoungmin Kim and Woo-Kyun Lee
Land 2026, 15(3), 432; https://doi.org/10.3390/land15030432 - 7 Mar 2026
Viewed by 489
Abstract
Human-driven land-use change has significantly altered forest ecosystems and carbon dynamics in mountainous regions. This study aims to quantify land cover transitions and associated forest carbon stocks changes in Bhutan. It also seeks to support the development of a national measurement, reporting, and [...] Read more.
Human-driven land-use change has significantly altered forest ecosystems and carbon dynamics in mountainous regions. This study aims to quantify land cover transitions and associated forest carbon stocks changes in Bhutan. It also seeks to support the development of a national measurement, reporting, and verification system. Using Landsat-based satellite imagery and object-based image classification techniques, we assessed forest cover transitions, stand structure variations, and forest type changes across temporal intervals. The analysis revealed a consistent increase in agricultural and built-up areas. It also showed a concomitant decline in coniferous forest cover. In particular, agricultural land increased by approximately 0.77 million ha, while coniferous forest decreased by approximately 0.19 million ha over the study period. These changes were driven by both climatic shifts and socio-economic factors. Approximately 57% of Bhutan’s population depends on agriculture. Correspondingly, forest carbon stocks declined from approximately 570 million tC in 1995 to 405 million tC in 2017. This decline was largely attributed to coniferous forest loss and climate-induced mortality. Bhutan has made significant preparations for the implementation of the Warsaw REDD+ framework under the United Nations Framework Convention on Climate Change. These preparations include the establishment of a forest reference emission level for submission. However, challenges remain in detecting small-scale land use changes. Additional challenges include addressing spectral misclassification in mountainous regions. Our study provides a scientific baseline to support national forest monitoring and carbon accounting systems. It also offers policy-relevant insights for achieving Bhutan’s nationally determined contributions and enhancing its carbon sink potential. Full article
(This article belongs to the Special Issue Monitoring Forest Dynamics Using Remote Sensing and Spatial Data)
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