Using Remote Sensing to Assess and Monitor Changes in Forest Ecosystems

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land – Observation and Monitoring".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 2083

Special Issue Editor


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Guest Editor
Department of Sustainable Agriculture, University of Patras, 30131 Agrinio, Greece
Interests: conservation ecology; biodiversity; biomonitoring; inventory and mapping of flora and habitat types/vegetation types; mapping and assessment of ecosystems and ecosystem services; GIS and remote sensing; environmental management; sustainable development; environmental policy
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Special Issue Information

Dear Colleagues,

The ongoing progress on remote sensing applications and earth observation science and products allow us to better capture nature characteristics, map and model all types of ecosystems and identify changes in spatial and temporal terms. Numerous satellite missions are already in action, while others are ready to be launched to monitor the earth’s surface and provide detailed information for different aspects of our planet, including emissions, land use change, climate data, spatial patterns and trends. Additionally, the use of UAVs and AI-driven software makes it possible to capture, map, model and interpret attributes in unprecedented detail. However, the potential of remote sensing and earth observation data to capture ecosystem attributes at the finest possible scale (yielding close-to-real-life results) is not yet met, thus limiting the capacity of decision and policy makers to the detail level available (local, regional, national or international scale), affecting conservation strategies and management. Woodland and forests are one of the most studied ecosystem types, in terms of extent, condition and changes, as well as in terms of biodiversity, productivity and climate change mitigation (e.g., carbon sequestration). However, some of their attributes (e.g., structural and functional) are still not well captured by remote sensing or earth observation applications.

With this Special Issue, we seek to provide a state-of-the-art collection of scientific articles (research articles and review papers) that document novel practices and advances in assessing and monitoring changes in forest ecosystems via remote sensing.

We welcome manuscripts on the following themes:

  1. Remote sensing and earth observation applications in mapping and monitoring changes in forest ecosystems at the regional and local scale.
  2. Remote sensing and earth observation applications combined with in situ, field survey data to map and assess ecosystem conditions (including structural, functional and landscape characteristics).
  3. Applications in identifying, assessing and mapping microhabitats and relevant indicators.
  4.  Natural capital accounting indicator development for woodland and forest ecosystems.
  5. Forest ecosystem service indicators, mapping and assessment (including change).
  6. Urban forest assessment and monitoring.
  7. Biodiversity assessment and monitoring in woodland and forest ecosystems.
  8. Integration of remote sensing applications for monitoring forest condition and change in policy and decision making (including climate and land-use change scenarios).
  9. Remote sensing and earth observation applications in digital platforms for decision making and protected area management.
  10. Use of remote sensing and citizen science to map and assess forest ecosystems.

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

Dr. Ioannis P. Kokkoris
Guest Editor

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Keywords

  • woodland and forest
  • ecosystem change and monitoring
  • earth observation
  • remote sensing
  • natural capital accounting
  • biodiversity

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Published Papers (2 papers)

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Research

20 pages, 2549 KB  
Article
National-Scale Economic Valuation of Forest Ecosystem Services in Pakistan Using Sentinel-2 Data
by Erika Filippelli, Anees Ahmad, Guglielmina Adele Diolaiuti and Antonella Senese
Land 2026, 15(2), 308; https://doi.org/10.3390/land15020308 - 12 Feb 2026
Cited by 1 | Viewed by 1051
Abstract
Pakistan’s forests cover only 4.2% of the national territory yet deliver critical ecosystem services that remain largely unaccounted for in policy and planning. This study provides the first harmonized, country-wide assessment of timber production and carbon sequestration services using Sentinel 2 imagery and [...] Read more.
Pakistan’s forests cover only 4.2% of the national territory yet deliver critical ecosystem services that remain largely unaccounted for in policy and planning. This study provides the first harmonized, country-wide assessment of timber production and carbon sequestration services using Sentinel 2 imagery and standardized valuation frameworks. A cloud-free Sentinel 2 composite for 2024 was processed at 20 m resolution to map forest cover, revealing an extent of 40,784 km2 concentrated below 2500 m a.s.l. Timber production was valued under two perspectives: forest-derived harvests (289,000 m3 yr−1; ~140 million USD yr−1) and total national supply (15 million m3 yr−1; ~7.3 billion USD yr−1), highlighting the marginal role of natural forests in Pakistan’s wood economy. Conversely, carbon sequestration emerges as a high magnitude regulating service: forests remove 2.53 million Mg CO2 yr−1, corresponding to 78 million USD yr−1 at a carbon price of 31 USD t−1 CO2. Sensitivity analysis across canopy thresholds (30%, 50%, 75%) confirms the robustness of this pattern. Despite their limited spatial footprint, Pakistan’s forests provide ecosystem services whose economic and ecological significance far exceeds their area. Findings underscore the need for integrated forest-landscape governance, improved monitoring systems, and inclusion of regulating services in national planning and carbon-finance mechanisms. Full article
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22 pages, 6011 KB  
Article
Remote Sensing for Vegetation Monitoring: Insights of a Cross-Platform Coherence Evaluation
by Eduardo R. Oliveira, Tiago van der Worp da Silva, Luísa M. Gomes Pereira, Nuno Vaz, Jan Jacob Keizer and Bruna R. F. Oliveira
Land 2026, 15(2), 306; https://doi.org/10.3390/land15020306 - 11 Feb 2026
Cited by 1 | Viewed by 529
Abstract
Remote sensing has revolutionized monitoring landscapes that are inaccessible or impractical to survey on the ground. Satellite platforms such as Sentinel-2 enable assessment of ecosystem changes over extensive areas with high temporal frequency, while Unmanned Aerial Systems (UAS) offer flexible, ultra-high-resolution observations ideal [...] Read more.
Remote sensing has revolutionized monitoring landscapes that are inaccessible or impractical to survey on the ground. Satellite platforms such as Sentinel-2 enable assessment of ecosystem changes over extensive areas with high temporal frequency, while Unmanned Aerial Systems (UAS) offer flexible, ultra-high-resolution observations ideal for site-specific analysis and sensitive environments. This study compares the performance of Sentinel-2 and Phantom 4 multispectral RTK data for monitoring vegetation dynamics in Mediterranean shrubland ecosystems, focusing on the Normalized Difference Vegetation Index (NDVI). Both platforms produced broadly consistent patterns in seasonal and interannual vegetation dynamics. However, UAS outperformed satellite data in capturing fine-scale heterogeneity, regeneration patches, and subtle disturbance responses, particularly in sparsely vegetated or heterogeneous terrain where satellite metrics may be insensitive. The comparison of NDVI across platforms accounted for standardized processing, harmonization, radiometric and atmospheric correction, and spatial resolution differences. Results show platform selection can be optimized according to monitoring objectives: satellite data are well suited for long-term monitoring of landscape-level vegetation dynamics, as both platforms capture consistent patterns when evaluated at comparable, spatially aggregated scales, while UAS data provide critical detail for localized management, early stress detection, and restoration prioritization by resolving fine-scale features. A combined approach enhances ecosystem disturbance assessments and resource management by binding the strengths of both wide-area coverage and precise spatial detail. Full article
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