Remote Sensing Technologies for Soil Health Monitoring

A special issue of Environments (ISSN 2076-3298).

Deadline for manuscript submissions: 15 December 2025 | Viewed by 1134

Special Issue Editors


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Guest Editor
Eratosthenes Centre of Excellence, 3012 Limassol, Cyprus
Interests: soil health; living labs; hydrogeology; remote sensing

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Guest Editor
World Agroforestry Centre (ICRAF), Nairobi, Kenya
Interests: soil physics; soil spectroscopy; machine learning; remote sesnsing

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Guest Editor
Laboratory of Geophysics—Satellite Remote Sensing & Archaeoenvironment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas, 74131 Rethymno, Greece
Interests: geoinformatics; remote sensing; GIS; soil spatial analysis
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Guest Editor
Laboratory of Remote Sensing, Spectroscopy, and Geographical Information Systems, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, 54636 Thessaloniki, Greece
Interests: soil science; infrared spectroscopy; big data; remote sensing; artificial intelligence
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Guest Editor
Department of Rural and Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: soil and water resource management; precision irrigation
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Guest Editor
Department of Agricultural Sciences, Biotechnology and Food Science, Cyprus University of Technology, Limassol 3036, Cyprus
Interests: soil-borne pests and diseases; nematology; agroecology; carbon farming practices; UAVs

Special Issue Information

Dear Colleagues,

Maintaining and restoring soil health has become an urgent global priority in the face of climate change, land degradation, and growing food security concerns. Though valuable, traditional soil health assessment methods are often labor-intensive and spatially limited. In contrast, integrating remote sensing (RS) technologies—enhanced by artificial intelligence (AI)—transforms soil health monitoring into a dynamic, scalable, and data-driven process.

This Special Issue invites contributions that explore innovative applications of RS for assessing soil health descriptors, supporting monitoring, reporting, and verification (MRV) frameworks and enabling precision land and soil management. We welcome studies utilizing the full spectrum of RS platforms—including spaceborne and airborne systems (e.g., UAVs and aerial campaigns)—and diverse sensor types (e.g., optical, radar, and thermal), along with synergistic approaches that integrate multiple data sources to enhance soil monitoring accuracy. In addition, we encourage research that addresses challenges in RS adoption, including accessibility and resolution limitations. Of particular interest are studies that demonstrate how earth observation data can support climate action through greenhouse gas monitoring, informed land-use planning and management aimed at a climate-neutral land-use sector, and the advancement of soil regeneration strategies.

Emphasis will be placed on works that combine AI-driven analysis, predictive modeling, and decision-support systems to build robust and coherent soil monitoring frameworks across local, regional, and global scales. Furthermore, we encourage contributions demonstrating how living labs and other multi-actor environments can facilitate the co-creation, testing, and validation of RS tools in real-world settings, ensuring that technological advances are locally relevant and contribute to climate-resilient and sustainable practices.

This Special Issue welcomes both original research and review papers. Ultimately, this Special Issue aims to showcase how RS technologies can empower stakeholders—from farmers to policymakers—with insights to regenerate degraded soils and support the transition toward sustainable and resilient land systems.

Dr. Ioannis Varvaris
Dr. Zampela Pittaki
Dr. Athanasios V. Argyriou
Dr. Nikolaos L. Tsakiridis
Dr. Nikiforos Samarinas
Dr. Michalakis Christoforou
Guest Editors

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Keywords

  • soil health
  • remote sensing
  • artificial intelligence (AI)
  • living labs
  • monitoring, reporting, and verification (MRV)
  • earth observation
  • sustainable land management
  • climate resilience
  • soil regeneration
  • data-driven decision making

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Published Papers (1 paper)

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Research

22 pages, 4715 KB  
Article
Remote Sensing-Based Mapping of Soil Health Descriptors Across Cyprus
by Ioannis Varvaris, Zampela Pittaki, George Themistokleous, Dimitrios Koumoulidis, Dhouha Ouerfelli, Marinos Eliades, Kyriacos Themistocleous and Diofantos Hadjimitsis
Environments 2025, 12(8), 283; https://doi.org/10.3390/environments12080283 - 17 Aug 2025
Viewed by 822
Abstract
Accurate and spatially detailed soil information is essential for supporting sustainable land use planning, particularly in data-scarce regions such as Cyprus, where soil degradation risks are intensified by land fragmentation, water scarcity, and climate change pressure. This study aimed to generate national-scale predictive [...] Read more.
Accurate and spatially detailed soil information is essential for supporting sustainable land use planning, particularly in data-scarce regions such as Cyprus, where soil degradation risks are intensified by land fragmentation, water scarcity, and climate change pressure. This study aimed to generate national-scale predictive maps of key soil health descriptors by integrating satellite-based indicators with a recently released geo-referenced soil dataset. A machine learning model was applied to estimate a suite of soil properties, including organic carbon, pH, texture fractions, macronutrients, and electrical conductivity. The resulting maps reflect spatial patterns consistent with previous studies focused on Cyprus and provide high resolution insights into degradation processes, such as organic carbon loss, and salinization risk. These outputs provide added value for identifying priority zones for soil conservation and evidence-based land management planning. While predictive uncertainty is greater in areas lacking ground reference data, particularly in the northeastern part of the island, the modeling framework demonstrates strong potential for a national-scale soil health assessment. The outcomes are directly relevant to ongoing soil policy developments, including the forthcoming Soil Monitoring Law, and provide spatial prediction models and indicator maps that support the assessment and mitigation of soil degradation. Full article
(This article belongs to the Special Issue Remote Sensing Technologies for Soil Health Monitoring)
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