Mapping and Monitoring Soil Properties using Remote Sensing Techniques

Aim and Scope
This Special Issue will provide a dedicated forum for cutting-edge research that leverages remote sensing data—ranging from multispectral and hyperspectral imagery to LiDAR-, SAR-, and UAV-derived products—to map, monitor, and model key soil properties (e.g., soil organic carbon, moisture, bulk density, texture, nutrients). We seek contributions that push methodological frontiers, integrate process-based or machine learning frameworks, quantify uncertainty, and translate findings into actionable insights for land-management, agriculture, grassland conservation, and climate-change assessments. This scope aligns squarely with Remote Sensing’s emphasis on novel Earth-observation techniques and sensor applications, yet is focused enough to foster a coherent collection of at least ten high-quality papers that may later be published in book form.

Call for Participation

Dear Colleagues,

1. Introduction
   Healthy soils underpin food security, biodiversity, and global carbon cycling, yet their properties are notoriously variable in space and time. Traditional field surveys cannot deliver the resolution or temporal frequency needed to track changes across landscapes and decades. Recent advances in satellite constellations, UAV platforms, and data-fusion algorithms now allow us to observe soils directly or infer their properties via spectral, thermal, and microwave signatures—opening unprecedented opportunities to diagnose soil health, forecast carbon feedbacks, and guide sustainable ecosystem management.
2. Aim of the Special Issue
   This Special Issue aims to showcase state-of-the-art approaches to mapping and monitoring soil properties through remote sensing, firmly within the scope of Remote Sensing. We welcome studies that (i) develop or refine retrieval algorithms, (ii) integrate remote sensing products with process-based or machine learning models, (iii) validate soil predictions with field and long-term experimental data, or (iv) assess soil responses to climate variability, land-use change, and management interventions.
3. Suggested Themes and Article Types
   Original research articles, methodological notes, and comprehensive reviews are all encouraged. Topics of interest include, but are not limited to, the following:

• Remote sensing of soil organic carbon, nitrogen, and other nutrients;
• Soil-moisture retrieval and drought monitoring;
• Hyperspectral, LiDAR, SAR, multispectral, or UAV applications for soil studies;
• Data-fusion and machine learning frameworks for high-resolution soil mapping;
• Change-detection and time-series analyses of soil degradation or recovery;
• Uncertainty analysis and validation strategies for soil property products;
• Remote sensing of peatlands, permafrost, and other carbon-rich soils;
• Applications to sustainable agriculture, grassland management, and carbon accounting.

We look forward to receiving your contributions.

Dr. Daorui Han
Dr. Nicolas Baghdadi
Dr. Nathan Robinson
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.

• Soil organic carbon
• Remote sensing
• Machine learning
• Soil monitoring
• Climate change
• Peatlands
• Soil moisture
• Permafrost
• UAV and hyperspectral imaging
• Soil property mapping.