Multi-Source Remote Sensing for Spatiotemporal Monitoring of Soil Quality and Degradation
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 31 July 2026
Special Issue Editors
Interests: reflectance spectroscopy; hyperspectral remote sensing; soil property prediction time-series remote sensing
Special Issue Information
Dear Colleagues,
Soil plays an irreplaceable role in maintaining the stability and functionality of the ecosystem. It has the ability to sustain biological productivity, maintain environmental quality, and promote the health of animals and plants. Soil degradation has a variety of negative impacts on soil functions, including material cycling, biodiversity maintenance, soil and water conservation, environmental purification, and climate regulation. Conventionally, soil investigations are based on field sampling and subsequent chemical analyses in the laboratory. This conventional method is laborious, costly, and time-consuming. In addition, investigations based on discrete sampling lack detailed spatial information. Remote sensing has been recognized as an effective alternative for soil investigation. Remote sensing imagery has the potential to map soil properties and reveal spatial information over large scales. Time-series remote sensing images allow the possibility of spatiotemporally monitoring soil. Recently, a new generation of hyperspectral remote sensing satellites have been put into operation, further promoting the application of remote sensing in soil monitoring. Deep learning and artificial intelligence exhibit outstanding abilities in data mining and feature extraction.
This Special Issue aims to publish original research articles on recent advances, technologies, solutions, applications, and new challenges in the field of the spatiotemporal monitoring of soil quality and degradation using multi-source remote sensing.
Articles may address, but are not limited, to the following topics:
- Soil property prediction;
- The use of soil spectral libraries (SSLs);
- Soil property mapping;
- Hyperspectral data mining and feature extraction;
- Satellite remote sensing imagery classification;
- Soil quality and degradation monitoring;
- Spatiotemporal monitoring using time-series remote sensing imagery.
Dr. Weichao Sun
Prof. Dr. Kun Shang
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. 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
- soil properties
- soil quality
- soil degradation
- reflectance spectroscopy
- multi-source remote sensing
- time-series remote sensing
- prediction and mapping
- spatiotemporal monitoring
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