Remote Sensing in Soil Organic Carbon Dynamics
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".
Deadline for manuscript submissions: 29 August 2025 | Viewed by 78
Special Issue Editors
Interests: digital soil mapping; deep learning model; analysis of time series characteristics
Interests: soil; organic matter; remote sensing; regression modeling; multivariate statistics
Interests: crop mapping; soil mapping; Google Earth Engine; remote sensing; agriculture
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Soil organic carbon (SOC) is among the largest active carbon pools in terrestrial ecosystems, with its dynamics directly influencing soil fertility, crop productivity, carbon cycling, and global climate change. Advances in remote sensing technology offer a novel approach to addressing this issue: multispectral, hyperspectral, thermal infrared, and radar data, acquired from satellite, airborne, or proximal remote sensing platforms, are integrated with surface parameter prediction models and machine learning algorithms to enable large-scale, high-frequency monitoring of SOC dynamics. Recently, integrating multi-source remote sensing data with GIS has further enhanced the accuracy of SOC spatiotemporal predictions. Additionally, process-based ecosystem models and remote sensing data assimilation techniques provide quantitative tools for assessing the long-term impacts of climate change and human activities on SOC content.
This Special Issue highlights innovations in remote sensing technology and methodology, interdisciplinary applications, and responses to global environmental challenges. The scope of this Special Issue includes developing novel methods for predicting SOC dynamics from multi-source remote sensing data, interdisciplinary research integrating remote sensing with soil science, ecology, climate science, and agricultural management, as well as SOC dynamics monitoring, which is directly linked to global challenges such as climate change mitigation (carbon sink assessment), land degradation management (SDG-15), and food security (SDG-2). Therefore, this Special Issue aligns closely with the journal in three key dimensions: technology, interdisciplinarity, and applied value.
Themes:
- High-accuracy dynamic monitoring of SOC content with multi-source remote sensing data;
- Extracting features from multi-source remote sensing data to enable SOC content prediction with deep learning models;
- Integrating remote sensing technology with ecosystem models for dynamic SOC content monitoring;
- Advanced sensors and data fusion techniques for SOC content prediction;
- Investigating the drivers of SOC spatiotemporal dynamics, including land management, climate change, and other influencing factors;
- Accurate validation of SOC spatiotemporal dynamics.
Article types:
In particular, we welcome submissions of original research articles, reviews, and case studies focusing on the remote sensing of SOC spatiotemporal dynamics.
Dr. Xiangtian Meng
Dr. Huanjun Liu
Dr. Chong Luo
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.
Keywords
- soil organic carbon
- remote sensing
- multi-source data
- spatiotemporal dynamics
- deep learning model
- driver analysis
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