Special Issue "High Spectral Resolution Remote Sensing of Soil Organic Carbon Dynamics"
Deadline for manuscript submissions: 31 October 2020.
Interests: soil properties; physical geography; remote sensing
Interests: soil erosion and biogeochemical cycling; soil spectroscopy; monitoring and mapping soil dynamics using UAVs
Interests: visNIR–SWIR–LWIR spectroscopy; digital soil mapping; hyperspectral remote sensing; soil erosion and degradation; satellite imaging spectrometers
Special Issues and Collections in MDPI journals
Soil organic carbon (SOC) in croplands is responsive to changes in management and/or land use. Over the last decades, a substantial inter- and intrafield variability has developed, impacting food security and with the potential for negative CO2 emissions. Visible and near-infrared (visNIR) spectroscopy is a high-throughput tool necessary for processing the large number of samples required to investigate the patterns in SOC and its dynamics. Pilot studies have demonstrated the potential of remote sensing using different platforms—from UAVs to satellites—for mapping SOC in the topsoil of exposed croplands. The development of miniature sensors on UAVs, as well as the high-resolution multispectral and hyperspectral sensors on board of satellites, is in full progress.
The prediction of soil properties, such as SOC, is not straightforward due to the variable spectral response of organic matter, resulting in a lack of clear and narrow spectral features. This Special Issue calls for efficient methods improving the quantification of SOC based on visNIR spectroscopy data, including the calibration of spectral models acquired from the laboratory to remote sensing platforms using spectral libraries, development of adequate databases, development of algorithms enhancing the detection of exposed cropland soils, techniques for increasing the spatial coverage of SOC maps by, e.g., mosaicking images acquired at different periods, and the demonstration of spaceborne applications from current or future sensors. Contributions on digital soil mapping—that allow topsoil SOC concentrations to be converted to changes in SOC stocks, from a field to regional scale—will be appreciated.
Prof. Dr. Bas van Wesemael
Dr. Florian Wilken
Dr. Sabine Chabrillat
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 papers will be 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 2200 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.
- Hyperspectral remote sensing
- Sentinel 2
- UAV borne sensors
- SOC stocks
- Algorithms for detecting exposed cropland soils
- Spectral libraries
- Digital soil mapping
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
"An operational protocol for soil organic carbon mapping in croplands using LUCAS topsoil database and Sentinel-2 data."
Castaldi Fabio, Chabrillat Sabine, Don Axel, van Wesemael Bas.