Remote Sensing of Soil Erosion in Forest Area
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Forest Remote Sensing".
Deadline for manuscript submissions: 15 June 2024 | Viewed by 9101
Special Issue Editors
Interests: satellite soil moisture retrieval; hydrological modeling; satellite vegetation parameter retrieval
Interests: Soil erosion; Land use and land cover; Wetland remote sensing
Interests: soil erosion; machine learning; geotechnical engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Soil erosion is currently one of the most important environmental problems worldwide. Specifically, with the aggravation of global climate change and human activities, forest has been suffering an increasing risk of soil erosion. As a consequence, many forestry ecosystem functions such as carbon exchange and water/soil conservation would be seriously affected.
In recent decades, the development of quantitative remote sensing allows for the generation of many key land surface/atmospheric parameters (such as soil moisture, precipitation, forest canopy cover, leaf area index, etc.) and associated remote-sensing-based soil erosion models and has provided an unprecedented opportunity to monitor soil erosion over forest areas. It is the right time to summary the achievements and to further guide the future research directions in this field and especially to promote new methods in the monitoring of forest soil erosion, since many new technologies (such as LIDAR and P-band radar) have been introduced to detect land surface parameters in forest areas.
In the context of “Remote Sensing of Soil Erosion in Forest Area”, this Special Issue seeks contributions reflecting the present innovative research progress in this field. The topics can range from the satellite retrieval methods for key factors of soil erosion, the remote-sensing-based soil erosion models, the effects of climate change and human activities on soil erosion, as well as the system development for soil erosion assessment. Specifically, research articles and review papers are warmly welcomed in this Special Issue.
Dr. Pei Leng
Dr. Hong-Yuan Huo
Dr. Walter Chen
Dr. Min-Cheng Tu
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 erosion model
- satellite soil moisture and vegetation cover
- forest degradation monitoring
- soil erosion modeling using InSAR
- IoT-based soil erosion monitoring
- soil erosion susceptibility with machine learning
- soil erosion sensitivity mapping
- soil erodibility and risk factors
- USLE/RUSLE
- USPED
- WaTEM/SEDEM
- WEPP/GeoWEPP