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Special Issue "Remote Sensing of Dryland Environment"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: 31 January 2020.
Dr. Olena Dubovyk Website E-Mail
Centre for Remote Sensing of Land Surfaces (ZFL), Geography Institute, University of Bonn, Genscherallee 3, D-53113 Bonn, Germany
Interests: Remote sensing of land surface dynamics; Remote sensing for land degradation and drought monitoring & assessment; Remote Sensing for agricultural applications; Earth observation and Geo-information for policy support and international cooperation support (SDGs, Sendai indicators etc)
Dr. Tobias Landmann Website E-Mail
Remote Sensing Solutions GmbH, Dingolfinger Str. 9, 81673 Munich, Germany
Interests: Understanding socio-ecological systems in Africa and Asia; Developing of geo-spatial solutions for environmental health monitoring (degradation and deforestation); Cropland and rangeland productivity mapping; Spatial epidemiology in Africa; Ecosystems services analysis and reporting
A large portion of the human population lives in dryland areas, and these biomes also offer a variety of ecosystem services to the local people. In spite of their importance, systematically mapping and characterizing them has been somewhat neglected by the remote sensing community. This is in part due to their bio-complexity and the diffuse scattering of satellite signals in open and sparsely-vegetated areas. Moreover, drylands exhibit large temporal dynamics because of their dependence on rainfall and are, thus, very sensitive to climate variability and human-driven land degradation. Capturing these intricate spatial and temporal land change processes requires multi-source and multi-scale data sets and fusion algorithms that intelligently integrate in situ data, remote sensing observations and modelling results. To reflect their intra-annual and inter-annual variations, the use of well-processed time series data is imperative. Specifically, monitoring dryland phenology from space plays an important role in assessing the anthropogenic pressures and drivers in drylands. Further combining remote sensing with process-based models offer the opportunity to unravel land change effects and consequences in drylands.
This Special Issue, therefore, calls for manuscripts that deal with assessing environmental issues in drylands using multi-scale and multi-source data in an integrated way. Specifically, manuscripts are encouraged that illustrate the possibilities of how multi-source data sets in terms of better dealing with land degradation in drylands, invasive species encroachment and land management issues and policy and decision support.
Dr. Olena Dubovyk
Assoc. Prof. Zhiwei Xu
Dr. Tobias Landmann
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 1800 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.
- Time series analysis and land surface phenology
- Dryland characterization and modelling
- Land use and land cover dynamics and rangeland integrity
- Deep learning, machine learning and artificial intelligence
- Data fusion (multi-source satellite data, in situ data, crowd sourcing , mobile sensors, or other ground sensors)
- Monitoring and assessment of land degradation and restoration in drylands
- Unmanned aerial system (UAS)-based applications