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Fused Active and Passive UAV and Miniaturised Remote Sensing Capabilities and Applications in Wetlands and Drylands

This special issue belongs to the section “Biogeosciences Remote Sensing“.

Special Issue Information

Dear Colleagues,

Wetlands and drylands, though occurring in spatially-distinct regions that may not always overlap, provide critical ecosystem services across a range of environmental gradients and are at heightened risk of degradation from anthropogenic pressures, continued development, and global environmental changes. There is a growing need for high-resolution (spatially and temporally) habitat identification and precise delineation of wetlands as well as drylands changes (such as woody encroachment) across a variety of stakeholder groups and programs, at scales ranging from globally to regionally and locally. Traditional wetland and dryland surveying and sampling approaches are costly, time-intensive, and can physically degrade the systems that are being surveyed, while aerial surveys are relatively fast and unobtrusive. This Special Issue will be a collection of papers that demonstrate integrate integration of active (focusing on LiDAR) and passive remote sensing data collected from UAV and miniature remote sensing platforms to assess the efficacy and feasibility of using such collection methods for mapping and modeling change in wetland or dryland systems worldwide. The Special Issue will include a variety of systems such as high-resolution topography in complex forested wetlands, vegetation structure based on fused spectral (multispectral and/or hyperspectral) and LiDAR and three-dimensional data with relevance for mapping subtle changes and conversions in these previously difficult to measure ecosystems. Especially for wetland and dryland conversions from grassy to more woody-dominated habitat types, the ability to fuse active and passive remote sensing data derived from UAV platforms that can carry multiple sensors simultaneously can provide opportunities to move the science forward in ways previously impossible. Additionally, papers that discuss the fusion of UAV-collected LiDAR and spectral datasets with satellite imagery are also invited as these methods are of vital importance in the extension of local to regional scales and these resulting datasets are inter-related both spatially and temporally.

Dr. Narcisa G. Pricope
Dr. Joanne N. Halls
Dr. Devon O. Eulie
Dr. Justin T. Ridge
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

  • Active and passive UAS
  • Miniaturized remote sensing
  • Wetlands modeling
  • Drylands modeling
  • Vertical vegetation metrics
  • Active-passive remote sensing fusion

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Remote Sens. - ISSN 2072-4292