Special Issue "UAV Applications in Forestry"
Deadline for manuscript submissions: closed (15 March 2019) | Viewed by 57180
Unmanned aerial vehicle (UAV) applications are rapidly expanding and revolutionizing remote sensing for natural sciences. UAV platforms provide a unique opportunity for acquiring low-cost imagery at fine spatial and temporal resolutions from local to regional scales. Recent advances in UAV sensors include LiDAR and hyperspectral sensors, although multispectral and thermal sensors have been commonly used on UAV platforms. UAV-based visible (RGB) and near-infrared (NIR) images are also used to generate three-dimensional models of topography and vegetation using structure from motion (SfM). Taken together, the UAV sensors, associated images, and derived products can now provide critical datasets for forest monitoring, impact assessment, change detection, and management protocols. This special issue examines UAV-based multispectral, hyperspectral, and three-dimensional images in forestry applications. In particular, this Special Issue focuses on quantitative assessment of errors and accuracies of UAV image-derived forest metrics and variables at the scale of forest stands as well as individual trees. Research papers that focus on both forest metrics and methodological development are welcome. This Special Issue includes the following potential topics, but is not limited to them:
- Accuracies and errors in UAV image-derived forest stand metrics (forest yield, biomass, tree density, stand age, etc)
- Accuracies and errors associated with UAV image-derived individual tree metrics (tree height, canopy dimension, volume, biomass, etc)
- Detection capabilities of UAV multispectral data (individual species classification and characterization)
- Detection capabilities of UAV LiDAR data (individual tree detection, tree- and stand-level estimates of biomass, growth, and changes)
- Detection capabilities of UAV-derived SfM data (individual tree- and stand-level metrics)
Dr. Temuulen Sankey
Manuscript Submission Information
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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 2500 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.
- Forest structure
- Tree species classification
- Forest cover change
- UAV lidar
- UAV multispectral data
- Data fusion