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DEM modeling using RGB-based vegetation indices from UAV images
Author(s): K. Themistocleous
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Paper Abstract

Traditional NDVI techniques require NIR images from multispectral cameras in order to identify vegetation. Research indicates that RGB images from UAV platforms can provide a cost-efficient and near-real time survey with high temporal and spatial resolution. In this study, only RGB images taken with a 20MP camera mounted on a UAV glider were used to conduct a ground survey and generate a Digital Elevation Model (DEM). Over 7,000 UAV images with less than 5cm ground resolution were used in order to survey a 5km2 in the Alassa region in Cyprus in order to produce a DEM. The area was geo-referenced using ground control points. Due to extensive vegetation coverage, a RGB-based vegetation indice was used to mask the vegetation and produce a DEM using interpolation techniques. This study highlights a cost-effective technique to survey and model large areas with vegetation coverage.

Paper Details

Date Published: 27 June 2019
PDF: 8 pages
Proc. SPIE 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 111741J (27 June 2019); doi: 10.1117/12.2532748
Show Author Affiliations
K. Themistocleous, Cyprus Univ. of Technology (Cyprus)


Published in SPIE Proceedings Vol. 11174:
Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019)
Kyriacos Themistocleous; Giorgos Papadavid; Silas Michaelides; Vincent Ambrosia; Diofantos G. Hadjimitsis, Editor(s)

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