Comparison of UAV-LIDAR and Aerial Photogrammetry in Rural Areas with High Vegetation
Journal: International Journal of Scientific Engineering and Science (Vol.8, No. 5)Publication Date: 2024-05-15
Authors : Arli Llabani; Freskida Abazaj;
Page : 46-51
Keywords : ;
Abstract
This study presents a comparative analysis of UAV-based Light Detection and Ranging (LiDAR) and aerial photogrammetry for mapping and surveying in rural areas. Both technologies have revolutionized geospatial data acquisition, offering unique advantages and facing specific challenges. UAV-LiDAR uses laser pulses to create high-resolution three-dimensional models, excelling in areas with dense vegetation and complex terrain by providing precise elevation data and the ability to penetrate canopy cover. Aerial photogrammetry, on the other hand, employs high-resolution images to generate 3D models through photogrammetric techniques, performing well in open fields and less vegetated areas due to its high-resolution orthomosaics and cost-effectiveness. Field studies conducted in various rural settings— agricultural lands, forests, and mixed-use landscapes—served as the basis for comparison, focusing on metrics such as data accuracy, point density, processing time, and cost. UAV-LiDAR demonstrated superior performance in densely vegetated and topographically complex areas, whereas aerial photogrammetry was more efficient and economical in open and semi-open landscapes. The study also explores the potential of integrating both technologies to leverage their strengths, enhancing overall data quality and providing comprehensive geospatial insights. The findings offer practical guidelines for selecting the appropriate technology based on specific project requirements, highlighting UAV-LiDAR's suitability for detailed topographic surveys and vegetation analysis, and aerial photogrammetry's advantages for broader area coverage and budget-sensitive projects. This comparison underscores the transformative impact of UAV technologies in rural mapping and supports informed decision-making in environmental monitoring, agriculture, and infrastructure development
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Last modified: 2024-07-08 19:09:24