Unmanned Aerial Vehicle Derived DEM Using in Accurate Geometric Analysis for Water Harvesting in Small-Scale Depressions

Abstract

Due to significant progress in remote sensing over the past few decades, topographic data is now widely available on a global scale. Recent advancements in unmanned aerial vehicle technology have made it possible to get high resolution topographic images on a scale of less than a meter. Making it perfect for small sites survey. Conducted an assessment of the unmanned aerial vehicle ability to estimate various geometric elements by generating a digital elevation model and subsequently analyzing the depression geometrically. The study area in focus was in AL-Sherqat, which consists of a small valley. Upon analysis of the generated digital elevation model, we were able to determine the valley's maximum capacity volume to be 18365.91 m3 at a water level of 186.8 m above sea level. The analysis also yielded other important elements, such as positive volume, negative and positive surface areas, negative and positive planar areas, residual capacity, average depression depth, and average island thickness. The interrelationships among these geometric elements were plotted for further analysis. Based on the results, we conclude that the unmanned aerial vehicle structure from the motion (SFM) algorithm and the produced digital elevation model are suitable for surveying small topographic depressions. This technique could prove valuable for water harvesting purposes.