Many water bodies play a crucial role as receiver of several urban basins within the water system of a city, these urban basins often face challenges of pollution and reduction in water flow, such as, the case of the Juan Angola channel in the city of Cartagena, Colombia. Current remote sensing strategies using Landsat and Sentinel-2 satellite imagery, lack the necessary spatial resolution to adequately study such as water bodies. In contrast, higher spatial resolution data, such as the PlanetScope one, allows for better spatial and temporal details. Nevertheless, PlanetScope does not count with the same spectral resolution as Landsat and Sentinel-2, requiring of further processings to extract relevant information. In this paper, we used PlanetScope satellite images, processed through computer vision techniques, to analyze the evolution of the Juan Angola channel, Laguna del Cabrero and Chambac´u over time. Our approach involved extracting water areas from PlanetScope images and comparing these over different periods. Preliminary findings revealed noticeable variations in the area of the channel due to factors such as rainfall and possible illegal human invasion, as well as, the increment in level of contamination observed by means of the Normalized Difference Turbidity Index (NDTI). The images used from PlanetScope offered a more detailed time-series analysis of different hydrographic areas, which is particularly pertinent in the Juan Angola channel.
Calibrating large-range vision systems like UAV cameras is a complex task that often involves costly setups and the potential for errors due to inaccuracies in target fabrication. Traditional UAV surveying software typically estimates camera parameters alongside ground control points, but this method may lack optimal accuracy. Our study explores an alternative: using out-of-focus camera calibration to improve the reliability and accuracy of drone cameras for surveying. In our approach, the UAV camera is positioned several meters away from a low-cost target to ensure focus. We then calibrate the intrinsic camera parameters using an out-of-focus small calibration target, fixing these parameters before flight. For evaluation, we compare this method against the standard approach of estimating UAV camera parameters with survey imagery. Preliminary results suggest that this out-of-focus method offers a reliable and accurate solution for UAV surveying applications.
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