Irrigation networks are important in distributing water resources to areas where rainfall is not enough to sustain agriculture. They are also crucial when it comes to being able to redirect vast amounts of water to decrease the risks of flooding in flat areas, especially near sources of water. With the lack of studies about irrigation feature extraction, which range from wide canals to small ditches, this study aims to present a method of extracting these features from LiDAR-derived digital terrain models (DTMs) using Geographic Information Systems (GIS) tools such as ArcGIS and Whitebox Geospatial Analysis Tools (Whitebox GAT). High-resolution LiDAR DTMs with 1-meter horizontal and 0.25-meter vertical accuracies were processed to generate the gully depth map. This map was then reclassified, converted to vector, and filtered according to segment length, and sinuosity to be able to isolate these irrigation features. Initial results in the test area show that the extraction completeness is greater than 80% when compared with data obtained from the National Irrigation Administration (NIA).
M. A. P. Mahor, R. M. De La Cruz, N. T. Olfindo, and A. M. C. Perez, "Irrigation network extraction methodology from LiDAR DTM using Whitebox and ArcGIS," Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980X (Presented at SPIE Remote Sensing: September 28, 2016; Published: 25 October 2016); https://doi.org/10.1117/12.2241969.
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