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Proceedings Paper

Automation of lidar-based hydrologic feature extraction workflows using GIS
Author(s): Noel Jerome B. Borlongan; Roel M. de la Cruz; Nestor T. Olfindo Jr.; Anjillyn Mae C. Perez
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Paper Abstract

With the advent of LiDAR technology, higher resolution datasets become available for use in different remote sensing and GIS applications. One significant application of LiDAR datasets in the Philippines is in resource features extraction. Feature extraction using LiDAR datasets require complex and repetitive workflows which can take a lot of time for researchers through manual execution and supervision. The Development of the Philippine Hydrologic Dataset for Watersheds from LiDAR Surveys (PHD), a project under the Nationwide Detailed Resources Assessment Using LiDAR (Phil-LiDAR 2) program, created a set of scripts, the PHD Toolkit, to automate its processes and workflows necessary for hydrologic features extraction specifically Streams and Drainages, Irrigation Network, and Inland Wetlands, using LiDAR Datasets. These scripts are created in Python and can be added in the ArcGIS® environment as a toolbox. The toolkit is currently being used as an aid for the researchers in hydrologic feature extraction by simplifying the workflows, eliminating human errors when providing the inputs, and providing quick and easy-to-use tools for repetitive tasks. This paper discusses the actual implementation of different workflows developed by Phil-LiDAR 2 Project 4 in Streams, Irrigation Network and Inland Wetlands extraction.

Paper Details

Date Published: 18 October 2016
PDF: 16 pages
Proc. SPIE 10005, Earth Resources and Environmental Remote Sensing/GIS Applications VII, 100050W (18 October 2016); doi: 10.1117/12.2241972
Show Author Affiliations
Noel Jerome B. Borlongan, Univ. of the Philippines Diliman (Philippines)
Roel M. de la Cruz, Univ. of the Philippines Diliman (Philippines)
Nestor T. Olfindo Jr., Univ. of the Philippines Diliman (Philippines)
Anjillyn Mae C. Perez, Univ. of the Philippines Diliman (Philippines)

Published in SPIE Proceedings Vol. 10005:
Earth Resources and Environmental Remote Sensing/GIS Applications VII
Ulrich Michel; Karsten Schulz; Manfred Ehlers; Konstantinos G. Nikolakopoulos; Daniel Civco, Editor(s)

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