The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLI-B4
https://doi.org/10.5194/isprs-archives-XLI-B4-195-2016
https://doi.org/10.5194/isprs-archives-XLI-B4-195-2016
13 Jun 2016
 | 13 Jun 2016

DATA ARCHIVING AND DISTRIBUTION OF LiDAR AND DERIVED DATASETS IN THE PHILIPPINES

M. E. A. Tupas, S. C. Lat, and R. A. Magturo

Keywords: LiDAR, Geospatial Data Infrastructure, Data Archiving and Distribution, Geospatial Database, Web Standards

Abstract. LiDAR programs in the Philippines have been generating valuable resource and hazard information for most of the country at a substantial rate since 2012. Significant progress have been made due to the programs design of engaging 16 Universities and research institutions spatially distributed across the country. Because of this, data has been accumulating at a brisk rate which poses significant technical and logistic issues. While a central node, the University of the Philippines, Diliman, handles data acquisition, pre-processing, and quality checking, processing and ground validation are devolved to the various nodes. For this setup to be successful, an efficient data access and distribution system should be in place.

In this paper, we discuss the spatial data infrastructure and data access protocols implemented by the program. At the center of the data access and distribution operations is LiPAD or our LiDAR portal for archiving and distribution. LiPAD is built on open source technologies, established web standards, and protocols. At its back-end a central data archive has been established using state of the art Object Storage technology to store both raw, processed Lidar and derived data sets. Catalog of available data sets ranging from data acquisition foot prints, to DEM coverages, to derived products such as flood hazard, and crop suitability are viewable and accessible on the main site based on the popular GeoNode application. Data exchange is performed using varying protocols to address various logistical problems. Given the various challenges the program is successful in distributing data sets not just to partner processing nodes but to other stakeholders where main requesters include national agencies and general research and academic institutions.