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Articles | Volume XL-7/W3
https://doi.org/10.5194/isprsarchives-XL-7-W3-1123-2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-1123-2015
30 Apr 2015
 | 30 Apr 2015

THE PHIL-LIDAR 2 PROGRAM: NATIONAL RESOURCE INVENTORY OF THE PHILIPPINES USING LIDAR AND OTHER REMOTELY SENSED DATA

A. C. Blanco, A. M. Tamondong, A. M. C. Perez, M. R. C. O. Ang, and E. C. Paringit

Keywords: LiDAR, agriculture, forest, hydrology, renewable energy, coastal resources

Abstract. The Philippines embarked on a nationwide mapping endeavour through the Disaster Risk and Exposure Assessment for Mitigation (DREAM) Program of the University of the Philippines and the Department of Science and Technology (DOST). The derived accurate digital terrain models (DTMs) are used in flood models to generate risk maps and early warning system. With the availability of LiDAR data sets, the Phil-LiDAR 2 program was conceptualized as complementary to existing programs of various national government agencies and to assist local government units. Phil-LiDAR 2 aims to provide an updated natural resource inventory as detailed as possible using LiDAR point clouds, LiDAR derivative products, orthoimages and other RS data. The program assesses the following natural resources over a period of three years from July 2014: agricultural, forest, coastal, water, and renewable energy. To date, methodologies for extracting features from LiDAR data sets have been developed. The methodologies are based on a combination of object-based image analysis, pixel-based image analysis, optimization of feature selection and parameter values, and field surveys. One of the features of the Phil-LiDAR 2 program is the involvement of fifteen (15) universities throughout the country. Most of these do not have prior experience in remote sensing and mapping. With such, the program has embarked on a massive training and mentoring program. The program is producing more than 200 young RS specialists who are protecting the environment through RS and other geospatial technologies. This paper presents the program, the methodologies so far developed, and the sample outputs.