The University of San Carlos (USC) in Cebu City is one of the fourteen partner universities of the PhilLiDAR 1 (Hazard Mapping of the Philippines Using LiDAR) research program funded by the Department of Science and Technology (DOST)with the Philippine Council for Industry, Energy, and Emerging Technology Research and Development (PCIEERD). The research program is spearheaded by the College of Engineering, University of the Philippines-Diliman through the Training Center for Applied Geodesy and Photogrammetry (TCAGP) with Dr.Enrico Paringit as program leader. The program will run for three years from 2014 to 2017.

  The objectives and the corresponding expected outputs of the program are the following:



Expected Outputs

Continue acquiring LiDAR datasets in critical areas not covered by the DREAM programLiDAR point clouds
Obtain digital elevation models (DEM)Digital surface model (DSM) and digital
terrain model (DTM)
Extract features essential to flood modeling and hazard assessmentSurface feature heights and laser intensity in digital standard (binary) format
Conduct ground validation of the data

generated by the Data Acquisition
Component (DAC)
Conduct topographic and hydrographic

surveys to obtain river profile and cross-

section data that will be integrated into
Elevation datasets
Conduct hydrologic measurements necessary for flood model calibration and validationFlood hazard maps of 2/3 of the country
Generate flood hazard maps


To carry out the above objectives the Phil LiDAR 1 research program is subdivided into component projects namely:

  1. The Data Acquisition Component (DAC) – responsible for the acquisition of LiDAR Data
  2. The Data Validation and Bathymetry Component (DVBC) – responsible for the conduct of  validation,topographic and hydrographic measurements.
  3. Data Processing Component (DPC) – responsible for the processing of LiDAR data, and generation of digital    elevation models and their calibration.
  4. Flood Modeling Component – responsible for flood modeling.

Data Archiving and Distribution Component (DAD) – responsible for the archiving and distribution of all data    sets and products.

                To facilitate collaboration between UP-Diliman and the partner universities in each region of the country, Program B under Phil LiDAR 1 was established and is known as ‘LiDAR Data Processing and Validation by SUCs and HEIs’. Under this program a project in each SUC/HEI is identified; for USC it is called Project 8. LIDAR Data Processing and Validation in the Visayas: Central Visayas (Region 7), which is also known as Phil LiDAR 1.B.8. The partner universities are shown in Figure 1.1. They are grouped into clusters, namely the Luzon Cluster, the Visayas Cluster, and the Mindanao Cluster. The schematic flow of data is shown in Figure 1.2.



  Figure 1.1. Partner universities and the corresponding project sites of the Phil LiDAR 1

                    Figure 1.1. Partner universities and the corresponding project sites of the Phil LiDAR 1 research program. The partner universitiesare grouped into clusters: Luzon Cluster, Visayas Cluster, and Mindanao Cluster. Phil LiDAR 1.B.8 is officially known in the University of San Carlos (USC) as USC Phil LiDAR 1. It is housed at the USC Phil LiDAR Research Center, Josef Baumgartner Learning Resource Center, University of San Carlos-Talamban Campus, Nasipit, Talamban, Cebu City. Our organizational structure is shown in Figure 1.3. The project started in April 2014 and will end in March 2017.





  Figure 1.3. The organizational structure of USC Phil LiDAR 1



  Figure 1.4. The new USC Phil LiDAR 1 team

                 Since the start of the project there were two occasions that the composition of the USC Phil LiDAR 1 team was altered. The first one was when Denniel Hurboda a research associate resigned to enroll in the M.S. Chemistry program in Ateneo de Manila University. The second occasion was when the Chief Science Research Specialist, Dr. Marlowe Edgar Burce, resigned to take the position of Chair of the USC Computer Engineering Department. The new team is shown in Figure 1.4.