LIDAR DATA PROCESSING AND VALIDATION IN LUZON: REGION III AND PANGASINAN (REGION I)

Central Luzon State University

Implementing Institution:

Institute for Climate Change and Environmental Management, Central Luzon State University

Funding Agencies:

Department of Science and Technology (DOST)

Monitoring Agency:

Philippine Council for Industry, Energy and Emerging Technology Research and Development (PCIEERD), Department of Science and Technology (DOST)

Duration of the Project:

April 2014 – March 2017

Project Objectives

1. To process data (LiDAR, Bathy, SAR) of selected rivers in Region 3 and Pangasinan.
2. To gather data for purposes of calibration and validation of hydrologic models and other products.
3. To generate and calibrate hydrologic and flood inundation models and real time inundation model (dependent on the availability of AWLS and Rain Gauges)
4. To produce and validate flood hazard maps.

Scientific Basis/Framework

The high data collection rate of LIDAR system requires a high data rate of instantaneous position and orientation. Current GPPS/INS systems could provide such data to geocode each range and intensity measurement. GPS would provide the three orientation parameters for the range vector, thus giving object space coordinates to each returning LIDAR pulse. The method of resolving strip discrepancies with the use of the physical sensor model and orientation measurement errors will be investigated. To aid in the determination of the conjugate points. Between strips, matching the range data but also on the intensity data is also examined, since LIDAR intensity can provide more variation on image texture and contrast compared to elevation data.

A filtering that makes use of surface information will also be examined. The DTM classification will have two phases. First the method searches the initial points and builds-up an initial, temporary TIN model, which are mostly below the ground and only vertices touch the ground. Data snooping will be done to filter out outliers in the data. In the second phase the model is lifted upwards for every point added to the TIN if it passes angle and distance limit conditions between it and the TIN. The method is done literately.

Significance

In recent years, earth surface height data has become a vital component of many geospatial planning strategies and is widely used by government agencies and the commercial sector for a variety of applications from flood risk modeling to urban development. The emergence of new spatial data acquisition systems such as Light Intensity Detection and Ranging (LIDAR) and Airborne Radar Interferometry (INSAR) presents complementary or even alternative solutions to the acquisition of spatial information unanswered by existing technologies such as aerial photography or satellite imagery. The coverage and accuracy of topographic data extracted by these systems, complemented by the features detected by an onboard digital aerial camera, provides rich information that would greatly benefit agencies using spatial data.

Before such data could be utilized, the raw data collected from the LIDAR and INSAR missions flights would need to undergo various processing steps to obtain information that are critical input to the calibration and validation of flood models for the watershed area. The enormous amount of LIDAR data should be filtered using various types of filters to extract the Digital Terrain Model (DTM) from the Digital Surface Model (DSM). The DTM is the boundary surface between the solid ground and the air, which is also the surface of superficial water run-off. This is the surface needed to model the geometry of the watershed and the floodplain. The DSM will be used in presenting the impact of flooding to man-made and natural features on the floodplain. Features significant to flood modeling and flood impact assessment such as buildings, forest cover, road and river network will also be extracted.

Data verification and validation project acts as a quality control for the output of the program. LIDAR is a rapid geospatial data acquisition system, that can output robust datasets and collect data in a wide range of conditions. But just like any other data acquisition system, it is subject to random and systematic errors. This project will carry out management activities prior to data collection to ensure that the raw and derived data pass the quality requirements of succeeding projects. This includes the calibration, ground validation surveys, and review of data collection activities. It also involves consistent checking to ensure the integrity, correctness and completeness of the data.

The ongoing DOST-GIA Nationwide DREAM Program covers only 1/3 equivalent to 100,000 sq.km. of 18 major river basins in the Philippines. The proposed program aims to cover the remaining 2/3 of river systems in the country by tapping the State Colleges and Universities (SUCs) and private higher education institutions (HEIs) nationwide in the processing and validation components of the program.