The Phil-Lidar 2 Program: National Resource Inventory of the Philippines Using Lidar and Other Remotely Sensed Data

Abstract

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.

Data on the techno-economic and financial analyses of hybrid renewable energy systems in 634 Philippine off-grid islands

“…The monthly average GHI and wind speeds were obtained from the Phil-LIDAR 2 database [7] . The original dataset primarily covered the mainland, so nearest neighbors interpolation was performed to obtain data at more distant islands.…”

Editing Cumulated Landscapes: Point Cloud Modeling as a Method of Analysis in Landscape Design

“…Meanwhile, in the context of landscape planning, small topographic differences can have severe implications for land management. For this reason, institutes carry out scanning missions on a regional scale for purposes such as to assess the flood risk in the Philippines (Blanco, Tamondong, Perez, Ang, & Paringit, 2015), to monitor water flow and dikes in the Netherlands (Nationaal Georegister Netherlands, 2007, and to supervise coastal areas in the United States (Davidson & Miglarese, 2003).…”

Towards nationwide mapping of bamboo resources in the Philippines: testing the pixel-based and fractional cover approaches

“…Existing high-resolution maps in the country could have provided this information gap. However, the official LULC maps in the Philippines are commonly confined with generic land cover classes, while recent LiDAR-based land-use maps only focused on lowland agriculture (Blanco et al 2015). Global bamboo maps can provide nationwide bamboo numbers (Du et al 2018) if they are open access and with uncertainty estimates to assess their usability at local scales.…”