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.

ABSTRACT:Considering that the Philippines is archipelagic in nature and is exposed to disasters accentuated by climate change, water resource monitoring and management has been an important concern in the country. The design and implementation of an effective management scheme relies heavily on accurate, complete, and updated water resource inventories, usually in the form of maps and geodatabases. With the aim of developing a detailed and comprehensive database of all water resources in the Philippines, a 3-year project entitled "Development of the Philippine Hydrologic Dataset (PHD) for Watersheds from LiDAR Surveys", has been initiated by the University of the Philippines Diliman (UPD) and the Department of Science and Technology (DOST). Various workflows has been developed to extract inland hydrologic features in the Philippines using accurate Light Detection and Ranging (LiDAR) Digital Terrain Models (DTMs) and LiDAR point cloud data obtained through other government-funded programs, supplemented with other remotely-sensed imageries and ancillary information. Since the project covers national-scale mapping and inventory, the implementation was structured to be a collaborative effort between fifteen (15) State Universities/Colleges (SUCs) and Higher Education Institutes (HEIs), along with multiple National Government Agencies (NGAs) and Local Government Units (LGUs). This paper presents the project's general structure, focusing mainly on its attempts and accomplishments in strengthening individual capacities of all involved SUCs, HEIs, and stakeholders utilizing hydrologic data for different applications.

The Philippines is experiencing recurring drought events accentuated by the increasing incidence of the El Niño phenomenon, particularly due to its position in the equatorial region. To address the negative effects of unpredicted drought events, especially in light of perceptible climate change, the present research developed a methodology for drought assessment in the Cagayan River Basin (CRB) by combining remotely-sensed data including 16-day MODIS Vegetation Indices (VIs) (250 m resolution), monthly Terrestrial Water Storage Changes (TWSC) in 1° grids from NASA's Gravity Recovery and Climate Experiment (GRACE), and daily in-situ measurements of rainfall and water levels. Time series data of these parameters from 2002 to 2011, a period when major and minor drought events occurred in the country, were statistically analyzed. To smooth out short-term and random variations in the individual time series, a 3-period running average was first applied to each time series. The resulting time series datasets were then subjected to cross-correlation analysis to examine whether the VI anomalies and TWSC values were statistically related to rainfall and water level. The cross-correlation results showed that VI anomalies and TWSC values exhibited strong correlation with in-situ rainfall and water level measurements, having coefficients greater than 0.90 and low time lags ranging from 1 to 3 months during drought events. From this observation, lag-normalized correlation analysis between TWSC and VI anomalies was developed to characterize the onset of drought events and identify drought-prone areas. The majority of the areas identified as susceptible to drought are located in the provinces of Cagayan and Isabela, with areas of 2,596 ha or 68.21 % of the total land area of Cagayan, and 3,751 ha or 56.89 % of the total land area of Isabela. The findings in this research can serve as a basis for proper water resource allocation, especially in the identified drought-prone provinces in the country.

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Commission VI, WG VI/6 KEY WORDS: LiDAR, natural resources, agricultural, forest, coastal, hydrological, renewable energy ABSTRACT:The Philippines has embarked on a detailed nationwide natural resource inventory using LiDAR through the Phil-LiDAR 2 Program. This 3-year program has developed and has been implementing mapping methodologies and protocols to produce high-resolution maps of agricultural, forest, coastal marine, hydrological features, and renewable energy resources. The Program has adopted strategies on system and process development, capacity building and enhancement, and expanding the network of collaborations. These strategies include training programs (on point cloud and image processing, GIS, and field surveys), workshops, forums, and colloquiums (program-wide, cluster-based, and project-based), and collaboration with partner national government agencies and other organizations. In place is a cycle of training, implementation, and feedback in order to continually improve the system and processes. To date, the Program has achieved progress in the development of workflows and in rolling out products such as resource maps and GIS data layers, which are indispensable in planning and decision-making. Challenges remains in speeding up output production (including quality checks) and in ensuring sustainability considering the short duration of the program. Enhancements in the workflows and protocols have been incorporated to address data quality and data availability issues. More trainings have been conducted for project staff hired to address human resource gaps. Collaborative arrangements with more partners are being established. To attain sustainability, the Program is developing and instituting a system of training, data updating and sharing, information utilization, and feedback. This requires collaboration and cooperation of the government agencies, LGUs, universities, other organizations, and the communities.