Disseminating near real-time hazards information and flood maps in the Philippines through Web-GIS

Alfredo Mahar Francisco A. Lagmay, Ph.D., Bernard Alan B. Racoma, Ken Adrian B. Aracan, Jenalyn A. Alconis-Ayco, Ivan Lester Saddi
National Institute of Geological Sciences, University of the Philippines
C.P. Garcia cor. Velasquez Street, UP Diliman, Q.C.

This was published in the Journal of Environmental Sciences on 18 March 2017. You may find it in their website here.

Abstract

The Philippines being a locus of tropical cyclones, tsunamis, earthquakes and volcanic eruptions, is a hotbed of disasters. These natural hazards inflict loss of lives and costly damage to property. Situated in a region where climate and geophysical tempest is common, the Philippines will inevitably suffer from calamities similar to those experienced recently. With continued development and population growth in hazard prone areas, it is expected that damage to infrastructure and human losses would persist and even rise unless appropriate measures are immediately implemented by government. In 2012, the Philippines launched a responsive program for disaster prevention and mitigation called the Nationwide Operational Assessment of Hazards (Project NOAH), specifically for government warning agencies to be able to provide a 6 hr lead-time warning to vulnerable communities against impending floods and to use advanced technology to enhance current geo-hazard vulnerability maps. To disseminate such critical information to as wide an audience as possible, a Web-GIS using mashups of freely available source codes and application program interface (APIs) was developed and can be found in the URLs http://noah.dost.gov.ph and http://noah.up.edu.ph/. This Web-GIS tool is now heavily used by local government units in the Philippines in their disaster prevention and mitigation efforts and can be replicated in countries that have a proactive approach to address the impacts of natural hazards but lack sufficient funds.

Introduction

A societal problem that persists necessitates an immediate solution if the very nature of the community’s existence is in peril. Year after year, the Philippines is devastated by calamities that result in numerous loss of lives, damage to property and economic losses by the billions. In 2011 alone the Philippines was hit by at least 3 devastating storms eroding progress on poverty reduction and developmental gains in the country. Tropical Storm Washi (local name Sendong) and its consequent floods, killed 1257, injured 6071, and affected 1,141,252 families in Luzon (ADRC, 2011). Months prior to Tropical Storm Washi, the tropical cyclone tandem of Typhoon Nesat (local name Pedring) and Tropical Storm Nalgae (local name Quiel) inflicted 102 fatalities and ravaged crops and infrastructure worth more than PhP15 billion ( NDRRMC (National Disaster Risk Reduction and Management Council), 2011a; NDRRMC (National Disaster Risk Reduction and Management Council), 2011b ;  Elona, 2011). In 2012, a strong local earthquake shook Negros and Cebu in Central Philippines leaving 51 dead and 62 missing with total damage amounting to PhP363.5 million (NDRRMC, 2011c). Deaths were attributed mainly to landslides triggered by the temblor. A year after, another earthquake devastated Bohol Island followed a month later by deadly storm surges spawned by Typhoon Haiyan (Lagmay and Kerle, 2015). The Bohol earthquake killed 222 people (NDRRMC, 2013), whereas the Haiyan storm surges left more than 6300 dead in the Central Philippines region (Lagmay et al., 2015). The problem of climate- and geophysical-related disasters is a perennial problem in the Philippines and requires swift and immediate action to mitigate its impacts. The human and financial cost of these disasters is high and all possible means of addressing the problem need to be explored with new approaches in the disaster effort, tested.

This paper elucidates the Nationwide Operational Assessment of Hazards (Project NOAH), a program, which undertakes disaster science research development, advances the use of cutting edge technologies and promotes innovative information services for government’s disaster prevention and mitigation efforts. Through the use of science and technology and in partnership with the academe and other stakeholders, the Department of Sciences and Technology (DOST) takes a multidisciplinary approach in developing systems, tools, and other technologies that could be used by the government, in particular the National Disaster Risk Reduction and Management Council (NDRRMC) and the Office of Civil Defense, in efforts to mitigate the adverse impacts of extreme natural events. By investing in new technologies and new scientific approaches to disaster mitigation, Project NOAH seeks to enhance disaster management and prevention capacity of the Philippines.

Initial efforts of Project NOAH include: deployment of weather-related sensors such as rain gauges and water-level sensors; use of state-of-the-art methods to construct high-resolution flood and landslide hazard maps that are relevant to the community; delivery of readily accessible, timely and accurate hazards information through various media and communication platforms; multidisciplinary disaster research and development; integration of disaster efforts by the national government, academe, civil society organizations and private sector; empowerment of Local Government Units and communities by providing open access to near-real-time data and information; and application of a bottom-up disaster prevention approach for more resilient communities.

1. State-of-the-art technologies

1.1. Estimation of rainfall probability

The percent chance of rain (PCOR) or probability of rain is calculated using processed infrared and water vapor satellite image data and Doppler data obtained at near-real-time in combination with statistical evaluation of historical rainfall. Forecasts of the PCOR are based on these sources as well as an algorithm for cloud trajectory prediction using image processing techniques based on the ForTraCC method (Vila et al., 2008). The PCOR is calculated every 30 min for all major cities of the country. The forecast is done for 1, 2, 3 and 4 hr lead-time and the forecasts have an average accuracy of 82.68% (Racoma et al., 2015).

1.2. Weather and water-level sensors

As part of the Development of Hybrid Weather Monitoring System and Production of Weather and Rain Automated Stations Project of DOST Advanced Science and Technology Institute (DOST-ASTI), locally-assembled Automated Weather Stations (AWSs) and Automated Rain Gauges (ARGs) have been installed in key areas across the country to complement the Philippine Atmospheric Geophysical and Astronomical Services Administration’s (PAGASA) weather monitoring facilities (DOST-ASTI, 2011).

The AWSs are monitoring stations equipped with different sensors capable of measuring wind speed and direction, air temperature, air humidity, air pressure, and rain amount, duration and intensity. ARG stations only measure rainfall amount and intensity. The weather data are sent wirelessly through the cellular network as a text message through Short Messaging Service (SMS). Card slots within the digital box are also in place for possible upgrade of the system to have an Iridium satellite backup and radio communication capabilities. Each station is equipped with the DOST-ASTI-developed data-logger platform Global System for Mobile Communications (GSM) Data Acquisition Terminal that serves as the central processing unit that intelligently controls all the functions and data communications of the station. Designed to be rugged and standalone, the station can be deployed even in the harshest remote areas and can operate continuously. The instrument gets power from the sun and is backed up by the internal rechargeable battery. All weather data from the remote stations are collected on a central database server and further analyzed (DOST-ASTI, 2011).

Standalone Water Level Monitoring Sensors (WLMSs) have also been deployed along the Marikina River in 2010 for the rehabilitation of the Effective Flood Control Operation System (EFCOS) of the Metro Manila Development Authority (MMDA). The WLMS is equipped with a solar panel and makes use of an ultrasonic sensor to measure the current water-level using the principle similar to radar and sonar. The sensor calculates the time interval between sending the signal and receiving the echo to determine the water-level. The data collected are then transmitted to a central server at a predefined interval, via SMS and are streamed into the NOAH website every 10 min.

Currently there are 81 AWSs and 872 ARGs from DOST-ASTI that stream data every 15 min to the Project NOAH website. On the other hand, a total of 441 WLMS instruments have been deployed along major rivers across the Philippines for early warning on imminent floods.

1.3. Light Detection and Ranging (LiDAR) and radar-derived topography

In terms of disaster management strategies, high-resolution hazard maps (1:5000 to 1:25,000 scale) based on similarly high-resolution topographic maps or cadastral level maps are very important (EXCIMAP, 2007). Members of the public are more interested in disaster risk that directly applies to them and as such, become aware of the hazard problems in their community with high-resolution maps. Getting individuals to identify with the problem is a key element since awareness is the first step towards building disaster resilient communities. High-resolution charts also provide more detailed scientific analysis of natural hazard phenomena, before, during and after the disaster event. Unfortunately, there is a dearth of 1:5000 to 1:25,000 scale base maps of the Philippines to build on.

To address the problem of lack of available high-resolution topographic maps for most of the country, the Philippine government acquired geospatial data through LiDAR and airborne Interferometric Synthetic Aperture Radar (IfSAR), high-resolution Digital Terrain Models (DTMs) to cover the 300,000 km2 land area of the country. LiDAR shall be used to generate high-resolution and up-to-date detailed national elevation dataset maps at 1:5000 scale with 1 m horizontal and 0.2 m vertical resolution of the lowlands. Radar remote sensing shall be used to provide at least 1:10,000 scale hydro-corrected topographic maps of the mountainous areas with 5 m horizontal resolution and about 0.5 m vertical accuracy.

1.4. 1 Dimensional and 2 Dimensional flood simulations and crowd sourcing of flood events

Once the high-resolution topographic maps are made available, different models such as the Hydrologic Engineering Center’s Hydraulic Modeling System (HEC-HMS), FLO-2D and ISIS 2D were used to simulate one-dimensional channel flow and two dimensional floodplain inundation maps. The HEC-HMS is designed to simulate the precipitation-runoff processes of dendritic watershed systems. The program produces hydrographs that are used directly or in conjunction with other software for different hydrologic studies which include but are not limited to flow forecasting, flood damage reduction, and floodplain regulation (US Army Corps of Engineers, 2013). Discharge rates collected from the HEC-HMS software for Rainfall Intensity Duration Frequency data retrieved from DOST-PAGASA and historical as well as real-time rainfall data shall be used as an input parameter for 2 Dimensional flood modeling using FLO-2D, and ISIS 2D.

A system has been developed for receiving, processing and visualizing spatiotemporal data allowing concerned citizens to provide and view flood data on a map. The system supports automation of data processing for filtering reports of flood events. Also in the system are clustering and aggregation of flood data entries with the option of adding arbitrary attributes, which allow better visualization of inundation in areas swamped by floods (Victorino et al., 2016). The Flood Reporting and Mapping System is an easy to use visualization tool, important for creating permanent records of flood events in urban areas. Unlike other existing web-based crowd sourcing systems, which exercise proprietary rights to their product, our crowd sourcing solution is open-source, free of charge and uses an automated filtering method. The crowd sourcing facility of Project NOAH is linked to http://www.nababaha.com where it was first deployed.

1.5. Landslide inventory, simulations and monitoring

The availability of high-resolution topographic maps for the entire Philippines, such as those generated by LIDAR surveys, paved the way for the conduct of more sophisticated means of identifying landslide-prone areas. Previously available downloadable maps provided by civil authorities show large areas of mountainous areas as landslide-susceptible. However, by conducting computer-assisted analyses of mountainsides with landslide scars, concave planform areas, storm runoff convergence and structurally controlled failure slopes, the selection of landslide vulnerable sites is narrowed down.

Identification of shallow translational slides and debris flow source areas was done using the Stability Index Model software (Pack et al., 1998) while structurally controlled landslide potential zones were determined using COLTOP 3D and the Matterocking 2.0 software (Jaboyedoff, 2002) whereas propagation zones from structurally controlled unstable regions were assessed with the Conefall software (Jaboyedoff, 2003). A landslide inventory combined with slope stability models were used to produce the landslide zonation maps (Rabonza et al., 2015; Alejandrino et al., 2016 ;  Luzon et al., 2016). With the help of both LiDAR-derived high-resolution topographic maps and the aforementioned software, instead of having the entire span of a mountain depicted as landslide-susceptible areas only certain sectors of the mountain are mapped as landslide-susceptible. Similarly, combining the high-resolution topographic maps with remote sensing and computer-assisted analysis of slopes and structures, provides a solution to the previous concern that nearly the entire Philippines is rendered unsafe by gravity failure of slopes and floods.

Early warning systems for landslides and slope failures deployed in the real world using alternative instrumentation was developed by the University of the Philippines scientists under the DOST Grants in Aid Program (Catane et al., 2011 ;  Marciano et al., 2011). The landslide monitoring system which is composed of a sensor column with tri-axial accelerometers and capacitive sensors are buried vertically underground in a borehole to measure tilt and water content. Accessed via a Controller Area Network (CAN) communications protocol, the monitoring instrument sends data to a remote host for post-processing using a GSM cellular infrastructure for post-processing ( Marciano et al., 2011). Instruments have been deployed in 2 sites in Benguet, and 2 sites in St. Bernard, Leyte. Another 7 sites in Benguet, Iloilo, Negros Oriental, Surigao del Norte and Surigao del Sur have been targeted for the landslide sensor monitoring.

1.6. Storm surge simulations and hazard maps

FLO-2D was used to simulate coastal flooding from potential storm surges by specifying water surface elevation as a function of time (stage-time relationship) for model grid elements along the coast. The model outputs are the predicted flow depths, velocities, discharge hydrographs, dynamic and static pressure, specific energy, and area of inundation. Input parameters for inundation are the time series results from the Japan Meteorological Agency (JMA) Storm Surge Model and the astronomical tide levels from WXTide, which are combined together to create the stage-time relationship. Airborne IfSAR derived DTMs with a spatial resolution of 5 m was used to represent the topography of the study area. Appropriate Manning’s n roughness coefficient, based on land cover, was also assigned to the grid elements to represent the land friction value. Since inundation starts at the shoreline, the detailed shorelines of the cities were also traced using high-resolution imagery. These were identified in the grid system of the model and assigned the timestage storm tide data.

1.7. Mapping platform mashups and the world-wide web

Programmers of Project NOAH created mapping platform mashups to tailor fit the web product for disaster response and mitigation purposes. These mashups combine public domain web information with open Application Programming Interfaces (or APIs) to facilitate communication between the mapping platform and different data sources. OpenLayers, an open-source dynamic mapping platform is used in the Project NOAH website to embed the web map service of Google and other online mapping services such as OpenStreetMap on a webpage. Using this platform, sensor data and hazard maps are overlain to achieve the end product of which is a web-based disaster Geographic Information System (Web-GIS) dedicated for addressing Philippine disaster problems.

2. Results

Pertinent meteorological data from DOST-PAGASA and DOST-ASTI, flood maps generated by the Disaster Risk Exposure Assessment and Mitigation (DREAM)/LiDAR program and rainfall prediction of the ClimateX component of Project NOAH are now collected and displayed in the website. This website is currently hosted in the Amazon Web Services platform and local Philippine servers housed at DOST-ASTI. To ensure continuity of service even during periods of heavy access, all disaster layers were placed and cached in a GeoServer in DOST-ASTI while near-real-time data from the sensors and PAGASA Doppler Radar stations are pulled from DOST-ASTI servers.

The Project NOAH website is one way by which near-real-time and hazards information are disseminated to the general public. It is a means by which communities and the local government units can be informed with such data, critical for the assessment of the situation in their area and for decision making prior, during and after extreme weather disturbances. Other forms of disseminating Project NOAH information in the near future will be through a weather media channel called DOSTV, radio broadcasts, SMS, Twitter, Facebook, as well as Android, iPhone and iPad apps. All forms of media platforms will be utilized to notify the people of flood hazard areas and provide near-real-time weather information. Currently, Project NOAH displays the following features in its websites at http://noah.dost.gov.ph and http://noah.upd.edu.ph.

2.1. Probability of rain

The PCOR or probability of rain is displayed in the website (Fig. 1). By selecting the checkbox for probability of rain in the weather outlook tab, forecasts for the major cities are shown every hour up to the next 4 hr. The probability of rain is displayed as weather icons and percentage chance: a sun or moon icon represents 0%–20% chance of rain; a sun or moon with a cloud for rainfall probabilities 20%–30%; an overcast icon for 30%–40% chance of rain; a cloud with light to moderate rain image for 40% to 60% chance of rain; and a dark cloud with heavy rain symbol for 60%–100% probability of rain. There are no 0% and 100% forecasts of chance of rain.

Fig. 1: Percentage chance of rain for key cities in the Philippines.

This feature of the NOAH website can be used for a variety of purposes. The primary intent is for disaster preparedness. However, it can also be used by farmers who want to know when to dry rice grain, fishermen who would like to check the sea condition, construction workers who need to know when to pour cement, and even by cleaners who need to ensure sweet-smelling sun-dried laundry. Its practical application as an outdoor reference tool is diverse.

2.2. Weather stations and stream gauges

AWSs and ARGs record rainfall intensity over time, which are then classified into light (< 2.5 mm/hr), moderate (2.5 < 7.5 mm/hr), heavy (7.5 < 15.0 mm/hr), intense (15 < 30.0 mm/hr), or torrential rain (> 30.0 mm/hr). They are color coded based on the PAGASA rain classification scheme into light blue, blue, dark blue, orange and red, respectively. The graphs of measured rainfall values already translated into intensity values in mm/hr (Fig. 2).

Fig. 2: Automated Weather Stations (AWSs), Automated Rain Gauges (ARGs) and water-level sensor distribution in the Philippines. Charts on the right side are rainfall and water-level data for each sensor represented in graphical form.

Stream gauges or WLMSs on the other hand are useful for monitoring river flooding. This information must be used in tandem with the known levels of flood along the river and their corresponding effects and actions to be taken by the community. Water-levels for previously surveyed stations are categorized according to the EFCOS assessments level (Table 1).

Station Levels

Montalban

Nangka

Sto Nino

Rosario

Napindan

Pandacan

San Juan

Normal <22.4 <17.1 <13.0 <12.5 <10.9 <11.0 <17.1
Alert 22.4 17.1 13.0 12.5 10.9 11.0 17.1
Alarm 23.0 17.7 14.1 13.2 11.9 11.5 17.7
Critical 23.6 18.3 14.9 13.8 12.0 12.0 18.3

Table 1: Effective Flood Control Operation System (EFCOS) assessment levels based from the 1999 feasibility study. Values are in meters above mean sea level.

Rain, temperature, pressure and humidity measured by the AWS sensors are interpolated and then plotted into a contour map using the radial basis function or RBF (Piazza et al., 2015). By looking into these contour maps, the viewer is provided with a quick look at the rain, temperature, pressure and humidity conditions of every part of the Philippine land territory (Fig. 3). The accuracy of the contour maps also becomes better as the deployment of the more than 1000 automated sensors progresses. However, these maps only give a general overview of the rain, pressure and temperature conditions, are useful for visualization purposes, and at this point should not be used as parameters for scientific calculations. Contour maps are also made available for accumulated rainfall every 3, 6, 12 and 24 hr to determine the amount of rain that has been delivered over a watershed for certain time periods. When matched with the historical record of the country’s weather bureau since 1951, it provides a gauge on the scale of flood that may occur over an area (i.e., flood generated by a 5-year, 25-year or 100-year rain return).

Fig. 3: Contour maps of rainfall, temperature, pressure and humidity for visualization of the general weather condition of the Philippines.

2.3. Other weather-related imagery

Weather satellite data are also displayed in the Web-GIS platform. Previously, weather satellite data from MTSAT or Multi-Functional Transport Satellite were displayed in the Web-GIS platform. The MTSAT images are downloaded by the PAGASA ground receiving station and provided a view every 30 min of the clouds and general weather condition of the Philippines and surrounding seas. Currently, these images along with the Doppler data are processed for predicting the probability of rain in key cities of the Philippines. When the MTSAT was decommissioned however, it was replaced by the Himawari-8 satellite in 2015 which provided images with higher spatial and temporal resolution compared to its predecessor (MSC, 2015). As such, the colorized infrared band of the Himawari-8 weather satellite imagery is now displayed in the Project NOAH website (Fig. 4).

Fig. 4: Himawari-8 weather satellite view of the Philippines and surrounding seas.

Doppler Radars from DOST-PAGASA are configured to detect moisture or precipitation in the air and calculate its volume and movement. Currently, there are nine DOST-PAGASA Doppler Radar stations that stream real-time information every 10 min to the NOAH website (Fig. 5). These are the Appari, Baguio, Subic, Tagaytay, Baler, Virac, Cebu, Hinatuan and Tampakan stations. However, connectivity issues have resulted to intermittent Doppler Radar feeds but have been mainly reliable during severe weather events over the past 5 years. A total of 14 Doppler stations were targeted for completion by PAGASA by the year 2013. The other stations located in Guiian, Busuanga, Iloilo, Zamboanga and South Palawan are also planned to be incorporated into the NOAH website to complete the ground radar coverage of the entire Philippines.

Fig. 5: The Doppler Radar image from the Virac Radar station of Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA).

The Doppler Radar images contain important rainfall intensity information derived from Radar reflectivity readings. Detected clouds are colored to represent the calculated rainfall intensity in mm/hr. It helps determine if the rain cloud hovering an area could precipitate light, moderate, heavy, intense or torrential type of rain. The colored scale bar to the left of the panel serves as reference to the meaning of the color with respect to the intensity of occurring rain.

2.4. Flood maps

Flood maps are currently being displayed in the Project NOAH website (Fig. 6). As of the time of writing this paper, inundation maps corresponding to 5-, 25-, and 100-year rainfall return events are available for the Marikina, Bicol, Cagayan de Oro, Iligan, Pampanga, Agno, Jalaur, Ilog-Hilabangan, Panay, Davao, Mag-asawang Tubig, Tullahan, Tagum-Libuganon, Tagoloan, Buayan-Malungun, Agusan, Cagayan, Mindanao, Infanta, Lucena, Iponan, Mandulog and Angat river basins (Table 2). Most in the list are the major river basins, identified by the Department of Public Works and Highways (DPWH) as the most vulnerable to extreme flooding in the country based on historical data. Flood simulations using LiDAR DTMs as base topography are being prepared for another 244 river basins and targeted for completion by the first quarter of 2018.

Fig. 6: Static flood hazard map of Marikina City showing high, moderate and low flood hazard levels with Filipino Boxer Legend Manny Pacquiao as height reference. Red = high hazard, Orange = medium hazard and Yellow = low hazard. Overlain on the flood hazard are the citizen reports used to validate the inundation maps. Red, orange and yellow dots refer to high, moderate and low flood reports, respectively. Green dots refer to areas where there are no flood occurrences.

River Basin

Target Date

Status

Marikina River Basin

July 2012

Completed
Bicol River Basin

July 2012

Completed
Cagayan de Oro River Basin

July 2012

Completed
Iligan River Basin

July 2012

Completed
Pampanga River Basin

July 2012

Completed
Agno River Basin

July 2012

Completed
Jalaur River Basin

December 2012

Completed
Ilog-Hilabangan River Basin

December 2012

Completed
Panay River Basin

December 2012

Completed
Davao River Basin

December 2012

Completed
Magasawang Tubig River Basin (Mindoro)

December 2012

Completed
Agus River Basin

December 2012

Completed
Tagum-Libuganon River Basin

December 2012

Completed
Tagoloan River Basin

December 2012

Completed
Buayan-Malungun River Basin

December 2012

Completed
Agusan River Basin

June 2012

Completed
Cagayan River Basin

June 2015

Completed
Mindanao River Basin

June 2013

Completed
Infanta River Basin

September 2014

Completed
Lucena River Basin

September 2014

Completed
Iponan River Basin

December 2013

Completed
Mandulog River Basin

December 2013

Completed
Angat River Basin

December 2014

Completed

Table 2: List of the 18 major river basins (and some critical river basins) prioritized by Project Nationwide Operational Assessment of Hazards (NOAH) under the Disaster Risk Exposure Assessment and Mitigation (DREAM) Program

At the left hand side of the flood hazards panel is the inundation height relative to boxing legend Manny Pacquiao who represents the typical Filipino height of 5′6″ (167.64 cm). Three colors representing flood heights can be seen in both the map and legend. The yellow color means inundation less than or equal to 0.5 m, orange means flooding 1.0 m high, while the red color represents greater than 1.5 m floods (Fig. 6).

The high-resolution static flood maps are necessary for planning localized emergency response (i.e., evacuation and access routes, road closures) and for people to become aware of the hazards in their community ( Lagmay, 2011). Longer term development plans of cities can be based on these high-resolution flood hazard maps and compromised areas should be avoided in future development.

The flood reporting system on the other hand is a web-based interactive map that shows flood levels in Metro Manila. It was originally created to serve as a permanent record of the Ondoy floods to help keep future residents of the metropolis reminded of the catastrophe. Refinements to the system, including crowd sourcing and filtering, now allow inputs for floods in Metro Manila spawned by any type of rainfall event (Victorino et al., 2016). The collective anecdotal accounts of the inundation of the metropolis and adjacent areas are used to validate computer generated flood simulations (Fig. 6) and can serve as a standalone flood hazard map should there be a large number of citizen reports.

2.5. Landslides

Due to the extraordinary threat posed by meteorological hazards to communities in the Philippines, a map database for landslide-susceptible areas was produced on a nationwide scale and available for viewing in the Project NOAH website. The mapping effort depicts the potential sites for the occurrence of 4 broad categories of landslides that can be triggered by extreme rainfall, namely: fall, topple, slide and flows (Varnes, 1978). Lateral spreads, which are mainly associated with an earthquake trigger as well as extremely long-runout landslides are not included in the analysis. These barangay-level (village-level) landslide maps are important for raising disaster awareness and act as reference for preparedness plans of communities.

The accuracy of the maps was verified using a nationwide landslide inventory comprised of 12,694 landslide points placed near the crown of each identified landslide event. The inventory of landslides was determined from the analysis of high-resolution optical imagery gathered between 2003 and 2015. Out of the total landslide inventory, 96.07% fall under the areas mapped to be susceptible to landslides. The areas delineated with the highest susceptibility contains 7249 landslides (57.11%), moderately susceptible areas contain 4383 landslides (34.52%) and the areas with the least susceptibility contain 563 landslides (4.44%).

Potential landslide areas are represented in three colors (Fig. 7). Red means the most dangerous and is recommended as a no dwelling zone. Should people still to choose to live in these hazardous areas, they must know the risk and be prepared. Orange is identified as moderately susceptible to landslides. These areas are also known to experience downward earth movements based on the landslide inventory. However, with proper slope protection and intervention as well as continuous monitoring of instability, structures may be built. The yellow zones are also susceptible to landslides but to a lesser extent and can be inhabited but with proper site assessment and continuous monitoring of slope instability. In terms of landslide susceptibility, all areas without any color are the most suitable areas for land development, safe evacuation, and siting of critical infrastructure such as hospitals, search and rescue depots, power plants, telecommunication centers, food warehouses, banks, water facilities, evacuation centers, government agencies, and transportation hubs.

Fig. 7: Landslide hazard maps for potential shallow landslides, deep-seated landslides and debris flows in alluvial fans.

2.6. Storm surge inundation maps

Project NOAH has previously identified storm surge vulnerable areas in the Philippines by simulating worst case scenarios over different coasts (Lapidez et al., 2015). Stemming from this study, storm surge hazard maps for all coastal provinces of the Philippines were subsequently made available in the Project NOAH website. These maps are for various levels of storm surge inundation and are classified according to advisory levels. Advisory levels 1, 2, 3 and 4 refers to storm surge inundation up to 2, 3, 4, and 5 m storm surge height, respectively (Fig. 8). These detailed maps available through the NOAH website along with the advance warning of Typhoon Hagupit (local name Ruby) helped mitigate the loss of life when Hagupit’s storm surges destroyed at least 1800 homes in December 2014 as it made landfall in the eastern part of the Central Philippines region ( Lagmay and Kerle, 2015). Since then, these hazard maps have been used by local government units and individuals to plan evacuation when there is an advisory from the NDRRMC on possible storm surge inundation whenever there is a tropical cyclone that enters into the Philippine Area of Responsibility.

Fig. 8: Storm surge inundation map for advisory level 4 (5 m) in the area of Northern Leyte and Samar. The legend on the left side of the panel shows the height of storm surge inundation relative to the Filipino boxing legend Manny Pacquiao who is 5′7″ inches in height.

3. Conclusions and recommendations

The latest government initiative of government seeks to share critical data to the public in order to empower communities. Project NOAH allows access to supplementary information apart from those already provided by civil authorities for local government units to have more facts available as basis for making critical decisions to defend themselves against imminent danger. The near-real-time information streamed through the internet and broadcast through other media platforms make full use of technological advances in mass communication for the benefit of people at risk from natural hazards.

Government has funded the survey of the entire Philippines using LiDAR and radar remote sensing technology, to generate high-resolution hazard maps relevant for community preparedness and development planning. Without these maps, majority of the Philippines would only have regional scale maps that are only appropriate for regional scale planning. Community or local scale hazard maps are the kind maps that people identify with because they are able to see the exposure of their properties and familiar places to danger. It raises their awareness, an important step to promote vigilance against natural hazards. The project aims to complete the flood hazard maps by the end of the year 2017, a task that could not be met without the use of a rapid topographic data acquisition system such as LiDAR.

Computer-assisted mapping which can build scenarios of possible hazards allows an understanding of disaster problems that beset us. It can be utilized to avoid surprise. The staggering impacts of Tropical Storm Ondoy and Typhoon Haiyan caught everyone unprepared by not realizing that such magnitude of inundation can occur. Elevated places normally not flooded were inundated and this could have been recognized in advance, information that is crucial for disaster preparedness.

Project NOAH is still in its infancy. It still has a long way to go in demonstrating its value in addressing a social problem imposed by natural events. This latest government initiative promotes frontier science and technology and establishes research and development platforms as key elements to assure homeland security. It is however, not a complete solution. Society would need to embrace the program and make it a rallying point for establishing a culture of safety. No matter how much the government delivers, it still rests on the people on how to use it wisely.

Acknowledgments

We wish to acknowledge the Department of Science and Technology Grants in Aid program for funding the Web-GIS project, the Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA), Nationwide Operational Assessment of Hazards researcher scientists and the National Institute of Geological Sciences, University of the Philippines for their support, the Japan Meteorological Agency (JMA) for the use of their software and all other collaborators in this huge interdisciplinary disaster reduction effort using the latest available science and technologies.

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5 Comments:

  1. Congratulation for P-NOAH for its almost three years in the service to the Filipino Peoples…

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  3. Good day! How can we download data especially shapefiles from your site like flood hazard and Landslide? Thanks!

    • Hi Venice. The download feature for the website is currently under development and will be available soon. Thank you.

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