Efforts for Emergency Observation Mapping in Manila Observatory

Efforts for Emergency Observation Mapping in Manila Observatory: Development of a Typhoon Impact Estimation System (TIES) focusing on Economic Flood Loss of Urban Poor Communities in Metro Manila

UN-SPIDER International Conference on Space-based Technologies for Disaster Risk Reduction – “Enhancing Disaster Preparedness for Effective Emergency Response” Session 4: Demonstrating Advances in Earth Observation to Build Back Better September 25, 2018

Ma. Flordeliza P. Del Castillo Manila Observatory EMERGENCY OBSERVATION MAPPING IN MANILA OBSERVATORY • Typhoon Reports • Sentinel Asia Data Analysis Node (2011-present) • Flood loss estimation for urban poor households in Metro Manila (2016-present)

1. Regional Climate Systems (RCS) – Hazard analysis (Rainfall and typhoon forecast) 2. Instrumentation and Efforts before typhoon arrives Technology Development – Automated Weather Stations 3. Geomatics for Environment and Development – Mapping and integration of Hazard, Exposure and Vulnerability layers Observing from space and also from the ground.

Efforts during typhoon event Now, incorporating exposure and vulnerability variables Efforts after a typhoon event

Data Analysis Node (Post- Disaster Event)

Image Source: Secretariat of Sentinel Asia Japan Aerospace Exploration Agency, Sentinel Asia Annual Report 2016 MO Emergency Observation (EO) and Mapping Protocol (15 October 2018)

Step 1: Step 2: Step 3: Establish the Apply for EMERGENCY Elevate status to LOCATION/COVERAGE of OBSERVATION to International Disaster EOR Sentinel Asia (SA) Charter (IDC) by ADRC

Step 6: Step 5: Step 4: Upload maps in MO, SA MAP Download images & IDC websites PRODUCTION Emergency Observation Mapping Work

• December 2011 – T.S. Washi “Sendong” • August 2012 – Southwest Monsoon Flood “Habagat” • ” Emergency Observation Mapping Work

• December 2011 – T.S. Washi “Sendong” • August 2012 – Southwest Monsoon Flood “Habagat” • December 2012 – Bopha “Pablo” • August 2013 – Southwest Monsoon Flood and T.S. Trami “Maring” • October 2015 – Typhoon Koppu “Lando” • December 2015 – Typhoon Melor “Nona” • October 2016 – Typhoon Haima “Lawin” • September 2018 – Typhoon Mangkhut “Ompong” Estimated Affected Population (Typhoon Koppu) Estimation of Economic Losses due to Flood among Urban Poor Households • Background • Pan-Asia Risk Reduction Fellowship Program (START Organization, • “Establishing a Geodatabase Towards Typhoon Impact Estimation System (TIES) for the Philippines” (Del Castillo, 2017) • “An Attempt to Evaluate Economic and Non-Economic Losses and Damages due to Flooding among the Urban Poor Households in Metro Manila” (See, 2017) • Context • Riverine urban poor communities that are frequently experienced flooding (Ondoy and Habagat flood events) • Household losses including non-economic losses at the local level were not usually reported. Estimation of Economic Losses due to Flood among Urban Poor Households • Objective • Estimate losses and damages to flooding of urban poor households in Santolan, Pasig, Metro Manila, Philippines • Estimate the economic losses • Estimate the non-economic losses • Rationale • Reduce exposure, damages and losses of urban poor households to flooding

Image Source: Global Water Partnership https://www.flickr.com/photos/globalwaterpartnership/4682586822 Data and Methods

• Data • Household survey (See, 2016) • Flood hazard maps (100 yr- flood) from UP DREAM Program flood model component • 2011 LiDAR images and orthophoto (1m and 0.25 m resolution) Lidar orthophoto, DEM Data and Methods and DSM

• Methods 1. Extracted urban poor households Extraction of urban poor Flood Hazard Map Data from LiDAR orthophoto, DEM and households (RS-GIS) Collection DSM via decision tree and segmentation 2. Intersected the urban poor households with flood extent 3. Computed for economic losses using the household survey Intersect 1. Household Survey (300 respondents sampled through systematic sampling with a random start) 2. Focused Group Discussion Compute for Economic Losses 3. Multivariate analysis economic Household Survey losses Losses and Damages Survey

• Flood Impact on Household Income = 7,050 PhP • Expenses for House Repair = 4,200 PhP • Household Assets and Amoung of damage incurred = 6,000 PhP • Calculated economic loss = 17,250 PhP NDVI equation: B1 EQ 2 NDSM equation: B2 EQ 2 NDSM equation: B3 LE 9 Figure 4: Segmentation of masked Orthophoto Image of Informal Settlements (left) versus Formal Settlements (right) Economic loss per household (PhP) 17,250 Total area of flood-prone urban poor settlements (square meters) 73,697.97 Average House Floor Area (square meters) 24.00 Number of urban poor settlements prone to 5-yr flood 3071 Total economic losses (PhP) 53.0 M Further Work

• Validation of Morphological Slums Location • Updating of the urban poor households and losses data and map • Communicating the results Acknowledgments • Dr. May Celine T.M. Vicente, Head Geomatics for Environment and Development Laboratory, Manila Observatory • Dr. Gemma T. Narisma, Executive Director of Manila Observatory • Mrs. Antonia Yulo-Loyzaga, Former Executive Director of Manila Observatory • Dr. Faye Abigail Cruz, Head of Regional Climate Systems, Manila Observatory • Justin Charles G. See (La Trobe University) – Collaborator and Co-PARR Fellow • Genevieve Lorenzo, RCS Research Staff – Authors of Typhoon Reports • Raul S. Dayawon, Jerome A. Azul, Ma. Angelica O. Dela Paz, John Edward Perez – colleagues in GED • Prof. Weisen Li (National Science and Technology Center for Disaster Risk Reduction), PARR Facilitator • Prof. Hsin-Chi Li and Prof. WenRey Su (National Science and Technology Center for Disaster Risk Reduction), Mentors at NCDR • Sentinel Asia, International Disaster Charter and Data Providers – Satellite Images • START (Global Change System for Analysis, Research, and Training) Acknowledgments • Data Contributors: • UP DREAM Project. 2017. Flood Hazard Maps. • NAMRIA. 2011. LiDAR DEM, DSM, and orthophotos of Metro Manila. • JAXA. Real-time rainfall measurements. • JAXA ALOS, PALSAR images. • CNES. Spot images. • TERRA SAR X and TANDEM X. 2013. German Aerospace Center. • ASTRIUM • GeoEye • TRMM. Accumulated Rainfall. • NDRRMC. Situation Reports. • SRTM DEM Thank you for your attention.