Efforts for Emergency Observation Mapping in Manila Observatory

Total Page:16

File Type:pdf, Size:1020Kb

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” • December 2015 – Typhoon Melor “Nona 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..
Recommended publications
  • Bishop Jane Alexander and the Rev. Patrick Stephens
    Learning through Lent A PWRDF resource by Bishop Jane Alexander and the Rev. Patrick Stephens 2021 Table of Contents Introduction, Lent 2019 .......................................................................................................3 Easter Garden Activity Plan ................................................................................................4 Creation is our story Ash Wednesday to Saturday: February 17–Fevbruary 20 ..........................................6 Creation: A relationship of respect e First Week of Lent: February 22_February 27 ....................................................14 Who we are and how we are called e Second Week of Lent: March 1–March 6 ............................................................26 Water and re: life in the balance e ird Week of Lent: March 8–March 13 .............................................................42 One world, one faith, many nations e Fourth Week of Lent: March 15–March 20 .........................................................54 Incarnation and redemption: a natural connection e Fih Week of Lent: March 22–March 27 ............................................................66 A personal commitment to creation discipleship Holy Week to Easter: March 29–April 4 .....................................................................78 How to read this resource ON PAPER ON A SCREEN IN AN EMAIL Download and print the PWRDF story links are Subscribe at PDF. Links to PWRDF also embedded within the pwrdf.org/Lent2021 to stories are included for text of the reection and receive an email every your reference. will take you directly to morning, Story links are our website. embedded in the text. Introduction Welcome to PWRDF’s 2021 Lent resource, “Creation care: climate action,” prepared as part of our three-year education focus of the same name. While COVID-19 has swept climate change concerns from the headlines over the past year, PWRDF partners around the world and here in Canada, continue to address the impacts of a changing climate on the communities they serve.
    [Show full text]
  • OCHA PHL TY Sarika Haima 17Oct2016
    Philippines: Typhoons Sarika (Karen) and Haima (Lawin) (17 October 2016) Typhoon Sarika Japan Typhoon Haima Typhoon category Typhoon Sarika (Karen) made landfall in (Saffir-Simpson Scale) Typhoon Haima (Lawin) has intensified 22 October 2016 Baler, Aurora province, at 2:30 a.m. on Category 1: 119-153 km/hr from a severe tropical storm. It was last 16 October. It slightly weakend while spotted 1,265 km east of the Visayas with China Category 3: 178-208 km/hr crossing Central Luzon but slightly maximum sustained winds of up to 150 intensified as it moves away from the Category 4: 209-251 km/hr km/h and gusts of up to 185 km/h. It is Philippines. As of 6am 17 October 2016, Taiwan moving west northwest at 22 km/h and is Typhoon Sarika is out of the Philippines Category 5: > 252 km/hr expected to enter PAR by the afternoon Area of Responsibility (PAR) and all PAGASA category of 17 October. The typhoon is projected Tropical Cyclone Warning Signals Hong Kong Typhoon Karen (SARIKA) to intensify into a category 5 as it moves Macao (TCWS) have been lifted. Tropical depression closer to northern Philippines. 21 October 2016 Lawin (HAIMA) Tropical storm EFFECTS Forecasted to make landfall Severe tropical storm PROFILE Regions I, II, III, IV-A, V and CAR in Northern Cagayan Typhoon within the 100 km radius of typhoon track affected areas 20 October 2016 P.A.R. 4 47 Actual typhoon track provinces cities/municipalities 75,000 Typhoon Haima people affected Forecasted track 17 October 2016 1.9 Million 406,000 19 October 2016 people households 70,800 LUZON people displaced 18 October 2016 Lawin (HAIMA) Forecasted to enter P.A.R.
    [Show full text]
  • 6 2. Annual Summaries of the Climate System in 2009 2.1 Climate In
    2. Annual summaries of the climate system in above normal in Okinawa/Amami because hot and 2009 sunny weather was dominant under the subtropical high in July and August. 2.1 Climate in Japan (d) Autumn (September – November 2009, Fig. 2.1.1 Average surface temperature, precipitation 2.1.4d) amounts and sunshine durations Seasonal mean temperatures were near normal in The annual anomaly of the average surface northern and Eastern Japan, although temperatures temperature over Japan (averaged over 17 observatories swung widely. In Okinawa/Amami, seasonal mean confirmed as being relatively unaffected by temperatures were significantly above normal due to urbanization) in 2009 was 0.56°C above normal (based the hot weather in the first half of autumn. Monthly on the 1971 – 2000 average), and was the seventh precipitation amounts were significantly below normal highest since 1898. On a longer time scale, average nationwide in September due to dominant anticyclones. surface temperatures have been rising at a rate of about In contrast, in November, they were significantly 1.13°C per century since 1898 (Fig. 2.1.1). above normal in Western Japan under the influence of the frequent passage of cyclones and fronts around 2.1.2 Seasonal features Japan. In October, Typhoon Melor (0918) made (a) Winter (December 2008 – February 2009, Fig. landfall on mainland Japan, bringing heavy rainfall and 2.1.4a) strong winds. Since the winter monsoon was much weaker than (e) December 2009 usual, seasonal mean temperatures were above normal In the first half of December, temperatures were nationwide. In particular, they were significantly high above normal nationwide, and heavy precipitation was in Northern Japan, Eastern Japan and Okinawa/Amami.
    [Show full text]
  • Global Catastrophe Review – 2015
    GC BRIEFING An Update from GC Analytics© March 2016 GLOBAL CATASTROPHE REVIEW – 2015 The year 2015 was a quiet one in terms of global significant insured losses, which totaled around USD 30.5 billion. Insured losses were below the 10-year and 5-year moving averages of around USD 49.7 billion and USD 62.6 billion, respectively (see Figures 1 and 2). Last year marked the lowest total insured catastrophe losses since 2009 and well below the USD 126 billion seen in 2011. 1 The most impactful event of 2015 was the Port of Tianjin, China explosions in August, rendering estimated insured losses between USD 1.6 and USD 3.3 billion, according to the Guy Carpenter report following the event, with a December estimate from Swiss Re of at least USD 2 billion. The series of winter storms and record cold of the eastern United States resulted in an estimated USD 2.1 billion of insured losses, whereas in Europe, storms Desmond, Eva and Frank in December 2015 are expected to render losses exceeding USD 1.6 billion. Other impactful events were the damaging wildfires in the western United States, severe flood events in the Southern Plains and Carolinas and Typhoon Goni affecting Japan, the Philippines and the Korea Peninsula, all with estimated insured losses exceeding USD 1 billion. The year 2015 marked one of the strongest El Niño periods on record, characterized by warm waters in the east Pacific tropics. This was associated with record-setting tropical cyclone activity in the North Pacific basin, but relative quiet in the North Atlantic.
    [Show full text]
  • Appendix 8: Damages Caused by Natural Disasters
    Building Disaster and Climate Resilient Cities in ASEAN Draft Finnal Report APPENDIX 8: DAMAGES CAUSED BY NATURAL DISASTERS A8.1 Flood & Typhoon Table A8.1.1 Record of Flood & Typhoon (Cambodia) Place Date Damage Cambodia Flood Aug 1999 The flash floods, triggered by torrential rains during the first week of August, caused significant damage in the provinces of Sihanoukville, Koh Kong and Kam Pot. As of 10 August, four people were killed, some 8,000 people were left homeless, and 200 meters of railroads were washed away. More than 12,000 hectares of rice paddies were flooded in Kam Pot province alone. Floods Nov 1999 Continued torrential rains during October and early November caused flash floods and affected five southern provinces: Takeo, Kandal, Kampong Speu, Phnom Penh Municipality and Pursat. The report indicates that the floods affected 21,334 families and around 9,900 ha of rice field. IFRC's situation report dated 9 November stated that 3,561 houses are damaged/destroyed. So far, there has been no report of casualties. Flood Aug 2000 The second floods has caused serious damages on provinces in the North, the East and the South, especially in Takeo Province. Three provinces along Mekong River (Stung Treng, Kratie and Kompong Cham) and Municipality of Phnom Penh have declared the state of emergency. 121,000 families have been affected, more than 170 people were killed, and some $10 million in rice crops has been destroyed. Immediate needs include food, shelter, and the repair or replacement of homes, household items, and sanitation facilities as water levels in the Delta continue to fall.
    [Show full text]
  • Typhoon Haima Haima
    EmergencyEmergency Plan Appeal Final Final Report Report PhilippinesPhilippines:: Typhoon Typhoon Haima Haima Emergency Appeal n° MDRPH022 Glide n° TC-2016-000110-PHL Date of Issue: 31 October 2017 Date of disaster: 19 October 2016 Operation start date: 19 October 2016 Operation end date: 31 July 2017 Host National Society: Philippine Red Cross Operation budget: CHF 1,662,701 Number of people affected: 2.4 million Number of people assisted: 31,100 N° of National Societies involved in the operation: The American Red Cross, British Red Cross, Canadian Red Cross Society, Finnish Red Cross, Japanese Red Cross Society, Norwegian Red Cross, Red Cross of Monaco, Swedish Red Cross and The Netherlands Red Cross have contributed towards the Emergency Appeal launched on behalf of Philippine Red Cross. The Swiss Red Cross supported PRC on a bilateral basis. N° of other partner organizations involved in the operation: Philippine Red Cross participated in the National Disaster Risk Reduction and Management Council (NDRRMC) meetings and coordinates with the Department of Social Welfare and Development (DSWD), and Department of Health, and the NDRRMC at provincial, municipal and barangay levels. Other agencies present were: Action Against Hunger and Relief International, through the support of UNICEF and Care Philippines. Appeal history: 17 October 2016 - Haima develops in the Pacific as a Severe Tropical Storm. 18 October - Government enforces pre-emptive evacuations in areas likely to be severely affected by the typhoon. 19 October - Tropical Cyclone Warning Signal (TCWS) number 5 – the highest – is declared over Cagayan province. - Haima makes landfall 23H00 (local time) over Peñablanca, Cagayan (around 500 km northeast of Manila) with winds of 225 kph and gustiness of 315 kph Haima brings strong winds and heavy rains; wind damage and flooding in the affected areas.
    [Show full text]
  • State of the Climate in 2015
    STATE OF THE CLIMATE IN 2015 Special Supplement to the Bulletin of the American Meteorological Society Vol. 97, No. 8, August 2016 severed during the storm, and four days after the Islands, on 28 June. Over the next couple of days, the storm nearly 60% of the nation’s inhabited islands system moved westward into the Australian region, remained cut off from the outside world. According where it was named a TC. Raquel then moved east- to UNESCO, 268 million U.S. dollars was required for ward into the South Pacific basin, where it weakened total recovery and rehabilitation of Vanuatu. into a tropical depression. On 4 July, the system The storm’s winds gradually slowed afterwards as moved south-westward and impacted the Solomon Pam tracked west of the Tafea Islands. However, the Islands with high wind gusts and heavy rain. Fiji Meteorological Service indicated that the TC’s pressure dropped farther to 896 hPa on 14 March. f. Tropical cyclone heat potential—G. J. Goni, J. A. Knaff, As Pam travelled farther south, the storm’s eye faded and I.-I. Lin away and Pam’s low-level circulation became dis- This section summarizes the previously described placed from its associated thunderstorms, indicating tropical cyclone (TC) basins from the standpoint of a rapid weakening phase. Later on 15 March, Pam en- tropical cyclone heat potential (TCHP) by focusing on tered a phase of extratropical transition and affected vertically integrated upper ocean temperature condi- northeast New Zealand and the Chatham Islands tions during the season for each basin with respect to with high winds, heavy rain, and rough seas.
    [Show full text]
  • Flood Hazard Mapping in an Urban Area Using Combined Hydrologic-Hydraulic Models and Geospatial Technologies
    Global J. Environ. Sci. Manage. 5(2): 139-154, Spring 2019 Global Journal of Environmental Science and Management (GJESM) Homepage: https://www.gjesm.net/ ORIGINAL RESEARCH PAPER Flood hazard mapping in an urban area using combined hydrologic-hydraulic models and geospatial technologies B.A.M.Talisay*, G.R. Puno, R.A.L. Amper GeoSAFER Northern Mindanao/ Cotabato Project, College of Forestry and Environmental Science, Central Mindanao University, Musuan, Maramag, Bukidnon, Philippines ARTICLE INFO ABSTRACT Flooding is one of the most occurring natural hazards every year risking the lives and Article History: Received 12 August 2018 properties of the affected communities, especially in Philippine context. To visualize Revised 12 November 2018 the extent and mitigate the impacts of flood hazard in Malingon River in Valencia Accepted 30 November 2018 City, Bukidnon, this paper presents the combination of Geographic Information System, high-resolution Digital Elevation Model, land cover, soil, observed hydro-meteorological data; and the combined Hydrologic Engineering Center- Keywords: Hydrologic Modeling System and River Analysis System models. The hydrologic Geographic information system (GIS) model determines the precipitation-runoff relationships of the watershed and the Inundation hydraulic model calculates the flood depth and flow pattern in the floodplain area. Light detection and ranging The overall performance of hydrologic model during calibration was “very good fit” Model calibration based on the criterion of Nash-Sutcliffe Coefficient of Model Efficiency, Percentage Bias and Root Mean Square Error – Observations Standard Deviation Ratio with the values of 0.87, -8.62 and 0.46, respectively. On the other hand, the performance of hydraulic model during error computation was “intermediate fit” using F measure analysis with a value of 0.56, using confusion matrix with 80.5% accuracy and the Root Mean Square Error of 0.47 meters.
    [Show full text]
  • Typhoon Haima in the Lao People's Democratic Republic
    TYPHOON HAIMA IN THE LAO PEOPLE’S DEMOCRATIC REPUBLIC Joint Damage, Losses and Needs Assessment – August, 2011 A Report prepared by the Government of the Lao PDR with support from the ADB , ADPC, FAO , GFDRR, Save the Children, UNDP, UNFPA, UNICEF, UN-HABITAT, WFP, WHO, World Bank, World Vision, and WSP Lao People's Democratic Republic Peace Independence Democracy Unity Prosperity TYPHOON HAIMA JOINT DAMAGE, LOSSES AND NEEDS ASSESSMENT (JDLNA) *** October 2011 A Report prepared by the Government of the Lao PDR With support from the ADB, ADPC, FAO, GFDRR , Save the Children, UNDP, UNFPA, UNICEF, UN- HABITAT, WFP ,WHO, World Bank, World Vision, AND WSP Vientiane, August 29, 2011 Page i Foreword On June 24-25, 2011, Typhoon Haima hit the Northern and Central parts of the Lao PDR causing heavy rain, widespread flooding and serious erosion in the provinces of Xiengkhouang, Xayaboury, Vientiane and Bolikhamxay. The typhoon caused severe damage and losses to the basic infrastructure, especially to productive areas, the irrigation system, roads and bridges, hospitals, and schools. Further, the typhoon disrupted the local people’s livelihoods, assets and properties. The poor and vulnerable groups of people are most affected by the typhoon. Without immediate recovery efforts, its consequences will gravely compromise the development efforts undertaken so far by the government, seriously set back economic dynamism, and further jeopardise the already very precarious situation in some of the provinces that were hard hit by the typhoon. A Joint Damage, Losses and Needs Assessment (JDLNA) was undertaken, with field visit to the four most affected provinces from 25th July to 5th August 2011.
    [Show full text]
  • 7 the Analysis of Storm Surge in Manila Bay, the Philippines
    INTERNATIONAL HYDROGRAPHIC REVIEW MAY 2019 THE ANALYSIS OF STORM SURGE IN MANILA BAY, THE PHILIPPINES By Commander C. S. Luma-ang Hydrography Branch, National Mapping and Resource Information Authority, (Philippines) Abstract In 2013, Typhoon Haiyan produced a storm surge over seven metres in San Pedro Bay in the Philippines that killed approximately 6,300 people. The event created significant public awareness on storm surges and exposed the lack of records and historical research in the Philippines. This study investigated the tidal height records during intense cyclone activities in 2016 and 2017 to provide accurate information about storm surge development in the largest and most populated coastal area in the country – Manila Bay. The results of this investigation indicated that there are consistencies in the characteristics of tropical cyclones that produce larger storm surges. The results also show that actual storm surge heights are generally smaller than predicted height values. Résumé En 2013, le typhon Haiyan a provoqué une onde de tempête de plus de sept mètres dans la Baie de San Pedro aux Philippines, faisant près de 6 300 victimes. Cet événement a provoqué une importante sensibilisation du public envers les ondes de tempête et a mis en évidence le manque d’archives et de recherches historiques aux Philippines. La présente étude a examiné les enregistrements des hauteurs des marées au cours d’activités cycloniques intenses en 2016 et 2017 afin de fournir des informations précises sur le développement d’ondes de tempête dans la zone côtière la plus étendue et la plus peuplée du pays, la Baie de Manille.
    [Show full text]
  • Humanitarian Civil-Military Coordination for Asia and the Pacific
    REGIONAL CONSULTATIVE GROUP HUMANITARIAN CIVIL-MILITARY COORDINATION FOR ASIA AND THE PACIFIC HUMANITARIAN CIVIL-MILITARY COORDINATION IN EMERGENCIES: TOWARDS A PREDICTABLE MODEL FOREWORD The Regional Consultative Group (RCG) on Humanitarian This revised publication was produced through Civil-Military Coordination (CMCoord) for Asia and collaboration between the ASEAN Coordinating Centre for the Pacific is a key forum for supporting and elevating Humanitarian Assistance on disaster response, the United coordination, building relationships, and sharing learning Nations Office for the Coordination of Humanitarian Affairs to enhance and strengthen emergency response. When – Regional Office for Asia and the Pacific, the Australian the RCG was formed in 2014, it was tasked with improving Civil-Military Centre and Humanitarian Advisory Group. awareness and enhancing the predictability of CMCoord Expert practitioners and researchers contributed their mechanisms, and their respective functions, during large- time to ensure the information is accurate and accessible. scale disaster response. As a result, the RCG initiated Like the initial version, the publication will be regularly the development of the first version of Humanitarian updated to reflect operational environments accurately. Civil-Military Coordination in Emergencies: Towards a Predictable Model, which focused on explaining the As the current Chair of the RCG, we recognize that effective legislation, coordination mechanisms, approach to and humanitarian CMCoord enables timely, efficient and leadership of disaster management in the five most effective response, and we appreciate every investment disaster-prone countries in Asia: Bangladesh, Nepal, and effort of the relevant individuals, governments and Indonesia, Myanmar and the Philippines. The publication organizations in the revision of this publication. We trust was launched in 2017, and soon became a key reference for that it will receive due attention and support future the CMCoord community.
    [Show full text]
  • Msc Thesis Sandra Van Lint
    MSc Thesis Sandra van Lint MSC THESIS SENSE-MAKING OF THE NETHERLANDS RED CROSS PRIORITY INDEX MODEL CASE: TYPHOON HAIYAN, PHILIPPINES MSc International Development Studies | Disaster and Conflict Studies | WUR Sandra van Lint Chair group: Disaster and conflict studies | WUR Dr. Ir. Annelies Heijmans Project manager coalition of humanitarian innovation | The Netherlands Red Cross Maarten van der Veen 30th of November 2016 1 MSc Thesis Sandra van Lint 2 MSc Thesis Sandra van Lint Wageningen University - Department of Social Sciences Disaster and Conflict Studies MSc Thesis Sense-making of the Netherlands Red Cross Priority Index Model Case: Typhoon Haiyan, Philippines November 2016 Student S.L. van Lint, BSc Registration number 920707-522-020 MSc program Master International Development Studies Specialisation Sociology – Disaster and Conflict Studies Commissioner The Netherlands Red Cross Supervisor Dr. Ir. A. Heijmans Examiner/2nd supervisor Dr. G. van der Haar Netherlands Red Cross supervisor M. van der Veen Thesis code SDC-80733 3 MSc Thesis Sandra van Lint Abstract In the aftermath of a typhoon, decision-makers struggle to find appropriate, reliable and timely information to decide upon the prioritisation of municipalities for assistance. The Netherlands Red Cross designed a model that aims to identify the high priority areas for humanitarian assistance on the basis of secondary data. This research identifies how decision-makers from humanitarian agencies and the Philippine Government ‘make sense’ of this model and its predictions in order to prioritise municipalities for humanitarian assistance. This research explores what the Priority Index Model is, what similar initiatives are, who the decision-makers are that have to prioritise and what their information needs are.
    [Show full text]