Monitoring and Evaluating Post-Disaster Recovery Using High- Resolution Satellite Imagery

Transcription

1 Monitoring and Evaluating Post-Disaster Recovery Using High- Resolution Satellite Imagery Daniel Brown, Keiko Saito and Torwong Chenvidyakarn Department of Architecture, Cambridge University Cambridge, UK Beverley Adams, John Bevington ImageCAT Ltd. Ashtead, UK Robin Spence, Steve Platt Cambridge Architectural Research Ltd.

2 Presentation Contents What is post-disaster recovery? Why must it be monitored? Recovery Indicators Methodology: Overview Case Study: Ban Nam Khem, Thailand Recommendations - What should be monitored? - When should imagery be acquired? - Transferability of Indicators - Tool Integration

3 Recovery Project Objectives Identify indicators for measuring, monitoring and evaluating post-disaster recovery Remote sensing-based Field survey-based + Explore the use of new technologies, including GPSbased field techniques and Satellite Imagery Analysis. Produce a standardised approach to monitoring longterm recovery. Develop a guide for aid agencies on how to best use these tools

4 Remote Sensing and Disasters Remote Sensing has been used to assist all four phases of the disaster management cycle through early warning, crisis mapping and spatial planning. Work has focussed on Disaster Response, by assisting rapid damage assessment and loss estimation after the event (often in the immediate weeks and months). Over 80 papers have been published on this topic (Saito, 2009). but still very little work on Remote Sensing as a monitoring tool.

5 What is Post-Disaster Recovery? Post-Disaster Recovery may be thought of as an attempt to bring a post-disaster situation to a level of acceptability through the rectification of damage and disruption that has been inflicted upon an urban system s built environment, people and institutions. Post-disaster Post-Recovery Long, costly, complex recovery process

6 Why must Post-Disaster Recovery be Monitored? Recovery is: a) Expensive b) Numerous Stakeholders c) Numerous Sectors Since 1984, the World Bank alone has financed US$ 26 billion in disaster activities in over 600 disaster responses. Table 1 shows major reconstruction program pledges (US$ 1 billion or more) between 1998 and Natural Disasters Post-Conflict 1998 Hurricane Mitch Iraq Bam Earthquake Sudan Aceh and Nias Tsunami 7.7* 2006 Lebanon Sri Lanka Tsunami Kashmir Earthquake Haiti Earthquake 9.9 Source: Dreamis (2009). * Pledges following the 2004 Indian Ocean Tsunami eventually reached US$ 14 billion

7 Why must Post-Disaster Recovery be Monitored? Recovery is: a) Expensive b) Numerous Stakeholders c) Numerous Sectors Executing Agencies UN Humanitarian Partners e.g. UNICEF, UNHCR Non-UN Humanitarian Partners e.g. Red Cross, Oxfam National Government of Affected Country Local and National NGOs Companies: e.g. BP after the oil spill Operationally, what should be done next? M&E improves coordination, situationalunderstanding and decision-making and contributes towards a better understanding of good-and-bad practice. Donors International Financial Institutions: e.g. World Bank International Development Departments: e.g. EU (through ECHO) National Development Departments: e.g. USAID and DFiD Public Donations: e.g. through DEC and National Governments Strategically, how much have we achieved so far? Strategically, the techniques allow users to monitor recovery in a comprehensive and independent manner that promotes transparency and accountability.

8 Why must Post-Disaster Recovery be Monitored? Recovery is: a) Expensive b) Numerous Stakeholders c) Numerous Sectors Executing Agencies and Donors Inter-Agency Standing Committee CLUSTERS Sector or Area of Activity Agriculture Camp Management Early Recovery Education Emergency Shelter Emergency Telecommunications Health Logistics Nutrition Protection Water, Sanitation and Hygiene Global Cluster Lead FAO UNHCR / IOM UNDP UNICEF / Save The Children UNHCR / IFRC OCHA / WFP WHO WFP UNICEF UNHCR / OHCHR / UNICEF UNICEF Cross-Cutting Issues Age Environment Gender HIV/AIDS HelpAge International UNEP UNFPA / WHO UNAIDS

9 Why must Post-Disaster Recovery be Monitored? Recovery is: a) Expensive b) Numerous Stakeholders c) Numerous Sectors Despite the complexity, cost and importance of post-disaster recovery a monitoring framework that is systematic and independent still does not exist: Shelter Meeting (2006): Lack of a standard, independent and replicable approach to measure, monitor and evaluate the relief and recovery processes TRIAMS (2007): There is a need to find suitable methodologies and modalities for the TRIAMS core indicators to be collected and analysed in a systematic and periodic way by local actors in the different sectors of the recovery. Existing techniques are commonly subjective and time-consuming The availability of VHR Satellite Imagery presents the opportunity to enhance and support existing data collection tools, such as ground surveys and social-audit methods.

10 Phase 1: Creation of the Indicator List and Data Collection A preliminary list of robust, versatile indicators were compiled based on: a) Current Frameworks b) User Needs Survey c) Field Collection The Sphere Guidelines ECLAC Handbook Post-Disaster Needs Assessment TRIAMS Millennium Development Goals

11 Phase 1: Creation of the Indicator List and Data Collection A preliminary list of robust, versatile indicators were compiled based on: a) Current Frameworks b) User Needs Survey c) Field Collection Replies received from the following organisations: DIFD EuropeAid European Commission FAO ILO International Recovery Platform OCHA UNDG UNDP UNEP UNFPA University of Memphis UNOSAT WFP World Bank Head Office World Bank Indonesia Josef Leitmann - World Bank Indonesia, Disaster Management Coordinator We lack good information about damage to housing and infrastructure; impact on access; land cover change. It would be very useful to have these indicators of recovery mapped as overlays onto satellite imagery Dan Ayliffe - DIFD, Response Officer It would be useful to map population movements; rehabilitation of homes; rehabilitation of infrastructure including roads, camps and medical centres; uptake of agricultural activities and other livelihoods. Top 5 Indicators: 1. Livelihoods 2. Housing Reconstruction 3. Water quality 4. Crops/livestock/fisheries = 5. Road Reconstruction =5. Floodwater removal Users want a comprehensive approach encompassing all aspects of recovery. All indicators were ranked very highly.

12 Phase 1: Creation of the Indicator List and Data Collection A preliminary list of robust, versatile indicators were compiled based on: a) Current Frameworks b) User Needs Survey c) Field Collection Objective 1: Obtain feedback on candidate indicators and proposed recovery timeline. Objective 2: Exchange knowledge and experience about post-tsunami recovery with key organizations and the local community to create a narrative of recovery and to verify the remote sensing analysis. Roundtable discussion Focus group meetings Household survey

13 Socio-economic Indicators Physical Indicators The Recovery Project Recovery Indicator List Sector Performance Indicator 1. Accessibility Analysis 2. Reconstruction of bridges and Transport transport facilities 3. Presence of vehicles 4. Removal and construction of buildings 5. Change in urban land use and Buildings / Shelter morphology 6. Quality of dwelling reconstruction Transitional 7. Temporary dwellings and shelters Shelters and IDPs 8. Location of population 11. Change in Land Cover and public open Environment space 9. Administration, education, healthcare and religious facilities Services 10. Power, Water and Sanitation (WATSAN ) Facilities Livelihoods 12. Recovery of livelihoods Table has large scope, encompassing many different aspects of Recovery Includes physical, environmental, social and economic factors, which combine to give a true picture of recovery...whilst containing a manageable number of indicators, so the list remains practical and usable. List refined using results of user-needs survey and comments from NGOs, Governments and Affected Communities.

14 Multi-Sensor Database of Very-High Resolution Imagery Indicators applied to two case studies (and Yingxiu, China) Muzaffarabad 2004 Indian Ocean Tsunami 2005 Kashmir Earthquake Date Timeline Sensor 1 13 August months Quickbird 2 22 October days Quickbird 3 13 June months Quickbird 4 20 September months WorldView June months Quickbird Ban Nam Khem Date Timeline Sensor 1 24 June months Ikonos 2 30 December days Orbview 3 02 January days Quickbird 4 21 April months Ikonos 5 14 July months Quickbird 6 28 February year Quickbird 7 21 November years Ikonos 8 08 February years Ikonos 9 05 February years Quickbird

15 Analysis Methodology Three Stages: 1) Pre-Processing 2) Mapping & Database Creation 3) Data Analysis 4) Product Creation Registration and Pan-sharpening Pansharp (PCI Geomatica) Gram-Schmidt (ENVI) Principal Component (ERDAS Imagine)

16 Analysis Methodology Three Stages: 1) Pre-Processing 2) Mapping & Database Creation 3) Data Analysis 4) Product Creation Mapping Features using both semiautomatic and manual techniques: Mapping Technique Manual Delineation Supervised Classification Object Based Image Analysis Features Buildings, Roads, Bridges, Boats, Tents, Water Towers etc. Land Cover Extraction, Green Spaces Transitional Shelters, Planned Camps, Shrimp Ponds Features Integrated into a Multi- Temporal Geodatabase with standardised Schema

17 Analysis Methodology Three Stages: 1) Pre-Processing 2) Mapping & Database Creation 3) Data Analysis 4) Product Creation Query the geodatabase using various analysis techniques: Technique Features Output Change Detection Speed of Recovery, Location of Change, Absence / Presence How fast were houses built at Site A? When was the school built? Spatial Analysis Abundance, Location How many houses were built? Are buildings a sufficient distance from potential hazards? Buffer Analysis Proximity, Changing Context How many buildings have been built within 200 m of the coast? Landscape Metrics Network Analysis Disaggregation Feature size, density and distribution. Connectivity, Travelling Distance All data may be disaggregated by geographic boundary, executing agency etc. Are the new houses the same size as those that existed before the disaster? How far are households from sources of livelihood? Are sufficient schools available? How many schools were built in each Province? Has Executing Agency A completed 2,000 houses in Region B?

18 June 2002 (1.5 years before) Ban Nam Khem

19 January 2005 (+ 1 week) Mangroves Homes and Businesses School Roads Temples Approximate Inundation Line

20 February 2006 (+ 1 Year) New Governmentprovided Housing Ban Nam Khem Camp Pruteow Camp

21 February 2008 (+ 3 Years) New Agencyprovided Housing New Shrimp Farms Restored Land Cover

22 Ban Nam Khem Status: a) Transport b) Buildings c) Environment d) Planned Camps - Pre-Disaster Road Length: 46 km. - The tsunami destroyed 29.8 km of road. - Emergency vehicles had access to region within several days - Major Routes cleared of debris and rubble within 4 months - 21 km of restoration completed in one year - The total length of asphalt road in February 2009 was 8.01 km longer than it was before the disaster. - Network Analysis: households relocated up to 10 Km from Ban Nam Khem, significant social and economic impact on fishing community.

23 Ban Nam Khem Status: a) Transport b) Buildings c) Environment d) Planned Camps buildings were washed away by the tsunami - A further 58 buildings were demolished during relief phase buildings were built in the first five months, including new school buildings - Numerous Agencies operating in BNK: -Military construction complete within 1.5 years; NGO construction complete between 2 to 4 years - There was disparity in the size/quality of housing provided by different agencies leading to discontent among many residents. - Military-built buildings smaller and more densely-built than the buildings that existed before the tsunami.

24 Ban Nam Khem Status: a) Transport b) Buildings c) Environment d) Planned Camps -Approximately 4.2 Km² of vegetation was removed by the tsunami. -a further 0.7 Km² removed during the first 4 months of recovery due to clearance and construction work. - Sparse vegetation was particularly badly affected but was seen to recover significantly in the first year. - Land Degradation was seen around new construction and planned camps, but later recovered. Where possible construction took place on existing urban sites. - Crop cycles appeared unaffected by the Tsunami.

25 Ban Nam Khem Status: a) Transport b) Buildings c) Environment d) Planned Camps -4 camps in Phang Nga hosting 3,200 people (correct within 10%) - Three camps dismantled within three years - One camp still hosting households after four years -Minimum Covered Space standards adhered to - EIA: Dismantled buildings with vegetation returning quickly

26 % change Total no. of structures Recovery Indicator Outputs Sector Performance Indicator 1. TRANSPORT Indicators for 1. Measuring, Accessibility Analysis Monitoring and Evaluating Post-Disaster Recovery Daniel Brown, Centre 2. Reconstruction for Risk in the of Built Environment (CURBE), Cambridge University, UK Transport bridges and transport facilities Buildings / Shelter Transitional Shelters and IDPs Services Environment Livelihoods 3. Presence of vehicles 4. Removal and construction of buildings 5. Change in urban land use and morphology 6. Quality of dwelling reconstruction 7. Temporary dwellings and shelters 8. Location of population 9. Administration, education, healthcare and religious facilities 10. Power, Water and Sanitation (WATSAN ) 11. Change in Land Cover and public open space 12. Recovery of livelihoods Figure 1: The length of functioning road was measured, by road type. 8. POPULATION Figure 3: The population living in transitional shelters was estimated throughout the recovery process and compared to Government Statistics. 11. ENVIRONMENT The Recovery Project 4. SHELTER Evaluating the Construction and Removal of Buildings in Ban Nam Khem 100 RSPSoc Cork, Ireland Figure 2: Jun-02 Total number Jan-05 May-05 of buildings Feb-06 in Nov-06 Ban Nam Feb-08Khem Feb-09 throughout the recovery period Buildings removed New buildings Total no. structures SERVICES (EDUCATION) Figure 4: The removal and construction of permanent and temporary buildings was monitored at Ban Nam Khem School. 12. LIVELIHOOD Figure 5: Multi-temporal supervised classification generated data on land cover changes Figure 6: The productivity of shrimp grow-out ponds was analysed throughout the recovery period.

27 Recommendations Four Parts: 1) What Indicators? 2) When? 3) Transferability 4) Tool Integration Produced a manageable number of indicators encompassing a large scope. Indicators used in this research are based on humanitarian frameworks, user needs survey and round table meetings with users and affected communities. Knowing which indicator(s) to employ is ultimately dependent on: The processes/projects occurring on the ground Requirements of users Spectral, spatial and temporal limitations An understanding of these issues is crucial to acquiring suitable data and avoiding costly mistakes. Spatial: At least 1.0 m, preferably 0.6 m or higher. Spectral: Vegetation require NIR band. Better spectral resolution likely to improve semiautomatic extraction e.g. Worldview-2 s 8-bands. Temporal: The satellite sensors listed below all have average revisit times under 3 days. For example, Worldview 1 and 2 have a revisit time of 1.7 and 1.1 days respectively at 1.0m GSD Appropriate Sensors: Ikonos, Quickbird, Worldview-1, Worldview-2, and Geoeye-1

28 Recommendations Four Parts: 1) What Indicators? 2) When? 3) Transferability 4) Tool Integration To avoid costly mistakes it is important to know when to acquire imagery. Images should be acquired when impacts are likely to be visible and measurable Due to the dynamic nature of recovery, the timing and duration of events and processes is likely to vary, so constant communication with ground workers is crucial. Many aspects of the recovery process are, to a certain extent, predictable and are ultimately determined by the funding strategies and timeframes of donors and affected governments. E.g. World Bank s 3-year Emergency Funding Loan. All of the crucial disaster response activities with infrastructure activities took years on average (IEG, 2006).

29 Recommendations Four Parts: 1) What Indicators? 2) When? 3) Transferability 4) Tool Integration Indicators designed to be versatile and applicable to multiple hazards and to be non-country specific. The techniques offer a standardised and quantitative methodology that allows the disparity in the speed and quality of recovery to be compared across an affected region and between different disaster events. Comparing different recovery trends allow us to better understand good and bad practice Analyst must be aware of cultural differences The Recovery Indicators provide a standardised method of quantifying the process of reconstruction, which allows the speed and scale of recovery after different events to be compared to each other.

30 Recommendations Four Parts: 1) What Indicators? 2) When? 3) Transferability 4) Tool Integration - Results from tools triangulated to verify the accuracy and reliability of results, identify data gaps - Cost-effectiveness analysis of tools (Time/Money, Detail, Accuracy, Skill Requirement) - VHR satellite imagery shown to be costeffectiveness at town/city scale - Identified tools strengths and weaknesses and recommend how tools may be integrated and when Remote Sensing Triangulation Ground Observations Social Audit GPS Camera, Views Techniques Focus Group Meetings, Key Informant Interviews, Household Survey)

31 Raw Satellite Images GIS Analysis Spatial Analysis and Change Detection Satellite maps direct survey teams to Areas of Interest and may be used to select suitable survey samples. Ground Survey Geo-tagged notes, videos and photographs may be used to note verify Remote Sensing analysis e.g. building use and construction quality and for detailed grounds observations. The maps are used to invoke discussion and inform the survey design and questions. Social Audit Methods Household surveys, Key Informant Surveys and Focus Group Meetings may all be used to measure progress, identify problems and derive an overall perception of recovery. Output: Geo-tagged photographs & maps from executing agencies. Ground Surveys populate maps with data on building use and construction quality. Maps Spatial- Temporal Recovery Geo-database Graphs Output: Annotated Maps The notes are all given a location and where appropriate attached to the relevant map feature. Tables

32 Conclusion VHR Satellite Images can effectively monitor and show disparity in the speed and quality of post-disaster recovery. Remote Sensing has been shown to be cost-effective at town/city scale, but more work is required to allow the techniques to be applied across larger areas e.g. sampling, medium resolution data and/or more automated techniques. Remote sensing can also be used to: -Plan Construction - Plan Field Work (logistics, including accessibility) - Create samples - host data from other tools, assisting triangulation and acting as a central data management system. -Visualisation tool -Map production

33 Recovery Project Report To be published: mid-2010 Recovery Project 4-pager Published: May 2010 Papers Technical (Int J Rem Sens) and Non-Technical (Disasters). Remote Sensing and Disaster Workshops 2008, 2009 and 2010.

34 Many Thanks

35 The Recovery Project