Geospatial Data Collection/Use in Disaster Response: A United States Nationwide Survey of State Agencies Michael E. Hodgson, Sarah E. Battersby, Bruce A. Davis, Shufan Liu and Leanne Sulewski
Abstract In the United States presidential disaster declarations are typically issued after major disaster events to provide assistance (in the form of monies, staff, geospatial data, etc.) to states when the disaster overwhelms the resources of the state. Geospatial support is one of the forms of assistance and a frequent item noted by Federal agencies in demonstrating their relevance. During the disaster the state is ‘in charge’ of the disaster response while the Federal government provides assistance. Are the geospatial data (including remotely sensed imagery of all types) needs met by the states (based on their experience)? What are the expectations of the states for Federal help in geospatial data? Are states embracing newer paradigms for collecting/exploiting geospatial data, such as volunteered geographic information or crowd-sourced data/information? In the winter of 2011–2012 a nationwide survey of the geospatial data, methods, and problems in all fifty United States emergency management offices (EMOs) was conducted. Responses to the key questions on geospatial data priorities, remotely sensed imagery, timeliness, expectations, staffing, and emerging technologies are presented in this article. This nationwide survey of state EMOs provides a unique view of the EMO director’s view of geospatial methods during emergency response/recovery. Keywords Disaster
Geospatial Remote sensing
M. E. Hodgson (&) S. E. Battersby S. Liu L. Sulewski Department of Geography, University of South Carolina, Columbia, USA e-mail:
[email protected] B. A. Davis Science and Technology Directorate, Department of Homeland Security, Washington DC, USA
M. Buchroithner et al. (eds.), Cartography from Pole to Pole, Lecture Notes in Geoinformation and Cartography, DOI: 10.1007/978-3-642-32618-9_29, Springer-Verlag Berlin Heidelberg 2014
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1 Introduction The hazard cycle is thought of, for a given place, as a sequence of phases— warning/preparation, the event, response, recovery, planning/mitigation, and back to the warning/preparation stage again. Geographic information systems (GIS) and remote sensing technologies have been used in hazard-related applications for some two to three decades (Jensen and Hodgson 2006). In the mapping sciences community the prevailing assumption is that the use of GIS, GPS, and remote sensing are critical components in all phases of the hazard cycle. The frequent, but misleading, assumption is the state emergency management office (EMO) has the geospatial capabilities to manage major disasters. In early 2005, 77 % of the statelevel EMOs, for instance, had at least one full-time staff that was qualified with GIS capabilities (Hodgson et al. 2010). But 23 % of the states had no GIS or remote sensing educated staff. In a disaster event whom do these states depend on for GIScience support? The Federal government’s primary coordination of geospatial support for disasters comes from the Federal Emergency Management Agency (FEMA) within the Department of Homeland Security (DHS). In response to the growing importance of geospatial technologies in the coordination of incident response and recovery operations, FEMA has created a Geospatial Information Officer to coordinate FEMA’s geospatial support to state agencies during a disaster. Prior to this new FEMA coordination position, the National Geospatial Intelligence Agency (NGA), in cooperation with other Federal agencies, created a geographic database called Homeland Security Infrastructure Program (HSIP) (Department of Homeland Security 2013). HSIP contains more than 311 layers in a confidential form (HSIP Gold), primarily for situational awareness in Federal Agencies. The public release form of HSIP Gold is referred to as HSIP Freedom. Do these DHS data meet state and local needs? What geographic data are required at the state and local levels? Where/how are these data obtained and maintained? Are these data adequate from the manager’s perspective? Remotely sensed imagery, such as from airborne or satellite sensors, is widely used by public media during disaster events, and presumably by state/local responders. For example, months after the 2005 survey (Hodgson et al. 2010) no less than six separate aerial image missions were conducted for the impact area of Hurricane Katrina. One mission collected imagery over the entire Mississippi coast within the first day after Hurricane Katrina while the other aerial missions required from 7 to 10 days for image collection. The most utilized Federal response to the recent hurricane Sandy in the northeastern United States included some satellite image collections but also over 158,000 oblique images taken from low-altitude aircraft. Are the needs of the disaster managers met with these image collections? Was the imagery collected and exploited in a timely manner? When is remotely sensed imagery collection too late for disaster response/recovery? The state-EMO directors surveyed in 2005 indicated they need information on most anthropogenic related phenomena (e.g. buildings, lifelines) within 3 days of the disaster event
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(Hodgson et al. 2010). Could imagery collected a week after the disaster event (as was many collections after Katrina) be useful? In 2005, the use of GIS was considered ‘‘very important’’ to 88 % of the states while only 40 % said the same for remote sensing (Hodgson et al. 2010). When asked why states do not rely on remote sensing imagery more, the dominant answers were cost and collection time by over 60 % of the states. The only nationwide (United States) survey of state agencies on the use of GIS, remote sensing, and alternative spatial technologies or spatial data needs of statelevel emergency management agency’s was conducted in the Spring of 2005 (Hodgson et al. 2010). Assessments for GIScience approaches in a specific hazard event have occasionally been conducted (NOAA 2001; Huyck and Adams 2002; Prechtel 2005; Parrish et al. 2007; DeCapua 2007) but they only address the one state that ‘‘hosted’’ the single event. Other surveys target samples of county managers on a specific topic, such as the National incident Management System (Jensen 2011). Since 2005, substantial change in the availability of technology (e.g., upgrades to GIS and remote sensing software, introduction of the Google Map API, volunteered geographic information, and use of crowd-sourced, etc.) has been made and, presumably, may have altered the emergency response mapping needs of state agencies. Other surveys have been conducted on related aspects of the disaster response phase, such as the incident Command System (ICS) and the National Incident Management System (NIMS) (Jensen and Yoon 2011). This research reports on the geospatial data use in state-level EMOs, derived from a nationwide survey. This survey provides independent (i.e. not a survey by a Federal agency) information on the state of GIScience use, particularly remote sensing, in the state-level emergency response centers within the United States. Most importantly, the perceived impediments to the use of remote sensing, the quality of geospatial data layers, the spatial/temporal requirements for obtaining these data after the event, and the adoption of emerging technologies were probed. The goal of this research was to identify the geospatial data needs, methods, and administrative process used by the state-level emergency management offices during a major disaster. While the full survey contained over 62 questions (45 primary questions with 17 sub-questions) this research focuses primarily on those survey questions that assist in the understanding of remote sensing and emerging technology use (or lack of) during disaster response. These questions focused on the emergency response/recovery phases are: • What are the priority baseline (collected prior to a disaster) and disaster impact data layers needed and where do the states obtain such data? • Are the states aware of and use the Federal supplied data streams, such as HSIP? • When is remotely sensed data too late to be useful? • What is the state of GIS/Remote sensing staff? Has this changed since 2005? • Are states adopting new technologies or approaches in data collection (e.g. crowd-sourcing, VGI)?
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Our survey population was the directors of the emergency management office within each state. We were interested in the perception/cognition of past, current, and future use of geospatial technology by those individuals who lead emergency response efforts within their governmental entity. We did not want to assemble multiple responses within each governmental entity and interpret for a nationwide representation (the logistics and interpretation problems of such an effort are demonstrable). We used the directors of each state office, or where they chose to designate other staff (e.g. GIS directors) to complete the survey, as the best indicators of geospatial use. Clearly, the experience level of emergency operations directors may vary based on their personal tenure at such positions, their interaction with other governmental entities, and their experience with previous natural or technological disasters. The frequency and type (e.g. earthquake, flood, and hurricane) of natural disasters varies across the United States (Fig. 1). As noted later in this article, 96 % of the states indicated they had experienced a presidential disaster declaration (PDD) in the last 5 years.
Fig. 1
Frequency of presidential disaster declarations by county since December 1964
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2 Methodology 2.1 Survey Method The survey of states in the United States was by invitation-only. We identified the single leader of the emergency management office in each state and allowed that individual to respond with his/her experience, perception, and expectations. It is critical that the governmental representative in charge of the disaster response provides the answers rather than allow a wide-open survey with an uncontrolled response population. The survey was developed, implemented, and executed following the Tailored Design Method (Dillman et al. 2008). The state emergency management directors were contacted via regular mail introducing the survey and indicating that they would receive a formal invitation to participate in the survey within the next few weeks. The formal, personalized and signed hardcopy letter to each director was sent on November 9, 2011 inviting them to complete the online survey. This letter included the assigned login name and password for their state. In the event that there were any issues with logging into the survey, contact information for the principal investigators was listed. If the survey was submitted, a thank you letter was promptly sent out. Not surprisingly, only a few state directors immediately complied with our initial invitation. Following Dillman’s protocol in the subsequent weeks we sent an email reminder, a second signed letter of invitation and a 2nd email reminder. Twenty-nine (29) states had completing the survey by January 1, 2012. From experience with the state survey conducted in 2005, we knew the remaining directors may only respond based on personal phone calls and explanations of the importance these results were to the Federal agencies and ultimately, to the Federal responses to future disasters. We made personal telephone calls to the remaining 21 state directors during the first 2 weeks of January 2012. Finally, by February 10, 2012 all 50 state directors or their designated staff completed the survey.
2.2 Survey Instrument The survey instrument consisted of a preamble explaining the survey, a password protected login page, and four data/information categories: geospatial data use, data/resource sharing, emerging technologies, and confidential questions/answers. The instrument was constructed in close cooperation with cognizant DHS staff, the FEMA Remote Sensing Coordinator, a DHS staff focus-group meeting, and feedback from the Office of Science and Technology Policy (OSTP) Subcommittee on Disaster Reduction. Additionally, NASA program managers provided constructive feedback in refining the survey instrument. Also, the North American Counties Organization (NACO), and representatives from several county-level
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emergency response agencies evaluated the final draft instrument and provided invaluable feedback on the question construction. To encourage honest and complete answers to question, and to abide by Institutional Review Board procedures, state respondents were all informed their individual answers to questions would be held confidential and only reported to Federal agencies or the public in summary form.
3 Findings 3.1 Disaster Experience Based on the documented frequency of presidential disaster declarations (PDDs) (Fig. 1) all states have experienced a major disaster. In large part, PDDs are issued for counties and the pattern of such declarations clearly indicates a differential experience level both within and between states. The responses from our survey respondents indicate all but two states have experienced a PDD during the last 5 years. Of those 48 states that had experienced a major disaster, 77 % said they used either satellite or aerial imagery over the disaster area in the response/ recovery phases. 92 % of those using imagery indicated the type of imagery was airborne (only 44 % utilized satellite imagery). Clearly the states have greater access to, and may prefer, the use of airborne imagery. How did the states obtain imagery? Fifty percent of the states relied on imagery collections by the Federal government and 72 % collected imagery (e.g. oblique photographs/images or vertical mapping imagery) from airborne platforms. 67 % of the respondents indicated the imagery was sufficient for their needs. In confidential responses, several states indicated that limitations to the use of imagery were often based on challenges of requesting imagery (if they were not able to collect independently), ability to collect imagery quickly enough for use in the response phase, and questions of how the imagery collection would be funded.
3.2 Pre-Event Geospatial Data Needs Baseline geospatial data representing the natural and built-up environment prior to a disaster event is used by counties for management purposes but essentially only useful to the state EMOs for mitigation/planning. During and after the disaster event baseline data provides detailed information on what was ‘‘there’’, prior to the disaster, may be useful for change detection, and is used for positioning resources in response/recovery operations. Since hurricane Katrina in 2005 the DHS has funded a large effort to create and maintain the HSIP-Gold and Freedom geospatial databases. Presumably these data sources are of high importance to state EMOs.
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We also sought to identify the primary source of baseline geospatial data the states rely on for each of the layers. In the 2005 survey the baseline data layers of extreme importance in the response and recovery phases were transportation, population distribution, and location of structures. The transportation data theme was clearly the most important baseline data in the response/recovery phase. Oddly, the two spatial data themes that are commonly mapped with remote sensing technologies, land cover and terrain, were listed as the least important data types of any hazard phase. Many states indicated an ‘‘other’’ source (65 and 76 % for buildings and parcels, respectively). We do not know for certain what this other source might be but hypothesize the other source may be a state-wide consortium where counties or local agencies within the state voluntarily contribute their parcel/building footprints. In the 2011 survey, the most important baseline data layer was the critical infrastructure data layer (as indicated by 74 % of the states in Table 1). (Note: We did not use the critical infrastructure or aerial imagery data layer as choices in the 2005 survey and thus, do not have directly comparable responses). The source of the critical infrastructure layer was either in-house (38 %), other (32 %), or from HSIP (30 %). The HSIP data stream is not a primary data source for any of the baseline data layers (i.e. pre-event). In fact, the highest percentage of responses by the states was the 30 and 29 % reliance on HSIP for the critical infrastructure and energy/fuel supplies data layers, respectively. This observation raises an interesting question about the overall importance or lack of awareness of the HSIP data stream in planning for and during the disaster response phase of the hazard cycle.
Table 1 Source of baseline (i.e. prior to disaster event) geospatial data and percentage of states in 2011 indicating this data layer was a priority Data type Source of data (% of states) Highest priority InHSIP Commercial Other house vendor Building footprints Building/parcel characteristics Communications networks Energy and fuel supplies (e.g., electric, gas, etc.) Critical infrastructure (e.g., hospitals, schools) Land use or land cover Hydrography Population distribution Sewer/water/utilities Shelter locations Elevation Transportation networks Aerial imagery (vertical or oblique)
21 12 36 18 38 11 15 11 18 65 11 26 17
0 2 15 29 30 5 2 9 11 0 0 9 0
15 10 19 18 0 7 7 11 5 6 11 9 29
65 76 30 35 32 77 76 69 66 29 78 58 54
4 18 20 20 74 4 0 33 6 22 16 39 45
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The most important data layer after critical infrastructure was aerial imagery. Interestingly, aerial imagery is not a typical GIS data layer that may be directly used in a GIS analysis. In fact, imagery is a source of information that must be abstracted, such as through visual analysis. In hurricane Katrina and Ike imagery was a key basemap for positioning other features on cartographic products. As in the 2005 survey, transportation and population were also selected in the 2011 survey as data layers of high priority. More than half (65 %) of the state-level EMOs maintain the data layer of shelter locations. All other data layers are obtained from a combination of HSIP, commercial vendors, or ‘‘other’’.
3.3 Disaster Impact Data Of particular interest in this research were the geospatial data types representative of the disaster impact that were of the highest priority (Table 2). We listed seven data layers indicative of the built-up environment for which the respondents selected. A disaster impact data layer represents the damaged features for that theme. The responses indicate a clear set of three priority data layers. Not surprisingly, critical infrastructure again appeared as the data layer of highest priority with 69 % of the states (Table 2). Disaster extent and damage to transportation features was almost the same priority level. So where do states obtain data on damaged features? Do they contract aerial flyovers, airborne or satellite imagery, or ground surveys? The use of emergency responders on the ground was the primary source of all data layers except for energy and fuel supply damage and disaster extent. The disaster extent source was from airborne flyovers, not airborne/satellite mapping imagery. In the 2011 survey, 32 % of the states indicated they had a mission responsibility to acquire satellite/aerial imagery in the next major disaster. When asked if the Federal government is expected to collect airborne/satellite imagery in
Table 2 Source of impact data (i.e. post-disaster event) geospatial data and percentage of states in 2011 indicating this data layer was a priority Data type Source of data (% of states) Priority level Ground Airborne Airborne or Other survey flyover satellite imagery Building damage 75 Communication network damage 62 Disaster extent (e.g., burned area) 28 Energy and fuel supply damage 48 Critical infrastructure (e.g., hospitals, schools) 80 Sewer/water/utilities 70 Transportation damage 59
17 9 46 2 4 2 27
8 0 16 0 4 0 4
0 30 10 50 12 28 10
31 37 67 25 69 8 65
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the response phase 46 % of the states indicated ‘‘only if requested’’ while 30 % indicated ‘‘regardless of whether requested’’. 54 % of the states expected the Federal government would collect such imagery with ‘‘no cost’’ to the states. When asked about institutional problems in acquiring/sharing geospatial data 51 % of the states indicated difficulties in working with other entities. The entity the states experienced the most problems with was with Federal agencies (73 % of states indicating this).
3.4 When Disaster Impact Data are Needed Perhaps the most difficult aspect of using geospatial information, such as remotely sensed imagery, during a disaster event is obtaining the data/information in a timely manner. Immediately following a disaster event police/fire department personnel and other emergency responders are deployed to view the impact area and provide situational awareness. This process is referred to putting ‘boots on the ground’ or ‘eyes in the air’, depending on terrestrial or airborne vantage points. Unlike most other applications of remotely sensed data collecting airborne/satellite imagery within 24 h of the event is challenging. Few previous studies exist to indicate how valuable new remote sensing collections are after the disaster event—or ‘n’ days after the disaster event. Hodgson et al. (2010) surveyed the emergency management offices in the United States and found practically all (90 %) state offices needed information on building damage within 3 days after the disaster event. However, the immediacy of information varied by damage type. For instance, only 50 % of states indicated they needed information on crop/ vegetation damage within 3 days of the event. A theoretical information-lag time curve was suggested to relate the relative value of remotely sensed derived information to the lag-time after the disaster event (Fig. 2). The understanding is if the information is provided after some delay other sources (e.g. ‘boots on the ground’) will provide the same information and thus, imagery is of less value. In this 2011 survey, 30 % of the states indicated building damage information obtained from remotely sensed imagery after 72 h (3 days) was too late. In other words, 70 % of the states indicated critical infrastructure damage was needed within 3 days of the event. 16 % of states indicated information from imagery after 7 days was still useful. From a modeling perspective, the value of information to lag time for all damage categories examined followed a reverse exponential trend. The value of information quickly dropped with increasing lag time and then became a constant value for a lag-time of 7 days and more. The pattern for other disaster impact data layers was similar (Fig. 3).
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Fig. 2 Theoretical curve illustrating when post-disaster imagery information is too late for the emergency response phase (after Hodgson et al. 2010)
Fig. 3 Empirical curve derived from state responses for when post-disaster imagery information is too late for the emergency response phase
3.5 Staffing Needs Adequate skilled staff is often cited as an impediment to using GIScience approaches in disaster management (Zerger and Smith 2003). In a series of questions we probed issues related to geospatial staffing (e.g. number of, expertise, etc.). For example, we obtained information on the GIS-based models (e.g. HAZUS, ALOHA, HURREVAC) used in disaster response and the limitations of using such models. By far the most frequent limitation cited was ‘‘user knowledge required’’ (18 % of the states). Only two states indicated ‘‘no limitations’’. What
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we experienced in the 2005 survey of states was a deficiency in geospatial staff within the emergency management agency. For example, 23 % of the states in 2005 indicated they had no geospatial analysts within their emergency management agency. This staffing problem has largely changed. In the 2011 survey 34 % indicated they only had one such analyst. Only two states did not have at least one geospatial staff in their agency. 90 % of the states had between one and five geospatial staff members. With respect to the exploitation of remotely sensed imagery (aerial or satellite), however, only 26 states indicated they had no staff that are responsible for such imagery. In separate questions on memorandum of understanding/agreements (MOU/MOA) and assistance, the 56 % of the states indicated they rely on additional staff support through an MOU/MOA. Thus, the reliance on federal or other state/county agency support during a disaster response for imagery exploitation is still a problem.
3.6 Crowd Sourced and VGI Data The research emphasis on volunteered geographic information (VGI) is one of the dominant paradigms in GIScience this decade (Goodchild and Glennon 2010; Heipke 2010). These methods are considered by several to be particularly useful in disaster response (Poser and Dransch 2010; Roche et al. 2011). VGI approaches are currently under investigation by FEMA, NOAA, the National Weather Service, and other agencies for acquiring near real-time information in disaster events. FEMA is investigating the potential of crowd-sourcing for exploiting image interpretation associated with hurricane Sandy in 2012. The infrastructure for utilizing VGI to understand the unfolding disaster is available although states may not have the capacity to utilize such approaches. Are state EMOs currently using or considering using such approaches? We did not separate questions on crowd-sourcing from VGI but grouped them in the survey questions. We asked the states if they were either using or considering the use of crowd sourced or volunteered geographic information (VGI) data during the response/recovery phases of the disaster. 58 % of the states indicated they have an interest in utilizing crowd-sourced and VGI data. Surprisingly, only 18 % of the states indicated they were currently using crowdsourced/VGI data. Subsequent questions revealed states had concerns about the reliability of VGI data (78 %) or quality of VGI data (66 %). 52 % said they saw a limitation of merely setting up a crowd-sourced or VGI system.
4 Conclusions Findings from this nationwide survey of U.S. state EMO offices provides important information on the geospatial data needs and expectations in the disaster response/ recovery phases of the disaster cycle. GIScientists interested in contributing to the
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solution in disaster response should focus on the priority disaster impact data layers of critical infrastructure, disaster extent, and transportation. To be largely useful, such damage information needs to be available within 72 h of the event and becomes decreasingly useful after even 24 h. There are considerable expectations of the Federal government to lead on the collection of image data. Although practically all state EMOs have a GIS analyst more than half do not have a remote sensing analyst, suggesting exploitation of imagery must be conducted by others. Finally, the state EMOs share considerable interest in using VGI or crowd-sourced approaches but have strong reservations of the reliability and quality of such derived data. This article presented results from part of the state survey of EMO agencies conducted in 2011. A companion survey of U.S. counties was also conducted concurrently with the state survey providing an understanding of the similarities and disparities between state and county geospatial data needs, approaches, and problems. It should also be reported that this survey occurred prior to Hurricanes Isaac and Sandy and do not reflect improvements made at Federal, State, and local levels in the use of remote sensing and GIS technologies for those incidents. Furthermore, this research did not investigate the variable of disaster incident scale as a determinant of the temporal value of remote sensing data. It may be that disasters at the scale of Hurricanes Katrina and Sandy or the next big earthquake require the collection and analysis of remote sensing to address critical response questions past the stated 72 h timeline. As the use of remote sensing for disaster response improves new questions may be discovered that extend the use of airborne and satellite images into the longer recovery period. That would mean collecting the appropriate imagery to support the answers to those questions. Acknowledgments This research was supported by a research grant from the Department of Homeland Security Science and Technology Directorate.
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