An evaluation of the role played by remote sensing technology following the World Trade Center attack

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An evaluation of the role played by remote sensing technology following the World Trade Center attack
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  See discussions, stats, and author profiles for this publication at: An evaluation of the role played by remotesensing technology following the World TradeCenter attack   ARTICLE   in  EARTHQUAKE ENGINEERING AND ENGINEERING VIBRATION · MAY 2003 Impact Factor: 0.73 · DOI: 10.1007/BF02857548 CITATIONS 3 READS 32 3 AUTHORS , INCLUDING:Charles HuyckImageCat 47   PUBLICATIONS   360   CITATIONS   SEE PROFILE Available from: Charles HuyckRetrieved on: 04 February 2016  An Evaluation of the Role Played by Remote Sensing Technology following the World Trade Center Attack. Charles K. Huyck Vice President, ImageCat Inc., 400 Oceangate, Suite 1050, Long Beach, CA 90802 Dr. Beverley J. Adams Project Scientist, ImageCat Inc., 400 Oceangate, Suite 1050, Long Beach, CA 90802 David I. Kehrlein Vice President GIS Operations, ImageCat Inc., Woodhaven Ave, Carmichael, 95608 Abstract- Remote sensing technology has been widely recognized for contributing to emergency response efforts after the World Trade Center Attack on September 11th, 2001. The need to coordinate activities in the midst of a dense, yet relatively small area, made the combination of imagery and mapped data strategically useful. This paper reviews the role played by aerial photography, satellite imagery, and LIDAR data at Ground Zero. It examines how emergency managers utilized these datasets, and identifies significant problems that were encountered. It goes on to explore additional ways in which imagery could have been used, while presenting recommendations for more effective use in future disasters and Homeland Security applications. To plan adequately for future events, it was important to capture knowledge from individuals who responded to the World Trade Center attack. In recognition, interviews with key emergency management and Geographic Information System (GIS) personnel provide the basis of this  paper. Successful techniques should not be forgotten, or serious problems dismissed. Although widely used after September 11th, it is important to recognize that with better planning, remote sensing and GIS could have played an even greater role. Together with a data acquisition timeline, an expanded discussion of these issues is available in the MCEER/NSF report "Emergency Response in the Wake of the World Trade Center Attack: The Remote Sensing Perspective" (see Huyck and Adams, 2002).  1 Introduction- The World Trade Center attack was an event unparalleled in history. There was no plan for such an event, and the demand for information proved to be immense. Remote Sensing and geospatial data played a critical role in response efforts (see Hiatt, 2002; Huyck and Adams, 2002; Logan, 2002; Williamson and Baker, 2002). The need to coordinate an event of this magnitude in a dense, yet relatively small area, made the combination of imagery and data maps very powerful. Before the event, the City of New York had undertaken a detailed mapping effort, resulting in the production of highly accurate vector coverage. This Geographic Information System (GIS) data, coupled with raster imagery collected by organizations including: EarthData; NASA;  NOAA; and Space Imaging, provided an evolving depiction of disaster response that would not otherwise have been possible. As an emerging technology in emergency response, a through investigation of the role played by remote sensing data at Ground Zero is clearly warranted. The following paper evaluates key data sets including: aerial photography; multispectral satellite coverage; LIDAR altimetry; thermal imagery; and hyperspectral data, drawing on information gained during a series of interviews with individuals involved in emergency operations. Although satellite-based radar imagery was also acquired, these scenes played a minimal role in response efforts, and as such are omitted from further discussion. Section 2 discusses how each remote sensing dataset was used, both singularly and in combination. A useful summary of GIS processing techniques employed at the various mapping centers is given by Cahan and Ball (2002) and Thomas et al. (2002). Significant  problems encountered with data manipulation, implementation and interpretation are presented, followed by a discussion of additional ways in which the imagery could have been used. Section 3 goes on to present key lessons learned, while Section 4 summarizes practical recommendations for integrating remote sensing into disaster planning and response. 2 Evaluation of Remote Sensing Data The following section provides details of remote sensing imagery that was acquired following the World Trade Center attack. Information concerning the application and performance of each dataset was primarily obtained through a series of interviews, undertaken by ImageCat with key individuals involved in emergency operations, from organizations including: the Federal Emergency Management Agency (FEMA); the New York Fire Department (FDNY); the City of  New York Department of Information, Technology and Telecommunications; the New York State Office for Technology; the State of California Governor’s Office of Emergency Services, managing FEMA’s Urban Search and Rescue GIS operation at Ground Zero; the Environmental Protection Agency (EPA); the United Sates Geological Survey (USGS); Environmental Systems Research Institute; MITRE Corporation; Plangraphics; the University of South Carolina; and Hunter College. 2.1 Aerial Photography  High-resolution digital images collected by EarthData were the most widely used source of aerial data. Figure 1 provides an example of the 6-inch panchromatic data collected between 15 th  September and 22 nd  October 2001, using a Navajo Chieftain aircraft equipped with a Kodak Megaplus Model 16.8i digital camera (see EarthData, 2001). Where possible, flights were timed to coincide with midday, in order to minimize shadowing effects. In terms of uses, optical coverage acquired during early stages of the response and recovery effort gave a clear indication of the magnitude of damage and extent of debris on the site. It also enabled rescue teams to orient themselves, while aiding the navigation of emergency workers unfamiliar with the Lower Manhattan area. The aerial scenes were widely distributed and extensively used for comparative purposes, presented alongside imagery of the World Trade Center prior to its collapse. EarthData aerial coverage was integrated with a number of other datasets. Fused with Computer Aided Design (CAD) models of the Twin Towers floor plan, ortho-rectified photographs enabled workers to pin-point specific locations of infrastructure, such as stairwells and elevator shafts. This composite of data was further employed for logistical planning, when it was necessary to identify a safe and stable position for cranes lifting and clearing debris at Ground Zero. Identifying potentially dangerous areas on the debris pile around voids and depressions also reduced the risk of injury to recovery teams. The orthophotographs were widely employed as a  base map, on which other geospatial data was overlaid. For firefighters, thermal and optical airborne data was a useful combination. A 2D 75sq ft, numbered, transparent grid, established by the FDNY for logistical purposes, was superimposed on the images. This provided a common reference system for tracking objects found amongst the debris. It also enabled recovery workers to discuss activities and locations on the site. This was particularly important, since GPS devices were not working due to interference. It is possible that use of this data significantly shortened thousands of conversations between firefighters. A number of problems were encountered with the use of aerial photography at Ground Zero, which if resolved, could substantially improve its performance in future emergency operations. Optical data is limited when the scene below is obscured by smoke. Optical coverage is therefore of little value if fires are burning during early phases of a disaster. Shadowing is a further limitation, particularly in dense urban environments with a concentration of high-rise buildings. Unless data is acquired at midday, shadows obscure areas of interest, impairing visual interpretation. In terms of spectral resolution, EarthData collected grayscale digital images (see Figure 1). However, color datasets are generally easier to interpret, since features are distinguished by color, in addition to shape and contrast (see Figure 2a). Ideally, color  photographs similar to those acquired by NOAA (NOAA, 2001) would have been available immediately after the event. Spatial resolution was also an issue. The Phoenix Photography and Imagery Group of the Fire Department of New York (FDNY) identify ~3” as the optimal pixel size for distinguishing individual girders. According to the FDNY, the usefulness of orthophotographs to response teams was further limited by the 12 hour lag between data acquisition and release, during which time conditions at Ground Zero had changed. Although this temporal resolution was the stipulated requirement on which EarthData acted, near real-time data, delivered within several hours of acquisition, was required.  Experience from the World Trade center attack suggests that the value of remote sensing data could be enhanced through a number of simple procedures. For example, multi-temporal change detection might enable automated monitoring of clean-up operations. Image processing techniques could also be used to generate additional information from high-resolution aerial  photographs. Manipulating the visual representation in this way might reduce shadowing effects, while procedures such as edge enhancement could map the location of girders. Density splicing and classification techniques could also be used to categorize debris for planning purposes. 2.2 Multispectral Satellite Imagery Following the World Trade Center attack Space Imaging and SPOT Image rapidly posted multispectral satellite coverage on the Internet. Spanning visible and near-infrared regions of the electromagnetic spectrum, these images are readily interpreted, as they resemble the ground surface as it appears to the human optical system. Multispectral satellite images were utilized by emergency responders several days before the aerial photography. As shown in Figure 3, IKONOS imagery acquired by Space Imaging (see Space Imagining, 2002) gave the General Public a dramatic view of Ground Zero, with the extent of damage published on the front page of newspapers around the World. The readily interpreted color composite, with a spatial resolution of 1m, provides a detailed representation of the ground surface. For visualization purposes, IKONOS data was widely employed as a base map, and frequently presented as a before/after sequence. As with the aerial coverage, these images helped out of town relief workers navigate around the area, and orientate themselves within the site. The IKONOS sensor subsequently acquired a number of ‘off-nadir’ images, where the sensing device points sideways towards its target area. Consequently, other tall buildings obscured features of interest in Lower Manhattan. Furthermore, immediately after the terrorist attack, visibility in the IKONOS imagery was limited by smoke obscuring the ground surface below. The revisit frequency is also an issue for earth orbiting satellites such as these, which for 1m IKONOS data captured near nadir, is 2.9 days. The SPOT 4 data played a limited role throughout  proceedings, due to the reduced spatial resolution of 10m (SPOT, 2002). In future disasters, high-resolution data from sensors such as IKONOS and Quickbird (which was launched in October 2001) will provide a useful alternative to aerial photography,  particularly when data acquisition by aircraft and helicopters is prevented due to an air traffic  ban. The extensive coverage provided by satellite data is useful for monitoring events where damage is sustained at a regional rather than localized scale, particularly when change detection algorithms are used (Huyck et al., 2002). For analytical purposes, multispectral imagery has the  potential to yield additional information, compared with grayscale or color aerial photography. Classification is an image processing technique that assigns features to groups or ‘classes’, depending on their characteristics in different bands of the electromagnetic spectrum. For example, classification of high-resolution imagery could distinguish between surface materials at Ground Zero. 2.3 LIDAR Altimetry
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