Sven Fuhrmann

Multimodal interface platform for geographical information systems (GeoMIP) in crisis management

A novel interface system for accessing geospatial data (GeoMIP) has been developed that realizes a user-centered multimodal speech/gesture interface for addressing some of the critical needs in crisis management. In this system we primarily developed vision sensing algorithms, speech integration, multimodality fusion, and rule-based mapping of multimodal user input to GIS database queries. A demo system of this interface has been developed for the Port Authority NJ/NY and is explained here.

Geoinformation Technologies to Support Collaborative Emergency Management

In todays emergency management environments geoinformation technologies play a vital role, but their potential has not been fully exploited. Key decision makers usually do not have direct access to Geographic Information Systems and if they receive access, complex user interfaces often hinder performance for high pressure tasks. In order to provide decision makers with direct and easy access to geoinformation in emergency situations and support group collaboration, we developed three collaborative geoinformation platforms: the Multimodal Interface Platform for Geographic Information Systems (GeoMIP), the GeoCollaborative Crisis Management platform for mobile collaboration and a web-portal for humanitarian relief logistics. The technologies developed are intelligent, multimodal (speech and gesture-based) user interfaces that allow synchronous and asynchronous collaboration between decision makers; support GIS use by mobile emergency management teams; and provide open standards-based web portal technologies.

GeoCollaborative crisis management: designing technologies to meet real-world needs

Preventing, preparing for, responding to, and recovering from natural and human-induced disasters all require access to geographically referenced information and tools for making available information relevant to the tasks at hand. Goals of the research summarized here are to advance our scientific understanding of how groups (or groups of groups) work with geospatial information and technologies in crisis management and to use that understanding to guide development of tools that are intuitive for non-specialist users and that enable coordination within and across crisis management teams. This overview highlights progress on: understanding work in crisis management, enabling distributed information access through context-mediated geo-semantic interoperability, extension of natural, multimodal interface methods to mobile devices, development of a collaborative map-based web portal to support international humanitarian relief logistics, and technology transition into real-world practice. We also introduce our new DHS-supported Regional Visualization & Analytics Center, which builds directly upon our GCCM work.

Flood mapping in the lower Mekong River Basin using daily MODIS observations

ABSTRACT In flat homogenous terrain such as in Cambodia and Vietnam, the monsoon season brings significant and consistent flooding between May and November. To monitor flooding in the Lower Mekong region, the near real-time NASA Flood Extent Product (NASA-FEP) was developed using seasonal normalized difference vegetation index (NDVI) differences from the 250 m resolution Moderate Resolution Imaging Spectroradiometer (MODIS) sensor compared to daily observations. The use of a percentage change interval classification relating to various stages of flooding reduces might be confusing to viewers or potential users, and therefore reducing the product usage. To increase the product usability through simplification, the classification intervals were compared with other commonly used change detection schemes to identify the change classification scheme that best delineates flooded areas. The percentage change method used in the NASA-FEP proved to be helpful in delineating flood boundaries compared to other change detection methods. The results of the accuracy assessments indicate that the −75% NDVI change interval can be reclassified to a descriptive ‘flood’ classification. A binary system was used to simplify the interpretation of the NASA-FEP by removing extraneous information from lower interval change classes.

Teaching Disaster Preparedness in Geographic Education

Abstract Extreme natural and human-made disasters can affect the lives of thousands of citizens. The only way we can prepare ourselves for such situations is to learn and establish basic survival strategies within our families and communities. This article explores how K–12 teachers could help educating children about disaster preparedness by utilizing existing educational standards and Web portals for disaster education. A set of exemplary lesson plans for elementary schools, middle schools, and high schools, based on the National Geography Standards, describe how disaster preparedness could be integrated in lesson planning. The lesson plans can be downloaded at http://www.geo.txstate.edu/grosvenor/publications/GEO7347_lesson_plans.pdf.

Developing interactive geospatial holograms for spatial decision-making

Spatial decision-making in time-critical situations requires effective and usable two-dimensional and three-dimensional (3D) cartographic products. Holographic displays allow decision makers to work with auto-stereoscopic maps without the hassle of interacting with complex user interfaces or additional vision hardware. Holographic production processes have advanced greatly in a short period and now support timely and full integration of digital 3D models in geospatial holograms. George Mason University’s and Zebra Imaging’s research on interactive holographic motion displays showcases the leadership in moving cartography and geovisualization research in the US forward. In close cooperation with academic researchers, decision makers, and domain experts, the usability and usefulness of these cartographic products is tested and design guidelines for effective geospatial holograms are being developed.

Estimating Residential Carbon Footprints for an American City

The proliferation of online emission calculators and the growing popularity of carbon footprint assessments recently underscores an emerging interest among Americans in understanding their personal environmental impacts, especially in relation to greenhouse gas emissions. While studies have quantified carbon footprints at a variety of geographic scales using economic data, or a combination of economic and census data, few have produced results that were immediately useful for local-scale emission reduction efforts. The authors explore the feasibility of utilizing block group level census data to estimate the residential carbon footprint of an American city. A census-based emission model was adapted from the United States Environmental Protection Agencys Individual Emission Calculator. Block group census data were used as surrogates for household energy consumption and transportation related carbon emissions. Although lacking some of the finer nuances of individual behavior assessments, this approach enables analysis of a continuous urban landscape with a relatively high degree of data resolution using Geographic Information Systems GIS and standard desktop-software. The model output, paired with choropleth and dasymetric visualizations, illustrate that census data can be successfully adapted to estimate the residential carbon footprint for Austin, Texas, and by extension, any other American city with equivalent census data coverage.

Comparing Fear of Crime and Crime Statistics on a University Campus

Campus crime at colleges and universities has resulted in a call for more safety and preventive measures from policymakers, students, to citizens. While research highlights students’ fear on campus crime, few studies have examined this topic from a spatial and cognitive perspective. In this chapter the authors report on a novel methodology to compare campus crime data with participants’ self-reported cognitive fear of crime maps. In this study, 313 undergraduate students provided fear of crime maps at a middle-sized university in the southwestern United States. The students’ perceptions were aggregated and compared to university crime statistics to produce five bivariate maps. These maps represent perceived fear of crime in relation to four broadly observed crime categories namely burglary, theft, harassment, and sexual assault. In this research effort, students’ fear of crime is aligned with data for actual burglary and theft occurrences but their fear is exaggerated for harassment and sexual assault. The implications of this study are multifold, extending from potential safety improvements and better decision-making (e.g., aid law enforcement to target specific areas for crime monitoring) to developing educational workshops to dispel myths and present facts on campus safety. The introduced bivariate mapping technique provides another step towards safer university and college campuses.

Investigating Geospatial Holograms for Special Weapons and Tactics Teams

Special Weapons and Tactics (SWAT) teams rely heavily on collecting and applying geospatial intelligence. Traditional two-dimensional mapping products might limit or hinder successful operations by not showing important three-dimensional information of the terrain and its natural and/or human-built objects. Geospatial holograms are able to display these three dimensional spatial features to users without requiring special eyewear or using complex viewing technologies. A point light source is all that is required to make the imagery visible. Before introducing geospatial holograms into the SWAT domain, where lives are at potential risk, a series of usefulness, acceptance, and usability tests need to be performed. One of the key geospatial hologram design requirements identified for SWAT incidents was support for effective route planning and wayfinding. This paper will report about a first pilot study that investigated and compared wayfinding performance of SWAT teams using both traditional 2D imagery and geospatial holograms. Our initial research indicates that geospatial holograms could enhance SWAT operations, especially in multi-story environments. In the pilot study geospatial holograms were positively reviewed by SWAT team members and were described as a technology that should be further explored.

GIS-Based Logistic Regression for Landslide Susceptibility Analysis in Western Washington State

The Oso landslide, one of the most recent disasters, occurred on March 22nd, 2014 in western Washington State. It caused significant property damage and killed over 40 people. As a result, a renewed interest has emerged for creating more accurate landslide susceptibility maps for this region. Research addressing landslide susceptibility within the north Puget Sound region of western Washington is lacking; therefore, this study develops a probabilistic GIS-based landslide susceptibility model for the north Puget Sound region. Multivariate logistic regression was utilized to create a landslide susceptibility map of Whatcom, Skagit, Snohomish, and King Counties. To predict probable areas of landslide occurrence, a landslide inventory map was prepared and fourteen topographic, geologic, environmental, and climatic predictor variables were considered. This research aims to assist in restructuring western Washingtons landslide policies, and could serve as the first step in producing more accurate landslide susceptibility maps for the region.