GIS Supports Decision Makers

By Guy Seeley

Geographic information systems are a powerful mechanism for integrating multiple spatial data sources into a common environment, enabling spatially aware quantitative data fusion — for example, combining vegetation mapping with structure location to compute potential wildfire exposure. With the right data resources and algorithms, a GIS platform can answer questions such as, How has mountain pine beetle damage affected vegetation within 100 yards of my house?

Dealing with complex geographic phenomena requires similar types of capabilities. For example, in wildfire risk, key parameters include vegetation type, terrain slope, road access, and building construction type, as well as weather and climate conditions. Remote sensing describes data derived from sensors not physically present at an actual site area — a satellite image vs. a site visit. GIS technology is needed to provide timely and efficient solutions for the fusion of remotely sensed information derived from airborne or space-borne cameras with existing geospatial information and characteristics of homes, roads, pipelines, political boundaries, and other indexed features.

Toward a Dynamic, High-Resolution Future
Today’s remote sensing capabilities are dramatically more advanced than even ten years ago. Multiple streams of remotely sensed data are now readily available from a variety of observing platforms — from orbiting multispectral scanners to automobile-mounted color cameras. Others have very high spatial resolution; commercially available panchromatic (a.k.a. black and white) imagery is now approaching 0.5 meters (roughly 20 inches).

What will be available ten years from now? Future plans call for higher spatial resolution combined with high spectral resolution and rapid refresh. Aircraft-mounted hyper-spectral (high spectral resolution) imagers can provide this capability currently for limited areas. Satellite implementations are also being planned.

The Importance of Remote Sensing Capabilities
With respect to spatial resolution, sub-meter-resolution satellite imagery (imagery with a pixel size less than one meter) is useful in many ways. But the dramatic improvement is in the increasing spectral resolution of imagery. Today, most data sources are capable in either spatial or spectral dimensions. Think of spatial and spectral as the difference in information between a black-and-white and a color photograph. Is the lawn brown or green? Is the roof wood or asphalt? Is there vegetation directly adjacent to the house? Have pine beetles killed trees in the immediate vicinity? Having answers to those types of questions in a readily accessible spatial-reasoning platform enables a new level of understanding of a variety of hazards, but it requires more information processing than is available from black-and-white imagery.

With respect to refresh, GIS technology has typically provided preparation and analysis that result in a static data set. In many cases, real-time decisions are made from the static data set. What decision makers need is the ability to incorporate up-to-the-minute and modeled forecast information into GIS data sets that update frequently and are accessible in real time.

High-Resolution Imagery Enables Advanced GIS Solutions
Future GIS solutions will soon offer enormous capabilities. But much can be done today. For example, the Landsat program, which began in 1972 and is now operated by the USGS, is a satellite program useful for assessing wildfire risk. Landsat data is used today to quantify wildfire risk and to monitor changes in vegetation due to growth, drought, and fire. Operated by NASA, MODIS is another important current multispectral imaging satellite used for many of the same applications. MODIS differs from Landsat mainly in its higher spectral — but lower spatial — resolution (see Figures 1 and 2).

Data derived from imagery is no longer a scarce commodity. Now widely available, robust GIS technology can be populated with current data made possible by advancements in remote sensing technology. New kinds of quantitative information can be gathered, placed in context, and used to assess risk in historical and currently evolving situations. The potential of GIS technology is only beginning to be realized.

Dr. Guy Seeley is vice president of the WIST (Weather Impacts on Sensing Technologies) division at Atmospheric and Environmental Research (AER). A Verisk Analytics subsidiary, AER provides cutting-edge environmental research, development, software tools, and analysis.