GIS / Remote Sensing
Although sometimes considered simply as a mapping tool, Geographic Information System (GIS) is a computerized database that stores, manipulates, analyzes, and presents spatial information. Remote sensing is the process of acquiring information without being in direct physical contact with the object, and generally refers to aerial or satellite imagery and/or radar imagery. ESI uses remotely sensed data in GIS for nearly every project. Use ranges from basic cartography to statistical analysis to advanced application of database features for landscape analysis and modeling.
Most geographic data are stored in GIS in “layers” that can be digitally overlaid upon one another to generate meaningful, relevant, and accurate project information. Often, during the proposal stage, GIS layers are combined to generate an informative “picture” of the project area. This tells us about natural features associated with a project area and helps us understand the scope and scale of the project. Once a project is awarded, use of GIS aids project design and implementation, including field activities. Field data are imported into GIS to create clear, precise maps for inclusion in our technical reports.
Mapping, though a universally recognized GIS product, is far from the most robust way that ESI uses GIS. Statistical analyses allow extraction of additional quantitative information that may otherwise be lost. At a basic level, GIS statistical analyses are used to produce tables and charts to quantify project impacts. For example, foraging data from radio telemetry studies is imported into GIS to determine the size, location, and other attributes of a species’ home range.
While most field data are incorporated directly into maps and reports, some projects, such as wetland delineations along linear corridors, require incorporation of additional attribute information for features identified in the field. ESI develops customized scripts to efficiently generate and analyze field attribute data. This reduces post-processing time and controls costs while accurately conveying survey data.
ESI’s professional geographers and landscape ecologists employ the power of GIS and remotely sensed data at an advanced level to develop species-specific predictive models. During this type of modeling, GIS runs a series of intricate mathematical algorithms to correlate known occurrences, landscape, and other environmental data to produce statistically accurate species distribution information. This model is used to estimate potential impacts (mortality risk) from project development and to aid implementation of conservation measures.