Remote sensing has established a key role in modern wildlife ecology, but the data types and methods are both varied and complex, and the potential for misuse by the uninformed is high. The basic attributes of earth-observing sensors and data products can be described by their spectral, spatial, radiometric, and temporal resolutions, and general categories of data products are normally consistent across agencies and organizations. Users of remote sensing technology seeking to link information needs with remote sensing strategy must balance knowledge of data and processing techniques with a clear understanding of the nature of the information desired. Wielded within a sophisticated application framework, remote sensing allows for an impressive suite of wildlife ecology and habitat attributes to be modeled, predicted, and monitored through time, including land cover physiognomy, vegetation structure and condition, forage characteristics, specific nutrient concentrations, overall productivity, and biomass.
IntroductionA spatial information management approach to applied wildlife ecology will rely on our capacity to link animal-based data sets -observations related to a species' distribution, abundance, health, or genetics, for example -to a variety of spatially