The Use and Uncertainties of Spatial Data for Landscape Models: An Overview with Examples from the Florida Everglades

摘要: Models are usually developed for one of two purposes: to better understand ecological systems or evaluate the influence an altered condition make a decision set policy. A spatial model can loosely be defined as that has either more state variables function space related other space-dependent variables. The information-richness data and models comes from their simultaneous depiction temporal patterns. This richness is easily grasped by only most powerful all computers, mind. For example, mind immediately compare temperature map today with day before quickly develop trend analysis areas change. Put three maps together computer may even venture predict cooling down warming up. It does this easily, no thought distribution weather stations, kriging techniques, collection errors, scale, knowledge meteorological models, yet these things factors contribute uncertainty mental model. These uncertainties become extremely important when tries formalize quantify modeling process prediction.