SELECTION OF SCALE FOR EVERGLADES LANDSCAPE MODELS

This article addresses the problem of determining the optimal ''Model Grain'' or spatial resolution (scale) for landscape modeling in the Ev erglades. Selecting an appropriate scale for landscape modeling is a c ritical task that is necessary before using spatial data for model dev elopment. How the landscape is viewed in a simulation model is depende nt on the scale (cell size) in which it is created. Given that differe nt processes usually have different rates of fluctuations (frequencies ), the question of selection of an appropriate modeling scale is a dif ficult one and most relevant to developing spatial ecosystem models. T he question of choosing the appropriate scale for modeling is addresse d using the landscape indices (e.g., cover fraction, diversity index, fractal dimension, and transition probabilities) recently developed fo r quantifying overall characteristics of spatial patterns. A vegetatio n map of an Everglades impoundment area developed from SPOT satellite data was used in the analyses. The data from this original 20 x 20 m d ata set was spatially aggregated to a 40 x 40 m resolution and increme nted by 40 meters on up to 1000 x 1000 m (i.e., 40, 80, 120, 160... 10 00) scale. The primary focus was on the loss of information and the va riation of spatial indices as a function of broadening ''Model Grain'' or scale. Cover fraction and diversity indices with broadening scale indicate important features, such as tree islands and brush mixture co mmunities in the landscape, nearly disappear at or beyond the 700 m sc ale. The fractal analyses indicate that the area perimeter relationshi p changes quite rapidly after about 100 m scale. These results and oth ers reported in the paper should be useful for setting appropriate obj ectives and expectations for Everglades landscape models built to vary ing spatial scales.