US Long-Term Ecological Research Network
Effects of sensor spatial resolution on landscape structure parameters
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We examined the effects of increasing grain size from 20 m to 1100 m on landscape parameters characterizing spatial structure in the northern Wisconsin lake district. We examined whether structural parameters remain relatively constant over this range and whether aggregation algorithms permit extrapolation within this range. Images from three different satellite sensors were employed in this study: (1) the SPOT multispectral high resolution visible (HRV), (2) the Landsat Thematic Mapper (TM), and (3) the NOAA Advanced Very High Resolution Radiometer (AVHRR). Each scene was classified as patches of water in a matrix of land. Spatial structure was quantified using several landscape parameters: percent water, number of lakes (patches), average lake area and perimeter, fractal dimension, and three measures of texture (homogeneity, contrast, and entropy). Results indicate that most measures were sensitive to changes in grain size. As grain size increased from 20 m using HRV image data to 1100 m (AVHRR), the percent water and the number of lakes decreased while the average lake area, perimeter, the fractal dimension, and contrast increased. The other two texture measures were relatively invariant with grain size. Although examination of texture at various angles of adjacency was performed to investigate features which vary systematically with angle, the angle did not have an important effect on the texture parameter values. An aggregation algorithm was used to simulate additional grain sizes. Grain was increased successively by a factor of two from 20 m (the HRV image) to 1280 m. We then calculated landscape parameter values at each grain size. Extrapolated values closely approximated the actual sensor values. Because the grain size has an important effect on most landscape parameters, the choice of satellite sensor must be appropriate for the research question asked. Interpolation between the grain sizes of different satellite sensors is possible with an approach involving aggregation of pixels.