Measuring Spatial and Vertical Heterogeneity of Grasslands Using Remote Sensing Techniques

Abstract

Grassland heterogeneity, defined by its components of spatial pattern, vertical structure, and species composition, is one of the most important indicators of prairie habitat. Maintaining grassland under conservation without disturbance may result in homogeneity at multiple spatial scales that could reduce wildlife diversity as a consequence. Therefore, monitoring grassland conditions that contribute to diversity can be critical for wildlife habitat and ecological integrity. Remote sensing, with multi-spatial, multi-spectral, and multi-temporal resolutions plus newly developed analytical techniques, provides a potential tool for measuring grassland heterogeneity under different management regimes quickly, efficiently, and at low cost. The objectives of this study were 1) to evaluate the heterogeneity of grassland under grazing and conservation management practices spatially and vertically, and 2) to investigate the feasibility of using remotely sensed data to measure grassland heterogeneity. The study area was Grasslands National Park of Canada and its surrounding pastures. Field data were collected in the 1999 growing season by measuring the grassland vertical profile in a fixed spatial array. A Landsat Enhanced Thematic Mapper Plus (ETM+) image was acquired for the same year. A grey level co-occurrence matrix (GLCM) texture analysis was applied to the Landsat ETM+ imagery to compare the grasslands under grazing and those under the conservation practice. The results derived from field measurement show that the variation of vertical structures of grasslands differ significantly under grazing and conservation management regimes. Optical remote sensing data could detect the spatial variation of grasslands under these two management practices. Texture analysis is effective at 15 m resolution, which confirmed other studies that grassland heterogeneity is at about 15 meter.

Keywords: Digital image, grassland, remote sensing, spatial heterogeneity, species diversity, vertical structure