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Detecting grassland spatial variation by a wavelet approach

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Abstract:

Insight into the spatial variation of an ecosystem can provide better understanding of ecological processes and patterns in different scales. Detecting these multiple scales of spatial variation in grassland landscapes is valuable for determining management options, designing proper sampling regimes, and selecting suitable resolutions of remote sensing products. The objective of this study is to examine how environmental factors affect spatial variation of biophysical properties in mixed grassland ecosystems. Field leaf area index (LAI), soil moisture, and topographical parameters (relative elevation, upslope length, and a wetness index) were obtained in three parallel transects of a grassland ecosystem in Saskatchewan, Canada in 2004. One 20-m resolution SPOT 4 (HRVIR) image was acquired at the same period of the growing season but in the following year. Normalized difference vegetation index (NDVI) was calculated from the satellite image of the centre 381-m transect and two extensive 2560-m perpendicular transects. A wavelet approach was used to identify the scales of variations. Statistical results showed that LAI is significantly correlated to the wetness index (r2 = 0.37) and soil moisture (r2 = 0.43). The wetness index is better than relative elevation and upslope length in demonstrating the effect of topography on grassland vegetation. The variation of soil moisture is significant at two small scales of about 20 m and 40 m, and that of the wetness index is at the large scale of 120 m. The variation of grassland LAI is significant at three scales (20 m, 40 m, and 120 m), which indicates that the spatial variation of LAI might be controlled by both topography and soil moisture, though the 120 m is the dominant scale of variation in LAI. NDVI significantly correlated with grassland LAI along the centre transect. The effect of topography on grassland LAI is also proven by the significant relationships between NDVI and the wetness index. The wavelet analysis identifies the variation of two extensive transects at the scale of about 120 m, which is similar to the dominant variation scale of grassland LAI. These results confirmed that the effect of topography on spatial variation can be identified from the appropriate satellite image. This study suggests that the spatial scales of soil and topographic data aid in the selection of appropriate satellite image resolution for monitoring and managing ecosystems.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160600794621

Affiliations: 1: Department of Geography, University of Saskatchewan, 9 Campus Dr., Saskatoon, Saskatchewan S7N 5A5, Canada 2: Department of Soil Science, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada

Publication date: January 1, 2007

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