Abstract
Improvement in vegetation cover in the upper reaches of the Minjiang River protects major freshwater sources and constructs ecological barriers in the upstream of Yangtze River located in southwest China. However, the spatially varying relationships between normalized difference vegetation index (NDVI) and topographic factors at multiple scales remain unclear. In this study, the two-dimensional discrete wavelet transform (2D-DWT) and geographically weighted regression (GWR) were combined to build a framework for examining the complex spatial relationships between NDVI and topographic factors at multiple scales. Based on the gridded datasets of NDVI and digital elevation model (DEM) of a small watershed located in the upper reaches of the Minjiang River situated in southwest China, the influence of topographic factors on NDVI variation in each grid and which topographic variables correlated most with the NDVI at each location were analyzed in this study. The grid data were decomposed into smooth and detail components using 2D-DWT. The results revealed that elevation, slope, and aspect exhibited different scale effects on NDVI in different wavelet components. In the smooth components, the spatial correlation of NDVI with elevation, slope, and south-facing index (SFI) of aspect increased with the decomposition scale, whereas topographic factors had different degrees of influence on NDVI. Elevation was found to be the most important topographic factor that determined the spatial distribution of NDVI on both sides of the valley, and SFI exhibited the highest effect on NDVI when elevation was higher than 2500 m. In the detail components, the spatial distribution of the most important topographic factor affecting the NDVI was not evident at a smaller scale, whereas it became obvious at 480 m scale. SFI was found to be more important than elevation and slope at a larger scale. These results will help in understanding the complex relationship between NDVI and topographic factors and determining the appropriate topographic location for ecological restoration.
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