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Based on the fractal theory, this study establishes a Continuous Spatial Scaling Model (CSSM) of the Normalized Difference Vegetation Index (NDVI) to address issues arising with spatial up-scaling in quantitative remote sensing. This model is able to quantitatively describe transformation relationships of the NDVI on continuous scales. Then the following experiments are accomplished: (1) the validation of ETM+ NDVI imagery is implemented based on the GEOEYE-1 image and its NDVI CSSM, and the following conclusion is obtained: because of bad stripes in the ETM+ image and the limited effect of destriping, the ETM+ NDVI image had a rather large error, and the error for the entire experimental imagery is about 25%, so the ETM+ NDVI product is not suitable for direct practical application; (2) Shatian Byland (Beihai City, China) is taken as the experimental area, and four images (two ETM+ images with wider and smaller coverage, respectively, a GEOEYE-1 image, and an HJ-1B CCD1 image) are studied. The most suitable scale levels are computed and compared for the four images, and a better understanding is obtained of the impact of various image characteristics (area of coverage, spatial resolution, and imaging quality) on determining the scale level for the NDVI CSSM.

The Application of Continuous Spatial Scaling Model of NDVI in Validation and Its Sensibility Analysis to Various Image Characteristics