Monitoring the Amazon with Different Spatial and Temporal Resolution

When monitoring deforestation, frequent images with an optimal spatial resolution are required. But in reality either images with low spatial resolution and a high revisit frequency or high spatial resolution images with a low revisit time are available. Combining different spatial and temporal resolutions could solve this problem. The study site in the Colombian Amazon contains small fields within the forest. The input data consisted of one high spatial resolution AIRSAR image and a time series of nine ERS-1 images of medium spatial resolution, and their supervised classifications. The AIRSAR image was upscaled with stepwise upscaling based on interim results and by direct upscaling from the same basis to different levels of spatial resolution. The comparison showed that the proportion of land cover classes did not change substantially in either of the two upscaling approaches, while the number and size of the patches showed a clear decrease with continuing upscaling. The direct upscaling approach provided best results. Furthermore, the conformity of the upscaled AIRSAR land cover map and the ERS-1 land cover maps was determined. For the study area with its particular land cover pattern, the effect of the spatial resolution on classification was not as important as expected. The fact that AIRSAR has three fully polarimetric bands, while ERS-1 has only one band and one polarization was a more important cause for differences between the land cover maps than the differences in spatial resolution.