The Moderate Resolution Imaging Spectroradiometer (MODIS) has been used in several remote sensing studies, including land, ocean, and atmospheric applications. The advantages of this sensor are its high spectral resolution, with 36 spectral bands; its high revisiting frequency; and its public domain availability. The first seven bands of MODIS are in the visible, near-infrared, and mid-infrared spectral regions of the electromagnetic spectrum which are sensitive to spectral changes due to deforestation, burned areas, and vegetation regrowth, among other land-use changes, making near-real-time forest monitoring a suitable application. However, the different spatial resolution of the spectral bands placed in these spectral regions imposes challenges to combine them in forest monitoring applications. In this paper, we present an algorithm based on geostatistics to downscale five 500-m MODIS pixel bands to match two 250-m pixel bands. We also discuss the advantages and limitations of this method in relation to existing downscaling algorithms. Our proposed method merges the data to the best spatial resolution and better retains the spectral information of the original data.
|Journal||IEEE Transactions on Geoscience and Remote Sensing|
|Publication status||Published - 2013|
- wavelet decomposition