Case Study: ALLEGRO
Advanced Land-cover, Land-use Extraction for Geospatial Region Operations (ALLEGRO) is a software application that enables inexperienced field operators to create consistent, high-quality land cover/land-use (LCLU) products from medium resolution, large footprint, multi-spectral satellite imagery such as LANDSAT and ASTER. The ALLEGRO software is an intuitive, workflow-based application that integrates a number of unique technologies with optimized workflow methods for increased quality of the LCLU results and efficiency of production. These advanced technologies were developed to help overcome several of the major limiting factors associated with LCLU classification such as mixed pixels, comparable spectra, data variance, and training set errors. Statistical Prediction of Bands is a data fusion technique that combines high-resolution panchromatic data with lower resolution multi-spectral data to improve the image resolution while retaining its spectral qualities. Spectral-spatial bootstrapping is a semi-automated workflow methodology designed to make is easy for inexperienced users to define high-quality training sets in conjunction with high spatial resolution inputs such as IKONOS or QuickBird imagery.