Abstract: Adequate imagery for automated mapping of large areas became available with the successful launch of the 30-meter 7-band thematic mapper (TM) on Landsat 4 in 1982. Yet an adequate approach to automated line-of-communication (LOC) extraction continues to elude the remote sensing community. Perhaps the single biggest complicating factor is the inherently subpixel nature of the problem; almost all LOCs are narrower than current commercial sensor resolutions. Other complications include: spatial and temporal variability of LOC surface spectra, proximity to and abundance of spectrally similar materials, and atmospheric effects. We describe progress towards the detection and identification of LOCs using a technique that simultaneously extracts both spatial and spectral information. The approach currently uses a linear mixture model for simultaneously decomposing the image into fractional compositions and corresponding spectra using physical constraints. The algorithm differs from other approaches in that no traditional preprocessing or prior spatial or spectral information is required to extract the LOCs and their spectra. The algorithm has been successfully applied to TM and M-7 data. Results are presented. !11
展开▼
