Automated vegetation mapping using digital orthophotography

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We used near-infrared digital orthophotography and three collateral data sets to model ecological communities on Block Island, Rhode Island. Aerial photography of the island was taken on 19 May 1992 at a scale of 1:40,000. The photography was scanned and processed to remove distortions from terrain, aircraft tilt, and optical aberration. The resulting digital orthophotograph was comprised of three spectral bands representing the red, green, and blue colors of the scanned photography and had a pixel dimension of 1.27 m. Three textural variables were developed by calculating the standard deviation within a 10-m radius of every pixel for each of the three spectral bands in the image. The terrain model that was used to create the orthophoto was also used to derive slope and aspect for each pixel. Soil survey data were used to map the distribution of soil drainage classes to distinguish wetland from upland vegetation. We used linear discriminant analysis to develop a model to distinguish 11 vegetation and cover classes on the island. The full model consisted of nine independent variables derived from the orthophoto, the textural indices, terrain metrics, and soils. Classification accuracies ranged from 60 to 80 percent for an independent validation data set. The variable DRAINAGE CLASS dominated the model and explained the most variation in vegetation and cover class.

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Photogrammetric Engineering and Remote Sensing





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