Per-field classification: an example using SPOT HRV imagery

Abstract

The classification of land cover on remotely sensed imagery is usually undertaken in a per-pixel format within an image file or in a per-field format within a non-image file. The latter is more accurate but does not produce an image output and is not readily input to a vector-based geographical information system. We propose setting the pixels in each field to a representative statistic for that field and then using a per-pixel classifier to perform a per-field classification in an image file. This procedure was evaluated using SPOT high resolution visible (HRV) imagery. The highest classification accuracy of 62.1 per cent (12 class) was achieved using measures of prior probabilities and image texture within the proposed per-field format.