A comparison of remote sensing techniques for Minnesota wetlands classification

A wetland classification study in a typically complex 650 sq km test site in east central Minnesota compared the time, cost and accuracy of manually interpreted 1:24,000 scale color infrared aerial photographs with digital analysis of Landsat data. The comparison was between the same general wetland and non-wetland classes; accuracy of both systems was evaluated with intensive ground verification. For the same general classes, the overall mapping accuracy was 96 percent for the aerial photo interpretation and 71 percent for Landsat double-date classification. Results with maximum likelihood and SECHO classifiers were the same, 71 percent, while mapping accuracy with a layered classifier was only 66 percent. Compared to a general geometric correction and a single-date data set, geographic position and classification accuracy improved when a precision geometric correction and a double-date data set were used. Landsat digital analysis was faster, 24 vs. 90 days, but photointerpretation was more economical at $0.15/hectare (including all costs of procurement, processing and analysis), compared with Landsat costs of $0.35/hectare (not including costs of data procurement, processing prior to delivery to user and related overhead).