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This article focuses on the use of remotely sensed multispectral imagery for land cover classification, a process that landscape architects may know little about but that underpins many of the maps that they use as the basis for their designs. The relatively arbitrary nature of classification, and the homogenization that occurs when classifying multispectral imagery to create land cover maps, is especially consequential when distinguishing between land and water. Yet ‘finding’ water is a key step in land cover classification. The salt marshes surrounding the Wetlands Institute in Stone Harbor, New Jersey, USA are used as a case study for multispectral analysis that combines satellite imagery with on-site surveying. However, the implications of the digital survey methods extend beyond any particular site and point to broader questions about the role of image interpretation for understanding how landscapes and environments are changing, especially with growing uncertainty about the rate of climate change.

Behind-the-Scenes: Multispectral imagery and land cover classification