Abstract

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.

摘要

本文重点介绍使用遥感多光谱图像进行土地覆盖分类，景观设计师可能对这一过程知之甚少，但却为他们用作设计基础的许多地图奠定了基础。分类的相对随意性，以及在对多光谱图像进行分类以创建土地覆盖图时发生的同质化，在区分土地和水域时尤其重要。然而，“寻找”水是土地覆盖分类的关键步骤。美国新泽西州斯通港湿地研究所周围的盐沼被用作将卫星图像与现场测量相结合的多光谱分析的案例研究。然而，