Landscape metrics are algorithms that quantify the spatial structure of patterns – primarily composition and configuration - within a geographic area. The term "landscape metrics" has historically referred to indices for categorical land cover maps, but with emerging datasets, tools, and software programs, the field is growing to include other types of landscape pattern analyses such as graph-based metrics, surface metrics, and three-dimensional metrics. The choice of which metrics to use requires careful consideration by the analyst, taking into account the data and application. Selecting the best metric for the problem at hand is not a trivial task given the large numbers of metrics that have been developed and software programs to implement them.
The interpretation of images that are created according to electromagnetic energy reflected from or emitted by earth surface features or atmosphere is a common practice to obtain useful information from raw image data. Images acquired by a device that is not in contact with objects and features are generally referred to as remotely sensed data, and the photo interpretation is generally carried out to extract meaningful information from image data for any subsequent uses. Specifically, this chapter covers elements of image interpretation, photo interpretation key, scale of an aerial photograph, heights, distances, and areas of objects in a photo, and land use land cover classification and mapping.