The purpose in acquiring ground truth is ultimately to aid in calibrating and interpreting remotely recorded surveys by checking realities within the scene. Since human interpreters normally experience Earth as ground dwellers, their view of the world from a horizontal or low-angle panorama is the customary frame of reference. In fact, the remote sensing specialist and the novice should retain a surface-based perspective during all phases of data collection, analysis, and applications, because they will implement most interpretations and decisions dealing with natural resources and land use at the ground level. Among many ground-oriented data sources are field observations, in situ spectral measurements, aerial reconnaissance and photography, descriptive reports and inventory tallies, and maps. Assume you are working on a Landsat scene that is close enough for you to actually go into the field to examine firsthand the features contained within it.
Field work is expensive, and often inconvenient.
Yet some kinds of data are needed in near real time. Mention three in this category from the above list. This simply means gathering the data under different conditions, such as the use of several sensors simultaneously and repeat coverage over time. Probably the most common reasons for conducting field activities are to select training sites prior to supervised classification or to identify key classes after unsupervised classification. The best way to collect field data, if feasible, is simply to spend a few days in the field, examining the terrain for the classification.