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Abstract A popular application of remotely sensed data is the estimation of an environmental variable at a point, with its extrapolation over a large area. For such work reliable ground data are required. This paper is divided into two parts; the first part is a review which looks at the considerations that are necessary for the collection of such ground data and finds that the spatial variability of the terrain has a profound effect on sample design. The second part illustrates these considerations by means of a case study in which airborne remotely sensed data are used to map the green-leaf-area index of grassland. It is concluded that even when large sample sizes were employed the error in ground data was greater than the error in remotely sensed data.
Curran et al. (Tue,) studied this question.
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