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.