Digitally processed Landsat MSS data and GIS technology were applied to work out a Land Suitability classification for reforestation activities in southern Sri Lanka. The methodology was designed to solve three main problems, i, e., 1) Where dose forest cover exist? 2) Where are the regions suitable for reforestation? and 3) Where are the regions impossible for reforestation?. About 17% of the total land area was classified as practically considerable for reforestation directed to the land suitability classification. More than 80% of this area was categorized as highly suitable or suitable lands for reforestation. If this reforestation program is implemented, the total forest area will increase from 12% to 25% in the study area.
The accuracy of the conventional system correction of AVHRR imagery using ephemeris data is not sufficient for some applications which demand high accuracy in geometry. The correction using GCPs can meet such demands. But it sometimes occurs that the adequate number of GCPs can not be acquired because of clouds, etc.. This paper introduces the new method of geometric correction of AVHRR imagery which utilizes coliniality condition as well as ephemeris data. The method is adaptable, however many number of GCPs are obtained.
An extension is given for general closed surfaces based on the earlier reconstruction method for a closed convex surface. It fits an object surface with a polyhedral model using outlines taken from multiple projections of the object. Initially, the model is defined as a tetrahedron, whose center of gravity is matched to that of the object. Next, it either moves each vertex of the model by calculating the most appropriate shift vector or adds a new vertex to the model. The two procedures are repeated till the number of vertices of polyhedral model reaches a given value. The result of experiments using photographs of an object shows a relative error of projection fitness of around 3%.