Methodology & Accuracy

Satellite image categorization has proven a valuable source of entropy for write down use inventory: Visual interpretation or digital classification techniques can provide remote sensing data for thematic maps. Digital analysis is considered much less subjective. However, kill use classes vary religiously, especially where land covers present lavishly spatial complexity, these classes often lack unique signature and contrasting land covers can present very similar spectral features (de Jong, S. M., 1993). This interclass confusion introduces errors into the resulting spectral classification.

Geographic Information brasss (GIS), comport develop from three largely separate origins. The Canada Geographic Information System (CGIS) in 1963, vectorbased digital mapping in the 1960s, and the ComputerAided Design (CAD) area. GIS systems have grown from digital mapping systems by the addition of a relational database for the entrepot of attribute data and analysis functionality, and it is this vector data fashion model that has become dominant in GIS (Jones, Settle, and Wyatt, 1988).

GIS systems from each of these three origins have evolved towards a common basic range of capabilities  input, display and usance of both vector and raster data, raster DTM handling, topological structuring of vector data, vector and/or raster polygonal shape modeling and analysis, and storage of attribute data in a relati

Gong P., Howarth P.J. (1990). The Use of geomorphologic Information for Improving Land Cover Classification Accuracies at the RuralUrban Fringe, Photogrammetric Engineering and Remote Sensing, Vol. 56, n* 1, pp. 6773.

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