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Land Cover Mapping Using Landsat Satellite Image Classification in the Classical Karst - Kras Region
Author(s) -
Žiga Kokalj,
Krištof Oštir
Publication year - 2007
Publication title -
acta carsologica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.362
H-Index - 24
eISSN - 1580-2612
pISSN - 0583-6050
DOI - 10.3986/ac.v36i3.177
Subject(s) - land cover , orthophoto , karst , remote sensing , digital elevation model , thematic map , computer science , thematic mapper , satellite , classifier (uml) , satellite imagery , land use , cartography , data mining , geography , artificial intelligence , civil engineering , archaeology , aerospace engineering , engineering
Such a diverse and sensitive eco-region as Karst needs to be managed with special attention and consideration of its natural and cultural resources. Land cover is an important indicator, which enables the analysis of their condition and development monitoring. Advanced satellite images classification represents an accurate and cost-effective alternative to the classical techniques of land cover mapping. The methods used to produce a reliable land cover map are presented in this paper. The complexity of the area requires a combination of various data such as Landsat satellite images, digital elevation model, digital orthophotos as well as existing topographic and thematic maps. The maximum likelihood algorithm was used as the main classifier and the accuracy of results was further improved by fuzzy classification, altitude and inclination filtering and auxiliary data integration.

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