ISO Cluster classifier by ArcGIS for unsupervised classification of the Landsat TM image of Reykjavík

The paper presents the use of Landsat TM image processed by ArcGIS Spatial Analyst Tool for environmental mapping southwestern Iceland, region Reykjavik. Iceland is one most special Arctic regions with unique flora and landscapes. Its environment presented vulnerable ecosystems highlands where vegetation affected climate, human or geologic factors: overgrazing, volcanism, annual temperature change. Therefore, land cover types in contribute to nature conservation, sustainable development monitoring purposes. This starts review current trends remote sensing, importance imagery general particular, requirements GIS specifically satellite analysis. followed extended methodological workflow supported illustrative print screens technical description data processing ArcGIS. used this research include which was captured using GloVis methodology includes a involving several steps raster ArcGIS: 1) coordinate projecting, 2) panchromatic sharpening, 3) inspection statistics, 4) spectral bands combination, 5) calculations, 6) unsupervised classification, 7) mapping. classification done clustering technique ISO Cluster algorithm Maximum Likelihood Classification. finally results application concludes final remarks on perspectives based ArcGIS.The present landscapes divided into eight distinct classes: bare soils; shrubs smaller trees river valleys, urban areas including green spaces; water areas; forests Reykjanesfólkvangur National reserve; ice-covered areas, glaciers cloudy regions; ravine valleys sparse type vegetation: rowan, alder, heathland, wetland; rocks; 8) mixed areas. discussion machine learning methods opportunities their applications GIS-based analysis Earth Observation ArcGIS, visualization, decision making forestry development.