Potential of Manual and Automatic Feature Extraction from High Resolution Space Images in Mountainous Urban Areas

Recent developments of optical space sensors enable us to use high resolution space images for topographic mapping. Geometric and radiometric resolution are the major factors for identification of objects in space images. Panchromatic and pan-sharpened images of IKONOS and QuickBird, and panchromatic OrbView-3 image are investigated in this study. The feature extraction is performed by manual and automatic methods, supported by eCognition. The results are verified against the 1:5000 topographic map. The test site is located in Zonguldak city centre, a mountainous urban area in Western Black Sea region of Turkey. The completeness of manual extraction reaches up to ~70% for buildings, ~100% for roads and ~80% for the coast line. The success of automatic extraction is limited compared to the manual extraction. Only the information content of a 1:10000 topographic map could be derived from these images. The geometric-, radiometricand spectral-resolution, effective GSD, object contrast, atmospheric condition, imaging time, sun elevation and topographic condition of imaged area are the important parameters for the object identification.