TOR VERGATA UNIVERSITY UNSUPERVISED CLASSIFICATION ...

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4 The retrieval of information in urban areas: a challenging issue It is easy to understand that they are one of the most complex and intricate environments and they are also among the most rapidly expanding and changing elements of the landscape (Fig. 1). Figure 1:An urban areas in Colorado: it is possible to see changes in land cover from 1992, to 1996 and 2002 (from [9], courtesy of Digital Globe) These preliminary considerations could explain the necessity to monitor urban areas with a certain accuracy and a high frequency. Reliable data in populated areas is essential for urban planning: knowledge of changes in either natural resources or man-made structures is a valuable source of information for decision-making processes [1]. Conversely, lack of information contributes to problem such as ineffective urban development programs and activities, unplanned investment projects, poor functioning land markets, and disregard of the environmental impact of developments [2].
Introduction 5 Since the late ‗70s, with the first Landsat missions, satellite remote sensing is increasingly being used as a timely and cost-effective source of information in a urban planning [3], [4]. During the last two decades, significant progress has been made in developing and launching satellites with instruments, in both optical/infrared and microwave regions of spectra, well suited for Earth Observation with an increasingly finer spatial, spectral and temporal resolution [5]. With the recent availability of commercial Very High Resolution (VHR) remote sensing multispectral imagery from sensors such as IKONOS and QuickBird, it is possible to identify small-scale features such as individual roads and buildings in the urban environment (roessner et. al, 2001) and have a specific potential for more detailed and accurate mapping of urban areas [6], [7]. Imagery from these sensors is an important source of timely data, which can be used for the creation and/or updating of GIS vector layer [8]. However, VHR images analysis is one of the most challenging areas for the remote sensing community due to its high spatial and spectral diversity. From the physical composition point of view, several different materials can be used for the same built-up element (for example, building roofs can be made of clay tiles, metal, concrete, glass, plastic). On the other hand, the same material can be used for different built-up elements (for example, concrete can be found in paved roads or building roofs [9]. Fig. 2 shows how the same surface (two types of roads) can be made from different material and two different surfaces (a road and a building) can be made with the same material (concrete). Misclassification occur between buildings and streets, which are caused by spectral similarities between materials covering these surfaces and the influence of shadow. A different spectral behavior could be explained also from the effect of the atmosphere, which operates at different wavelengths.
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174 Bibliography [10] P. M. Teillet
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176 Bibliography [102] Geoeye, Ikon
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178 Bibliography [122] P. Dreyer,
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180 Bibliography [141] P. Gong, D.
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182 Bibliography [160] B. Guindon,
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184 Bibliography [307] F. Melgadi a
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188 Bibliography [424] C. Elachi,
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190 Bibliography [709] A. R. Gilles
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196 CV, conferences and publication
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