Remotely Sensed Cities

About this book

Remotely Sensed Cities examines how the world's urban areas can be located, measured and analysed using information from the latest airborne and satellite remote sensors, including breakthroughs in the use of LIDAR and IKONOS data for precision mapping, and DMSP OLS night-time imagery for establishing global distributions of population and economic activity. Emphasis is also given to techniques on urban feature extraction using wavelet transforms, and graph-based structural pattern recognition; along with population mapping using zone-based dasymetric models, pixel-based entropy maximisation models and Bayesian classifications. In addition, novel applications include links with geodemographics, crime prevention, and the importance of monitoring urban heat islands of cities in the developing world. The urban emphasis of this book helps to redress the balance with many publications on environmental remote sensing. Only relatively recently has remote sensing assumed equal importance in the monitoring of the world's centres of population. Dynamic changes in global urban growth and economic activity, especially in the developing world are rapidly attaining prominence in applications requiring precise delineation of urban features, and of changes and behaviour. The book is designed for upper-level undergraduates and graduate students, along with research scientists in geo-mapping disciplines, environmental issues and the social sciences. Mesev; Victor Florida State University, Tallahassee, USA

Contents

Remotely-sensed cities - an introduction. Part 1 High-spatial-resolution data: comparison of IKONOS and SPOT HRV imagery for classifying cities; resolution convergence; determining urban land use through and analysis of the spatial composition of buildings identified in LIDAR and multi-spectral image data; the use of wavelets for feature extraction of cities in satellite images. Part 2 Cities by day: refining methods for dasymetric population mapping using satellite remote sensing; zone-based estimation of population and housing from satellite-generated land use maps; population estimation at the pixel level; urban land use uncertainty; population mapping geodemographics and satellite imagery; GIS and remote sensing in urban heat islands in the Third World. Part 3 Cities by night: LandScan - a global population database for estimating populations at risk; overview of DMSP OLS and scope of applications; estimation non-population activities from night-time satellite imagery; does night-time lighting deter crime? - an analysis of remotely-sensed imagery and crime data.

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Biography

Victor Mesev is Lecturer of Geography at the University of Ulster where he teaches on Ireland's first Master's course on GIS and remote sensing. Previously, he spent seven years at the University of Bristol conducting ESRC and NERC funded research into the integration of GIS and remote sensing, and developments in urban fractal models. He is on the editorial board of 'Computers, Environment and Urban Systems'.