chapter  20
22 Pages

Remote Sensing of Urban Biophysical Environments

Urban environmental problems have become unprecedentedly signicant in the twenty-rst century. This is not a simple consequence of ever-increasing urban population and land, but also because urbanization is one of the most profound examples of human modi-cation of the Earth. Urbanization may have an impact on local energy, water and carbon exchanges, climate, habitat, and biodiversity. Depending on the size of the area affected, the impacts may be on a local, regional, or global scale. Continued urbanization and the associated environmental impacts are receiving great attention in the remote sensing community and beyond. It has been suggested that urban environment should be dened as a “new science” to be focused on U.S. satellite missions such as Hyperion in the near future. Driven by societal needs and improved spatial, spectral, and geometric (e.g., light detection and ranging [LiDAR]) resolutions in sensor technology and image processing algorithms, in recent years we have witnessed a great increase in the number of publications, special issues, and books on urban remote sensing. The Decadal Survey (National Research Council 2007) further suggests improving the temporal resolution of satellites

CONTENTS

20.1 Introduction ........................................................................................................................503 20.2 Remote Sensing of Urban Landscapes............................................................................504 20.3 Remote Sensing of Impervious Surfaces ........................................................................506 20.4 Remote Sensing of Urban Climate and Air Quality .....................................................508 20.5 Remote Sensing of Urban Vegetation .............................................................................509 20.6 Improved Sensors and Algorithms Integral to Urban Remote Sensing .................... 510

20.6.1 Ultra High-Resolution Satellite Imagery and LiDAR Data .............................. 510 20.6.2 Enhanced and New Image Analysis Algorithms ............................................. 511

20.6.2.1 Knowledge-Based Expert Systems ....................................................... 511 20.6.2.2 Articial Neural Network ..................................................................... 512 20.6.2.3 Object-Based Image Analysis ................................................................ 513 20.6.2.4 Data Mining ............................................................................................. 513 20.6.2.5 Data Fusion .............................................................................................. 514 20.6.2.6 Hyperspectral Imaging .......................................................................... 515

20.7 Conclusions ......................................................................................................................... 515 References ..................................................................................................................................... 516

capable of urban imaging. Therefore, we may well be entering an era of “high-denition” urban remote sensing. This chapter reviews recent research progresses in several aspects of urban remote sensing, including urban landscape, impervious surface, urban air quality, and vegetation. The chapter ends with the author’s prospects on future developments and emerging trends in urban remote sensing.