Monitoring the Urban Environment from Space

Monitoring spatiotemporal changes in large urban agglomorations will become increasingly important as the number and proportion of urban residents continue to increase. The synoptic view of urban landcover provided by satellite and airborne sensors is an important complement to in situ measurements of physical, environmental and socioeconomic variables in urban settings. The 10 to 80 m spatial resolution of most operational satellites has impeded the use of remotely sensed imagery for studies of urban infrastructure but this resolution is sufficient for measurement of some important environmental parameters that would be logistically difficult or prohibitively expensive to measure directly. Intra-urban variations in vegetation abundance influence environmental conditions and mass/energy fluxes by selective reflection and absorbtion of solar radiation and by modulation of evapotranspiration. Operational satellites such as Landsat provide the ability to monitor spatiotemporal dynamics of urban vegetation and thermal emission simultaneously on seasonal to interannual time scales to better understand their relationship to the urban environment. Monitoring of spatiotemporal variations of urban vegetation abundance may also allow the effect of the urban environment on vegetation phenology to be determined. In this study, we discuss methodology for measurement of urban vegetation and compare vegetation distributions in the New York and Guangzhou metropolitan areas using Landsat TM imagery. A systematic analysis of the spatiotemporal dynamics of vegetation in the world's major evolving urban centers would facilitate comparative studies of urban environment and its role in public health and energy consumption as well as constraining the role of the urban center in the dynamics of larger metro-agro-plex system Importance of Urban Vegetation One of the primary challenges to understanding the dynamics of the Earth system is an accurate assessment of the relationships between human population and the other components of the system. Recent estimates indicate that over 45% of the world's human population now lives in urban areas with over 60% projected by 2030 (United Nations, 1997). The global rate of urbanization is expected to continue to accelerate in the near future with the emergence of large urban agglomerations in developing countries (Berry, 1990; United Nations, 1980). Even if developing countries follow the course of post-industrial urban dispersion to suburbs, the continuing localization of populations from rural to urban/suburban connurbations will result in increasing numbers of people living in built environments. As the size and number of urban agglomerations increases, so does the relative importance of the urban environment to the global population. Urban areas exert influences on the Earth system far disproportionate to their geographic extent and require special consideration in the context of a Digital Earth (Miller and Small, this volume). Monitoring spatio-temporal changes in large urban/suburban areas will therefore become increasingly important as the number and proportion of urban residents continue to increase. The spatiotemporal distribution of vegetation is a fundamental component of the urban/suburban environment. Vegetation influences urban environmental conditions and energy fluxes by selective reflection and absorption of solar radiation (e.g. Goward et al, 1985; Roth et al, 1989; Gallo et al, 1993) and by modulation of evapotranspiration (e.g. Price, 1990; Carlson et al, 1994; Gillies et al, 1997; Owen et al, 1998). The presence and abundance of vegetation in urban areas has long been recognised as a strong influence on energy demand and development of the urban heat island (e.g. Harrington, 1977; Oke, 1979; Huang et. al., 1987). Urban vegetation abundance may also influence air quality and human health (Wagrowski and Hites, 1997) because trees provide abundant surface area for sequestration of particulate matter and ozone. Urban vegetation also experiences both short and long term phenological changes and may itself be sensitive to subtle changes in environmental conditions. Changes in the built component of the urban environment are generally documented at various levels of detail but phenological changes in urban vegetation are not under direct human control and are not generally monitored over large areas. The synoptic view of the urban mosaic provided by satellite and airborne sensors is an important complement to in situ measurements of physical, environmental and socioeconomic variables in urban settings. Forster (1983) provides a thorough summary of the evolution of urban remote sensing and introduces a methodology with which some socioeconomic parameters may be predicted using reflectance based estimates of land cover classes. Compared to agricultural areas and sparsely populated regions, however, application of remotely sensed observations to studies of the urban environment has been rather limited. In part, this is because accurate identification of most built components of the urban environment requires finer spatial resolution than is offered by operational satellites such as Landsat or SPOT. The 30 to 50 m spatial resolution of the Landsat TM sensor (Markham, 1985; Wilson, 1988) is comparable to the characteristic scale of urban land cover (Welch, 1982, Woodcock & Strahler, 1987) and is generally too coarse for identification of individual structures. While this resolution has limited Landsat's use for studies of the built urban environment, it may be sufficient to detect significant spatial and temporal variations in urban vegetation and surface temperature. The objective of this paper is to present results of an analysis of urban vegetation distribution in New York City and to discuss implications for environmental monitoring of evolving urban areas. Estimation of Urban Vegetation with Landsat Imagery Urban areas are generally recognized in remotely sensed imagery by their geometric and textural characteristics. Spectral characteristics of urban landcover are less diagnostic than those of the rural periphery. Urban areas are generally characterized by