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In coming decades, the rapid increase of large cities in the developing world and the transformation of urban landscapes in the developed world will be among the greatest challenges to human welfare and a viable global environment. Although cities occupy only 5% of the Earth’s terrestrial surface, they are home to almost half the global population, who consume 75% of the world’s natural resources and generate an equivalent proportion of pollution and waste. The United Nations estimates that virtually all net population growth over the next 30 years will occur in cities, doubling their population. This anticipated population growth will transform urban landscapes, create undreamed-of challenges and opportunities for political and social institutions, and require an unprecedented investment in infrastructure.

The Atlantic Forest is the most devastated Brazilian biome. This forest initially occupied the coastal region of the country from Ceará to Rio Grande do Sul and was approximately 1,000,000 km in size. Now the forest is limited to areas distributed across several states, and occupies approximately 91,000 km. This level of devastation can be explained by the economic value of forest species, as well as by intense human occupation: approximately 70% of the Brazilian population lives in the region, creating all kinds of anthropic pressures (Thomas et al. 1998, Sips 1999).

Urban remote sensing has long been a niche aspect of modern remote sensing. Aerial photo interpretation, based on national aerial photo surveys, is an established method in urban planning and in the context of urban ecological applications. Thermal remote sensing also has a long tradition in the urban context. Many other remote sensing approaches have become established in major fields of research, but not in urban remote sensing.

The urban environment is strongly influenced by the physical properties of the urban mosaic across a wide range of spatial and temporal scales. The presence or absence of spatial scaling behavior in these physical properties has implications for the parameterization of physical process models that incorporate land surface mass and energy fluxes. The performance of these models is dependent on the accuracy and resolution of the land surface inputs that drive them. The spatial scaling behavior of land surface properties at fine (1–10 m) scales determines the aggregate properties at moderate (< 100 m) and meso (> 100 m) scales. Multiscale land surface properties like patch size and density could potentially be mapped at meter scales using the current generation of high resolution sensors. The results could then be used to scale up moderate resolution land cover maps to regional scales. In spite of its importance to physical and ecological processes, relatively little quantitative analysis has been done on the spatial scaling properties of urban land cover.

For urban planning and management, it is essential that detailed and up-to-date information about the urban ecosystem, with its high level of pattern heterogeneity, is available. In urban areas the steadily increasing land requirements for housing, new areas zoned for economic activities, and new provision of infrastructure, all lead to a reduction of green and open spaces. Owing to their high dynamism, such changes call for the use of methods which allow not only the updating of the planning basis, but also the recording of the consequences (Spitzer 1998). Remote sensing data can provide essential information that is both inexpensive and up-to-date. Formerly, this was only possible with high-cost airborne data. Today, high-resolution satellite data such as IKONOS, with more spectral information and 1–4 m spatial resolution, as well as alternative classification methods based on object-oriented analyses, plays an important role in urban studies.

Over the last several decades, scientists have investigated urban influences on atmospheric conditions (Oke 1987). Much of this work has been conducted using historical climate records of urban and rural sites; doing spatial sampling in and around a given urban area with mobile transects and at instrumented tower sites; and using satellite and airborne remote-sensing technology. In the 21 century, more and more people are moving to cities. Soon, cities will contain the majority of the Earth’s population. It is thus critical to maintain urban environments in sustainable ways that ensure acceptable levels of health, welfare, and safety of citizens. Scientists from many disciplines have converged upon several urban themes at the inter-disciplinary juncture of climate, meteorology, information technology, space technology, architecture, planning, and engineering of the built environment, in order to understand the interactions between a city and its overlying atmosphere. One major facet of this convergence could broadly be labeled “urban climatology.” This area of research has advanced knowledge at the nexus of climate and urbanization over the last several decades, but there are many challenges yet to be met, with the ultimate goal of applying scientific understanding to maintain sustainable urban environments and quality of life (e.g., Arnfield 2003, review of the field of urban climate).

The Phoenix metropolitan agglomeration (Fig. 7.1) is one of the fastest-growing conurbations in the United States, and is the focus of the Central Arizona-Phoenix Long-Term Ecological Research Project (CAP LTER) (Grimm et al. 2000, Grimm and Redman 2004). This project has been the locus of significant remote sensing investigation and characterization of the Phoenix urban and peri-urban areas (Stefanov 2002), combined with ground truthing and allied studies (Hope et al. 2003). The information derived from these and other studies is increasingly being used by local governments and regional planners (GP2100 2003). As an example, the City of Scottsdale, Arizona has used high-resolution, airborne, multispectral data to assess impervious and pervious land-cover percentages for surface water runoff studies. This use of remotely sensed information, rather than traditional ground-based surveys, produced estimated cost savings of eight to fifteen million dollars for the city (W. Erickson 1999). Construction of an advanced visualization and modeling environment (a “decision theater”) that integrates remotely sensed and other geospatial data for the Phoenix metropolitan region was completed in 2005 at Arizona State University (J. Fink 2005). Use of such an advanced system enables near real-time modeling of the impact of planning and development decisions. Remotely sensed data acquired at a variety of spatial, spectral, and temporal resolutions provides the basic biophysical information necessary to initialize models of urban resilience and sustainability.

India no longer lives in villages, and rapid urban development has increased the size of India’s urban population. During the last fifty years the population of India has grown two-and-a-half times, but urban India has grown nearly five times. In 2001, 306.9 million Indians (30.5%) were living in nearly 3700 towns and cities spread across the country, compared to 62.4 million (17.3%) who lived in urban areas in 1951. This is an increase of about 390% in the last five decades. The urban population is expected to increase to over 400 million and 533 million by 2011 and 2021, respectively. In 1991 there were 23 metropolitan cities in India; the number increased to 35 in 2001. Among the megacities of the world (those with a population greater than 10 million), Mumbai with 16.37 million, Delhi with 13.78 million, Kolkata with 13.22 million, and Chennai with 6.42 million people figure prominently (Raghavswamy et al. 1996). The high rate of urban population growth is a cause of concern among India’s urban and town planners. The term urbanization once conveyed an image of a city’s radial expansion into its rural surroundings. Urban areas of today are more aptly described as sprawling regions that become interconnected in a dendritic fashion (Carlson and Arthur 2000). The positive aspects of urbanization have often been overshadowed by deterioration in the physical environment and quality of life caused by the widening gaps between supply and demand for essential services and infrastructure.

In accordance with the resolutions of the United Nations Conference on the Environment and Development in Rio de Janeiro in 1992, the state and federal capital of Berlin has made the principle of sustainability a guideline for its further development. This principle, in addition to socially just and economically sustainable development, contains a third component: The development of the environment in a way that ensures the long-term protection of our basis of life.

From space, the rice fields of the Mae Nam Ping basin around Chiang Mai curve like a fetus around the square heart of the old city, nourished by a placenta of forested hills (Plate 10.1). If we zoom in closer to the heart, the square moat, road and ramparts of the old city (Plate 10.2), we can make out the arterial roads streaming out from ancient city gates to feed the growing body marked by the curves of new ring roads (Plate 10.2). The lowland rice farmer’s view is of a society nurtured by, but separate from, wild nature, with the river, Mae Nam, literally the “mother.”