Karen C. Seto

Classification and change detection using landsat TM data : When and how to correct atmospheric effects?

Abstract The electromagnetic radiation (EMR) signals collected by satellites in the solar spectrum are modified by scattering and absorption by gases and aerosols while traveling through the atmosphere from the Earths surface to the sensor. When and how to correct the atmospheric effects depend on the remote sensing and atmospheric data available, the information desired, and the analytical methods used to extract the information. In many applications involving classification and change detection, atmospheric correction is unnecessary as long as the training data and the data to be classified are in the same relative scale. In other circumstances, corrections are mandatory to put multitemporal data on the same radiometric scale in order to monitor terrestrial surfaces over time. A multitemporal dataset consisting of seven Landsat 5 Thematic Mapper (TM) images from 1988 to 1996 of the Pearl River Delta, Guangdong Province, China was used to compare seven absolute and one relative atmospheric correction algorithms with uncorrected raw data. Based on classification and change detection results, all corrections improved the data analysis. The best overall results are achieved using a new method which adds the effect of Rayleigh scattering to conventional dark object subtraction. Though this method may not lead to accurate surface reflectance, it best minimizes the difference in reflectances within a land cover class through time as measured with the Jeffries–Matusita distance. Contrary to expectations, the more complicated algorithms do not necessarily lead to improved performance of classification and change detection. Simple dark object subtraction, with or without the Rayleigh atmosphere correction, or relative atmospheric correction are recommended for classification and change detection applications.

Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools

Urban land-cover change threatens biodiversity and affects ecosystem productivity through loss of habitat, biomass, and carbon storage. However, despite projections that world urban populations will increase to nearly 5 billion by 2030, little is known about future locations, magnitudes, and rates of urban expansion. Here we develop spatially explicit probabilistic forecasts of global urban land-cover change and explore the direct impacts on biodiversity hotspots and tropical carbon biomass. If current trends in population density continue and all areas with high probabilities of urban expansion undergo change, then by 2030, urban land cover will increase by 1.2 million km2, nearly tripling the global urban land area circa 2000. This increase would result in considerable loss of habitats in key biodiversity hotspots, with the highest rates of forecasted urban growth to take place in regions that were relatively undisturbed by urban development in 2000: the Eastern Afromontane, the Guinean Forests of West Africa, and the Western Ghats and Sri Lanka hotspots. Within the pan-tropics, loss in vegetation biomass from areas with high probability of urban expansion is estimated to be 1.38 PgC (0.05 PgC yr−1), equal to ∼5% of emissions from tropical deforestation and land-use change. Although urbanization is often considered a local issue, the aggregate global impacts of projected urban expansion will require significant policy changes to affect future growth trajectories to minimize global biodiversity and vegetation carbon losses.

A Meta-Analysis of Global Urban Land Expansion

The conversion of Earths land surface to urban uses is one of the most irreversible human impacts on the global biosphere. It drives the loss of farmland, affects local climate, fragments habitats, and threatens biodiversity. Here we present a meta-analysis of 326 studies that have used remotely sensed images to map urban land conversion. We report a worldwide observed increase in urban land area of 58,000 km2 from 1970 to 2000. India, China, and Africa have experienced the highest rates of urban land expansion, and the largest change in total urban extent has occurred in North America. Across all regions and for all three decades, urban land expansion rates are higher than or equal to urban population growth rates, suggesting that urban growth is becoming more expansive than compact. Annual growth in GDP per capita drives approximately half of the observed urban land expansion in China but only moderately affects urban expansion in India and Africa, where urban land expansion is driven more by urban population growth. In high income countries, rates of urban land expansion are slower and increasingly related to GDP growth. However, in North America, population growth contributes more to urban expansion than it does in Europe. Much of the observed variation in urban expansion was not captured by either population, GDP, or other variables in the model. This suggests that contemporary urban expansion is related to a variety of factors difficult to observe comprehensively at the global level, including international capital flows, the informal economy, land use policy, and generalized transport costs. Using the results from the global model, we develop forecasts for new urban land cover using SRES Scenarios. Our results show that by 2030, global urban land cover will increase between 430,000 km2 and 12,568,000 km2, with an estimate of 1,527,000 km2 more likely.

Quantifying Spatiotemporal Patterns of Urban Land-use Change in Four Cities of China with Time Series Landscape Metrics

This paper provides a dynamic inter- and intra-city analysis of spatial and temporal patterns of urban land-use change. It is the first comparative analysis of a system of rapidly developing cities with landscape pattern metrics. Using ten classified Landsat Thematic Mapper images acquired from 1988 to 1999, we quantify the annual rate of urban land-use change for four cities in southern China. The classified images were used to generate annual maps of urban extent, and landscape metrics were calculated and analyzed spatiotemporally across three buffer zones for each city for each year. The study shows that for comprehensive understanding of the shapes and trajectories of urban expansion, a spatiotemporal landscape metrics analysis across buffer zones is an improvement over using only urban growth rates. This type of analysis can also be used to infer underlying social, economic, and political processes that drive the observed urban forms. The results indicate that urban form can be quite malleable over relatively short periods of time. Despite different economic development and policy histories, the four cities exhibit common patterns in their shape, size, and growth rates, suggesting a convergence toward a standard urban form.

Monitoring land-use change in the Pearl River Delta using Landsat TM

The Pearl River Delta in the Peoples Republic of China is experiencing rapid rates of economic growth. Government directives in the late 1970s and early 1980s spurred economic development that has led to widespread land conversion. In this study, we monitor land-use through a nested hierarchy of land-cover. Change vectors of Tasseled Cap brightness, greenness and wetness of Landsat Thematic Mapper (TM) images are combined with the brightness, greenness, wetness values from the initial date of imagery to map four stable classes and five changes classes. Most of the land-use change is conversion from agricultural land to urban areas. Results indicate that urban areas have increased by more than 300% between 1988 and 1996. Field assessments confirm a high overall accuracy of the land-use change map (93.5%) and support the use of change vectors and multidate Landsat TM imagery to monitor land-use change. Results confirm the importance of field-based accuracy assessment to identify problems in a land-use map and to improve area estimates for each class.

Urban land teleconnections and sustainability

This paper introduces urban land teleconnections as a conceptual framework that explicitly links land changes to underlying urbanization dynamics. We illustrate how three key themes that are currently addressed separately in the urban sustainability and land change literatures can lead to incorrect conclusions and misleading results when they are not examined jointly: the traditional system of land classification that is based on discrete categories and reinforces the false idea of a rural–urban dichotomy; the spatial quantification of land change that is based on place-based relationships, ignoring the connections between distant places, especially between urban functions and rural land uses; and the implicit assumptions about path dependency and sequential land changes that underlie current conceptualizations of land transitions. We then examine several environmental “grand challenges” and discuss how urban land teleconnections could help research communities frame scientific inquiries. Finally, we point to existing analytical approaches that can be used to advance development and application of the concept.

Systems integration for global sustainability

Seeking systems-based solutions Without sustainable solutions, the worlds most pressing environmental concerns will continue to persist or worsen. Achieving the goal of sustainability involves so many factors—from economics to ecology—that investigating one or even a handful of variables at a time often overlooks major parts of the problem. Liu et al. review systems-based approaches that are beginning to provide tenable ways to assess sustainability. Further integrating coupled human and natural components of a problem across multiple dimensions, including how one solution can create unintended consequences elsewhere, is essential for developing effective policies that seek global sustainability. Science, this issue 10.1126/science.1258832 BACKGROUND Many key global sustainability challenges are closely intertwined (examples are provided in the figure). These challenges include air pollution, biodiversity loss, climate change, energy and food security, disease spread, species invasion, and water shortages and pollution. They are interconnected across three dimensions (organizational levels, space, and time) but are often separately studied and managed. Systems integration—holistic approaches to integrating various components of coupled human and natural systems (for example, social-ecological systems and human-environment systems) across all dimensions—is necessary to address complex interconnections and identify effective solutions to sustainability challenges. ADVANCES One major advance has been recognizing Earth as a large, coupled human and natural system consisting of many smaller coupled systems linked through flows of information, matter, and energy and evolving through time as a set of interconnected complex adaptive systems. A number of influential integrated frameworks (such as ecosystem services, environmental footprints, human-nature nexus, planetary boundaries, and telecoupling) and tools for systems integration have been developed and tested through interdisciplinary and transdisciplinary inquiries. Systems integration has led to fundamental discoveries and sustainability actions that are not possible by using conventional disciplinary, reductionist, and compartmentalized approaches. These include findings on emergent properties and complexity; interconnections among multiple key issues (such as air, climate, energy, food, land, and water); assessment of multiple, often conflicting, objectives; and synergistic interactions in which, for example, economic efficiency can be enhanced while environmental impacts are mitigated. In addition, systems integration allows for clarification and reassignment of environmental responsibilities (for example, among producers, consumers, and traders); mediation of trade-offs and enhancement of synergies; reduction of conflicts; and design of harmonious conservation and development policies and practices. OUTLOOK Although some studies have recognized spillover effects (effects spilling over from interactions among other systems) or spatial externalities, there is a need to simultaneously consider socioeconomic and environmental effects rather than considering them separately. Furthermore, identifying causes, agents, and flows behind the spillover effects can help us to understand better and hence manage the effects across multiple systems and scales. Integrating spillover systems with sending and receiving systems through network analysis and other advanced analytical methods can uncover hidden interrelationships and lead to important insights. Human-nature feedbacks, including spatial feedbacks (such as those among sending, receiving, and spillover systems), are the core elements of coupled systems and thus are likely to play important roles in global sustainability. Systems integration for global sustainability is poised for more rapid development, and transformative changes aimed at connecting disciplinary silos are needed to sustain an increasingly telecoupled world. Illustrative representation of systems integration. Among Brazil, China, the Caribbean, and the Sahara Desert in Africa, there are complex human-nature interactions across space, time, and organizational levels. Deforestation in Brazil due to soybean production provides food for people and livestock in China. Food trade between Brazil and China also contributes to changes in the global food market, which affects other areas around the world, including the Caribbean and Africa, that also engage in trade with China and Brazil. Dust particles from the Sahara Desert in Africa—aggravated by agricultural practices—travel via the air to the Caribbean, where they contribute to the decline in coral reefs and soil fertility and increase asthma rates. These in turn affect China and Brazil, which have both invested heavily in Caribbean tourism, infrastructure, and transportation. Nutrient-rich dust from Africa also reaches Brazil, where it improves forest productivity. [Photo credits clockwise from right top photo: Caitlin Jacobs, Brandon Prince, Rhett Butler, and David Burdick, used with permission] Global sustainability challenges, from maintaining biodiversity to providing clean air and water, are closely interconnected yet often separately studied and managed. Systems integration—holistic approaches to integrating various components of coupled human and natural systems—is critical to understand socioeconomic and environmental interconnections and to create sustainability solutions. Recent advances include the development and quantification of integrated frameworks that incorporate ecosystem services, environmental footprints, planetary boundaries, human-nature nexuses, and telecoupling. Although systems integration has led to fundamental discoveries and practical applications, further efforts are needed to incorporate more human and natural components simultaneously, quantify spillover systems and feedbacks, integrate multiple spatial and temporal scales, develop new tools, and translate findings into policy and practice. Such efforts can help address important knowledge gaps, link seemingly unconnected challenges, and inform policy and management decisions.

Modeling the Drivers of Urban Land Use Change in the Pearl River Delta, China: Integrating Remote Sensing with Socioeconomic Data

This paper estimates econometric models of the socioeconomic drivers of urban land use change in the Pearl River Delta, China. The panel data used to estimate the models are generated by combining high-resolution remote sensing data with economic and demographic data from annual compendium. The relations between variables are estimated using a random coefficient model. Results indicate that urban expansion is associated with foreign direct investment and relative rates of productivity generated by land associated with agricultural and urban uses. This suggests that large-scale investments in industrial development, rather than local land users, play the major role in urban land conversion. (JEL R14)

Climate Response to Rapid Urban Growth: Evidence of a Human-Induced Precipitation Deficit

Abstract The authors establish the effect of urbanization on precipitation in the Pearl River Delta of China with data from an annual land use map (1988–96) derived from Landsat images and monthly climate data from 16 local meteorological stations. A statistical analysis of the relationship between climate and urban land use in concentric buffers around the stations indicates that there is a causal relationship from temporal and spatial patterns of urbanization to temporal and spatial patterns of precipitation during the dry season. Results suggest an urban precipitation deficit in which urbanization reduces local precipitation. This reduction may be caused by changes in surface hydrology that extend beyond the urban heat island effect and energy-related aerosol emissions.

Global typology of urban energy use and potentials for an urbanization mitigation wedge.

Significance Many case studies of specific cities have investigated factors that contribute to urban energy use and greenhouse-gas emissions. The analysis in this study is based on data from 274 cities and three global datasets and provides a typology of urban attributes of energy use. The results highlight that appropriate policies addressing urban climate change mitigation differ with type of city. A global urbanization wedge, corresponding in particular to energy-efficient urbanization in Asia, might reduce urban energy use by more than 25%, compared with a business-as-usual scenario. The aggregate potential for urban mitigation of global climate change is insufficiently understood. Our analysis, using a dataset of 274 cities representing all city sizes and regions worldwide, demonstrates that economic activity, transport costs, geographic factors, and urban form explain 37% of urban direct energy use and 88% of urban transport energy use. If current trends in urban expansion continue, urban energy use will increase more than threefold, from 240 EJ in 2005 to 730 EJ in 2050. Our model shows that urban planning and transport policies can limit the future increase in urban energy use to 540 EJ in 2050 and contribute to mitigating climate change. However, effective policies for reducing urban greenhouse gas emissions differ with city type. The results show that, for affluent and mature cities, higher gasoline prices combined with compact urban form can result in savings in both residential and transport energy use. In contrast, for developing-country cities with emerging or nascent infrastructures, compact urban form, and transport planning can encourage higher population densities and subsequently avoid lock-in of high carbon emission patterns for travel. The results underscore a significant potential urbanization wedge for reducing energy use in rapidly urbanizing Asia, Africa, and the Middle East.