Annemarie Schneider

A new map of global urban extent from MODIS satellite data

Although only a small percentage of global land cover, urban areas significantly alter climate, biogeochemistry, and hydrology at local, regional, and global scales. To understand the impact of urban areas on these processes, high quality, regularly updated information on the urban environment—including maps that monitor location and extent—is essential. Here we present results from efforts to map the global distribution of urban land use at 500 m spatial resolution using remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our approach uses a supervised decision tree classification algorithm that we process using region-specific parameters. An accuracy assessment based on sites from a stratified random sample of 140 cities shows that the new map has an overall accuracy of 93% (k = 0.65) at the pixel level and a high level of agreement at the city scale (R 2 = 0.90). Our results (available at http://sage.wisc.edu/urbanenvironment.html) also reveal that the land footprint of cities occupies less than 0.5% of the Earth’s total land area.

Compact, Dispersed, Fragmented, Extensive? A Comparison of Urban Growth in Twenty-five Global Cities using Remotely Sensed Data, Pattern Metrics and Census Information

Despite growing recognition of the important role of cities in economic, political and environmental systems across the world, comparative, global-scale research on cities is severely limited. This paper examines the similarities and differences in urban form and growth that have occurred across 25 mid-sized cities from different geographical settings and levels of economic development. The results reveal four city types: low-growth cities with modest rates of infilling; high-growth cities with rapid, fragmented development; expansive-growth cities with extensive dispersion at low population densities; and frantic-growth cities with extraordinary land conversion rates at high population densities. Although all 25 cities are expanding, the results suggest that cities outside the US do not exhibit the dispersed spatial forms characteristic of American urban sprawl.

A new urban landscape in East–Southeast Asia, 2000–2010

East–Southeast Asia is currently one of the fastest urbanizing regions in the world, with countries such as China climbing from 20 to 50 percent urbanized in just a few decades. By 2050, these countries are projected to add 1 billion people, with 90 percent of that growth occurring in cities. This population shift parallels an equally astounding amount of built-up land expansion. However, spatially-and temporally detailed information on regional-scale changes in urban land or population distribution do not exist; previous efforts have been either sample-based, focused on one country, or drawn conclusions from datasets with substantial temporal/spatial mismatch and variability in urban definitions. Using consistent methodology, satellite imagery and census data for greater than1000 agglomerations in the East–Southeast Asian region, the authors show that urban land increased to greater than 22 percent between 2000 and 2010 (from 155 000 to 189 000 square kilometers), an amount equivalent to the area of Taiwan, while urban populations climbed greater than 31 percent (from 738 to 969 million). Although urban land expanded at unprecedented rates, urban populations grew more rapidly, resulting in increasing densities for the majority of urban agglomerations, including those in both more developed (Japan, South Korea) and industrializing nations (China, Vietnam, Indonesia). This result contrasts previous sample-based studies, which conclude that cities are universally declining in density. The patterns and rates of change uncovered by these datasets provide a unique record of the massive urban transition currently underway in East–Southeast Asia that is impacting local-regional climate, pollution levels, water quality and availability, arable land, as well as the livelihoods and vulnerability of populations in the region.

Bringing an ecological view of change to Landsat-based remote sensing

When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser-scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, longterm trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

Expansion and growth in Chinese cities, 1978?2010

It has long been recognized that compact versus more sprawling urban forms can have very different environmental impacts. As the Chinese population continues to rapidly urbanize, the size, shape, and configuration of cities in China will undoubtedly change to accommodate expansion of housing, industry, and commerce, causing direct and indirect environmental impacts at multiple scales. It is therefore imperative to understand how urban areas are evolving as socio-economic reforms in China are implemented across different regions. This paper compares trends in 142 Chinese cities (including 17 agglomerations) to understand urban expansion and population growth following reforms, 1978?2010. The results show that cities tripled in size, while doubling in population over the same period. In coastal areas targeted by early policies, urban land increased 4?5 times since 1978, for all city sizes. Large agglomerations are the primary consumers of land in coastal and western regions, each adding an average of 450?km2 during the study period, while small-medium cities consumed an average 20?km2. Although populations in these agglomerations increased an average 1.3 million, 2000?2010, cities within 100?km of each agglomeration grew >1.8 million collectively. Proximity to large agglomerations contributed to the growth of small-medium cities, especially in western regions.

Mapping the Expansion of Boom Crops in Mainland Southeast Asia Using Dense Time Stacks of Landsat Data

We performed a multi-date composite change detection technique using a dense-time stack of Landsat data to map land-use and land-cover change (LCLUC) in Mainland Southeast Asia (MSEA) with a focus on the expansion of boom crops, primarily tree crops. The supervised classification was performed using Support Vector Machines (SVM), which are supervised non-parametric statistical learning techniques. To select the most suitable SMV classifier and the related parameter settings, we used the training data and performed a two-dimensional grid search with a three-fold internal cross-validation. We worked in seven Landsat footprints and found the linear kernel to be the most suitable for all footprints, but the most suitable regularization parameter C varied across the footprints. We distinguished a total of 41 LCLUCs (13 to 31 classes per footprint) in very dynamic and heterogeneous landscapes. The approach proved useful for distinguishing subtle changes over time and to map a variety of land covers, tree crops, and transformations as long as sufficient training points could be collected for each class. While to date, this approach has only been applied to mapping urban extent and expansion, this study shows that it is also useful for mapping change in rural settings, especially when images from phenologically relevant acquisition dates are included.

Monitoring the Extent and Intensity of Urban Areas Globally using the Fusion of MODIS 500m Resolution Satellite Imagery and Ancillary Data Sources

Although only a small percentage of global land cover, urban areas significantly alter climate, biogeochemistry, and hydrology at local, regional, and global scales. Despite the fact that three billion people live in cities, information related to global geographic patterns in urban extent and density is poor. Here we present results from efforts to map the global distribution of urban land use at 463 m spatial resolution using remotely sensed data from MODIS. Our approach uses a supervised decision tree classification algorithm that we process using region-specific parameters. The resulting map shows that urban areas occupy only 0.5-1.0 percent of the Earths land area. Because resource and energy consumption is concentrated in urban areas, the geographic distribution and intensity of urban land use has important implications for models and related studies that require information related to role of humans in the global environment.