Mapping global urban areas using MODIS 500-m data: New methods and datasets based on ‘urban ecoregions’

Abstract

Although cities, towns and settlements cover only a tiny fraction (< 1%) of the world's surface, urban areas are the nexus of human activity with more than 50% of the population and 70–90% of economic activity. As such, material and energy consumption, air pollution, and expanding impervious surface are all concentrated in urban areas, with important environmental implications at local, regional and potentially global scales. New ways to measure and monitor the built environment over large areas are thus critical to answering a wide range of environmental research questions related to the role of urbanization in climate, biogeochemistry and hydrological cycles. This paper presents a new dataset depicting global urban land at 500-m spatial resolution based on MODIS data (available at http://sage.wisc.edu/urbanenvironment.html). The methodological approach exploits temporal and spectral information in one year of MODIS observations, classified using a global training database and an ensemble decision-tree classification algorithm. To overcome confusion between urban and built-up lands and other land cover types, a stratification based on climate, vegetation, and urban topology was developed that allowed region-specific processing. Using reference data from a sample of 140 cities stratified by region, population size, and level of economic development, results show a mean overall accuracy of 93% (k = 0.65) at the pixel level and a high level of agreement at the city scale (R² = 0.90).

Introduction

In a relatively short period of time, urbanization has emerged as a top environmental issue facing many parts of the Earth (Montgomery, 2008). Urban areas have profound environmental impacts that extend beyond city boundaries, including urban heat island effects, impervious surfaces that alter sensible and latent heat fluxes, conversion and fragmentation of natural ecosystems, loss of agricultural land, contamination of air, soil and water, increased water use and runoff, and reduced biodiversity (Pickett et al., 1997, El Araby, 2002, Alberti, 2005, Shepherd, 2005). New estimates that half of the global population now lives in urban areas means that the importance and impact of cities is greater than ever before (UN, 2008). An additional two billion people are expected to arrive in cities by 2050, with nearly 90% of this growth expected in developing countries. Clearly, the impact of urban areas on the human population and the global environment is significant, and will become even more pronounced in the future (Mills, 2007).

While we are beginning to comprehend the local environmental impacts of urbanization, there is a new interest across several disciplines to understand how urbanization — regionally or cumulatively — contributes to global environmental change (Grimmond, 2008, Mills, 2007). Urban areas are the primary source regions of anthropogenic carbon emissions (Svirejeva-Hopkins et al., 2004), yet global models of climate and biogeochemistry include only relatively crude representations of urban areas (Pataki et al., 2006). Recent studies have demonstrated that accurate representation of urban land use is both important and poorly captured in current models (Oleson et al., 2008, Peters-Lidard et al., 2004). Accurate and timely information on the distribution and characteristics of urban areas are therefore essential for a wide array of geophysical research questions related to the impact of humans on the environment (Kaye et al., 2006). The datasets that have emerged during the last decade show considerable disagreement on the location and extent of urban areas (Potere and Schneider, 2007, Potere et al., 2009). Moreover, most environmental modeling efforts require additional information that is not available at regional to global scales, including urban vegetation types, presence of irrigation, building heights and materials, and urban surface radiative and thermodynamic properties (Oleson et al., 2008).

In this paper we present results from a new effort to create a global map of urban, built-up and settled areas, which serves as the first stage in our development of a comprehensive database of urban land surface characteristics for 2001–2010. This work builds on previous mapping efforts using Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1-km spatial resolution (Schneider et al., 2003, Schneider et al., 2005), which is included as part of the MODIS Collection 4 (C4) Global Land Cover Product (Friedl et al., 2002). Here we address weaknesses in the first map as well as several limitations of contemporary global urban maps by developing a methodology that relies solely on newly released Collection 5 (C5) MODIS 500-m resolution data. Specifically, a supervised decision-tree classification algorithm is used to map urban areas using region-specific parameters. At the heart of our approach is a new, global stratification of “urban ecoregions” that facilitates study and mapping of cities and towns at regional to global scales. After describing our methods, we expand on work presented in Schneider et al. (2009) by presenting our results, a validation of the new map using a global, stratified random sample of 140 case study cities, and assessment of urban land densities captured by the new global urban map.