Administration. The product has a resolution of about 500 meters per cell and is available from 2001 onward (Friedl and others 2010).

- _GHSL‐Landsat_ is derived from images taken by sensors aboard satellites that are part of the Landsat program. As one of the first civilian satellite programs on land cover, Landsat has produced the longest continuous space‐based record of the Earth’s land surface. Data for the years 1975, 1990, 2001, and 2013/14 are available from the Global Human Settlement Layer project (Pesaresi, <mark>Ehrlich,</mark> and others 2016). The resolution of the product is about 38 meters per cell.

- _GUF‐TerraSAR_ is based on radar images taken by sensors aboard the twin satellites TerraSAR‐X and TanSAR, which are part of the more recent WorldDEM program. Reliance on radar images implies lower sensitivity to weather conditions, cloudiness and vegetation density. Data for 2011 are available from the German Aerospace Center at a resolution of about 12 meters per cell (Esch and others 2017).

After a careful comparison of the three data sources, we selected the GHSL‐Landsat product for this study. This choice is consistent with that of Burchfield and others (2006), who use the Landsat product to study urban development in the United States.

In the case of India, MODIS is limited by its coarse resolution. In particular, it does not capture built‐up cover in forest areas as well as the other two data sources. Data from both GHSL‐Landsat and GUF‐ TerraSAR yield very similar results while GUF‐TerraSAR has a higher resolution. The correlation coefficient between the two sources for the built‐up share at the town or village level is 0.96. In addition, GHSL‐ Landsat data are available for multiple years, whereas GUF‐TerraSAR data are available only for 2011. This is a constraint, because we want to estimate not only the urban extent, but also the speed of urbanization over time. We use GHSL‐Landsat data for 2001 and 2013/14 for the census years 2001 and 2011, respectively. But we check that the results remain the same when using GUF‐TerraSAR data for the year 2011.

For the measurement of the lit‐up area we rely on the Global Radiance Calibrated Nighttime Lights product. This product is derived from images taken by the Operational Linescan System (OLS) sensors aboard satellites from the U.S. Air Force Defense Meteorological Satellite Program (DMSP). Data are available from the National Geophysical Data Center at the National Oceanic and Atmospheric Administration (NOAA).

This is not the only product available for nighttime light images, but it has a higher quality than its competitors because it captures stable lights, addresses the saturation problem, and is intercalibrated to reduce inconsistencies across satellites (Elvidge and others 2009; Hsu and others 2015; NOAA 2014). The intensity of nighttime light is reported in Digital Numbers. We use data for 2001 and 2011, thereby matching the census years. Because the data are not generated in the same way in both years, we apply the intracalibration formula proposed by Hsu and others (2015) to ensure consistency over time.

A key challenge when using data on nighttime light is that even areas without human activity may appear to be lit up (Henderson and others 2003; Li and Zhou 2017; Zhou and others 2014). This may be due to blooming, or to the reflection of light from surrounding water and other land covers, or to the sensitivity of the sensors, or to the cumulative effects of geo‐referencing errors made in the capture and composting of satellite imagery. To avoid overestimation of the lit‐up share, a threshold is generally set up for nighttime light intensity, and only observations above the threshold are considered urban. However, the 15