_al_ . (1997), Sutton (2003), and Small _et al_ . (2005). More recent applications at either a regional or a global scale include Zhang and Seto (2011), Zhou _et al_ . (2015), Ellis and Roberts (2016), and CAF (2017).

Applications of NTL data to delineate metro areas have invariably relied on data products that have been derived by the National Oceanic and Atmospheric Association (NOAA) from sensors (Optical Line Scanner, or OLS, sensors) on-board the Defense Meteorological Satellite Program (DMSP) constellation of satellites. The derived DMSP-OLS data products cover the entire globe and are available at a resolution of 30 arc-seconds, which is, again, equivalent to approximately 1 km<sup>2</sup> at the equator. One deficiency of DMSP-OLS NTL data, however, is that they suffer from a well-documented “overglow” or “blooming” problem, whereby the light emitted from a given point on the earth is recorded as covering an area that extends beyond that point.<sup>10</sup> This creates a tendency for the lit area of a metro to overstate its “true” extent – for example, the Pacific Ocean can be lit up as far as 50 km from the coastline near Los Angeles (Pinkovskiy, 2013). The most common approach to dealing with this overglow problem has been to threshold the NTL data, considering only pixels in the data that exceed a certain luminosity, or digital number (DN), value as part of the area of a city or metro (see, for example, Imhoff _et al_ ., 1997; Small _et al_ ., 2005; Zhou _et al_ ., 2015; Ellis and Roberts, 2016). A contiguous cluster of grid cells that falls above the applied threshold is then classified as constituting a “metro” area.

More recently, however, DMSP-OLS NTL data have been superseded by NTL data collected from a new satellite sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor, launched in 2011. This sensor collects NTL data at a far higher resolution than the old DMSP-OLS sensors and the derived data products are also not subject to the overglow problem. We use the new VIIRS satellite data to delineate metro areas. Specifically, we use the 2015 annual composite product which has recently been released by NOAA.<sup>11</sup> This product reports luminosity values, calculated as an annual average over all cloud-free nights in 2015, at a resolution of 15 arc seconds, which is equal to 460 m<sup>2</sup> at the equator. Prior to averaging, NOAA applies filtering techniques to remove data that are affected by stray light, lightning, and lunar illumination. NOAA likewise filters out lights from aurora, fires, boats and other temporary lights. Although the VIIRS NTL data do not suffer from the same overglow problem as the DMSP-OLS NTL data, they, nevertheless, record light emitted to the nighttime sky by all human activities, including light at very low levels outside of what may be considered metro or even urban areas. For this reason, the use of a threshold may still be required to properly delineate metro from non-metro areas. As with papers that have used the DMSP-OLS data for the same purpose, we consider a contiguous cluster of grid cells that falls above any imposed threshold as representing a “metro” area.

# **3. Application to Indonesia**

# _3.1. Data sources_

The data that we use to apply the four approaches to delineating metro areas to Indonesia come from a variety of sources. For Duranton’s algorithm, we use data on O-D commuting flows between Indonesian districts that we derive from the August rounds of Indonesia’s national labor

> 10 See Doll (2008) for a description of the underlying causes of the overglow problem with DMSP-OLS NTL data.

> 11 This product is available for download from: https://ngdc.noaa.gov/eog/viirs/download_dnb_composites.html.

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