# _3.3. Key descriptives of identified metro areas_

Table 1 summarizes key statistics for metro areas delineated by each of the four approaches. For Duranton’s algorithm, we present statistics for commuting flow thresholds between 27 percent – which is when the first metro area appears using this algorithm – and 7 percent. Although we generated results for all commuting flow thresholds between these two values at 0.5 percent intervals, we only show results for selected thresholds. Meanwhile, for the cluster algorithm, we show results based on both the “Urban Cluster” (UC) set of thresholds (i.e. T<sup>�</sup> � = 300 people per km<sup>2</sup> , T<sup>�</sup> � = 5,000) and the “High Density Cluster” (HDC) set of thresholds (T<sup>�</sup> � =1,500 people per km<sup>2</sup> and T<sup>�</sup> � = 50,000). Finally, for the NTL approach, we present selected results based on the thresholding of the lights data at different points in the distribution of luminosity values.<sup>19</sup> In presenting results, we include information not only on the total number of metro areas, but also on the number of metro areas that belong to the official island-region of Java-Bali, which is where the majority of Indonesia’s urban population – approximately 70 percent in 2016 – resides and which, overall, is significantly more urbanized and densely populated than Indonesia’s other island-regions.<sup>20</sup>

**<u>Table 1: Comparison of key statistics</u>**

||<br>**No.**|<br>**No. me**|<br>**tro district**|**s**<br>**P**|**opulatio**|**n**|**Land**|<br>**area**|**Largest Metro**|
|---|---|---|---|---|---|---|---|---|---|
||**Metros**|||||||||
|**Threshold**|<br>**(Java-Bali)**|**total**|**avg per**<br>**Metro**|**Total**<br>**(mil.)**|**% IDN**|<br>**Urban**|**Total**<br>**(km**<sup>**2**</sup>**)**|**% IDN**|**Name**<br>**(no. districts)**|
||||**DU**|<br>**RANTON**|**ALGO**|**RITHM**||||
|27.0%|1 (1)|2|2.0|3.05|1.2|3.05|191|0.0|Bandung (2)|
|23.0%|2 (2)|4|2.0|6.71|2.7|6.71|513|0.0|Jakarta Selatan (2)|
|21.0%|3 (2)|6|2.0|10.88|4.3|10.40|3,405|0.2|Medan (2)|
|17.5%|4 (3)|8|2.0|12.36|4.9|11.75|3,921|0.2|Medan (2)|
|15.5%|8 (5)|17|2.1|19.31|7.7|16.99|17,616|0.9|Jakarta Selatan (3)|
|13.5%|11 (7)|23|2.1|25.45|10.1|20.86|24,483|1.3|Jakarta Selatan (3)|
|12.0%|14 (8)|31|2.2|32.81|13.0|27.18|35,205|1.9|Surabaya (3)|
|11.0%|20 (13)|43|2.2|49.55|19.7|41.18|41,529|2.2|Surabaya (3)|
|10.0%|24 (17)|58|2.4|64.51|25.6|51.13|54,181|2.9|Bogor (2)|
|9.0%|28 (16)|77|2.8|81.79|32.5|63.86|76,542|4.0|Jakarta (11)|
|8.0%|32 (17)|86|2.7|88.18|35.0|67.70|89,773|4.7|Jakarta (11)|
|7.0%|39(18)|103|2.6|97.09|38.5|72.70|110,197|5.8|Jakarta(13)|
||||**AGG**|**LOMER**|**ATION**|**INDEX**||||
|AI|12(4)|126|10.5|14170|56.2|89.38|126414|6.7|West-Central Java (38)|
|||<br>|<br>**CL**<br>|,<br>**USTER**<br>|<br>**ALGOR**<br>|<br>**ITHM**<br>|,<br>|<br>||
|HDC|9(8)|38|4.2|62.53|24.8|54.15|22,739|1.2|Jakarta(15)|

19 For the NTL approach, we experimented with a total of 19 thresholds by breaking the national range of NTL intensity values (from 0 to 1,340.44) at every 5<sup>th</sup> percentile. Despite the wide range, low values are prevalent in Indonesia and 95 percent of the values fall below 9.11.

20 In 2016, 60.8 percent of Indonesia’s population was classified as urban. For Indonesia’s other main island-regions, the shares of the population classified as urban were as follows: Kalimantan (43.5 percent), Sumatra (40.2 percent), Sulawesi (35.0 percent), Nusa Tenggara (31.6 percent), and Maluku-Papua (31.3 percent).

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