Hong Kong, China vs Kansai region: Land cover and land cover change — Gain of artificial surfaces

Hong Kong, China
55.77 Square kilometres
in 2022
Kansai region
946.46 Square kilometres
in 2022
Hong Kong, China rank
138th
Kansai region rank
137th

Land cover and land cover change — Gain of artificial surfaces over time

  • Hong Kong, China
  • Kansai region
02004006008001.0k200520132022

How they compare

Kansai region currently reports 946.46 Square kilometres against 55.77 Square kilometres in Hong Kong, China, a difference of 890.69 Square kilometres.

That makes Kansai region's figure about 17.0 times Hong Kong, China's.

Across all 5 years both countries report, Kansai region has been ahead every year.

Hong Kong, China ranks 138th and Kansai region ranks 137th of 164 countries.

Kansai region has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade Hong Kong, China Kansai region Difference Ahead
2000s 18.03 Square kilometres 51.31 Square kilometres 33.27 Square kilometres Kansai region
2010s 38.94 Square kilometres 696.74 Square kilometres 657.8 Square kilometres Kansai region
2020s 55.31 Square kilometres 931.67 Square kilometres 876.36 Square kilometres Kansai region

Averages of every year both report within each decade.

Frequently asked questions

Which has higher land cover and land cover change — gain of artificial surfaces, Hong Kong, China or Kansai region?
Kansai region, at 946.46 Square kilometres against 55.77 Square kilometres in Hong Kong, China as of 2022.
What is the difference in land cover and land cover change — gain of artificial surfaces between Hong Kong, China and Kansai region?
890.69 Square kilometres, with Kansai region ahead.
How many years of comparable data are there for Hong Kong, China and Kansai region?
5 years are reported by both, from 2005 to 2022.
How do Hong Kong, China and Kansai region rank globally for land cover and land cover change — gain of artificial surfaces?
Hong Kong, China ranks 138th and Kansai region ranks 137th of 164 countries.
Where does this data come from?
Organisation for Economic Co-operation and Development, published as Land cover and land cover change — Gain of artificial surfaces. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Hong Kong, China vs Kansai region: Land cover and land cover change — Gain of artificial surfaces. Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 16 September 2026, from https://environment.statizoid.com/compare/land-cover-and-land-cover-change-gain-of-artificial-surfaces/hong-kong-sar-china/kansai-region/

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About this data

Indicator
Land cover and land cover change — Gain of artificial surfaces
Unit
Square kilometres
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
978 places, 4,890 data points, 2005–2022
Last refreshed

The land cover dataset provides a global assessment of land cover and land cover change to monitor pressures on ecosystems and biodiversity. By using geospatial data with high spatio-temporal resolution, it develops a set of internationally comparable indicators with a long time series and a five-year interval from 2000 to 2022 for the Climate Change Initiative Land Cover dataset, and from 1975 to 2030 for the Global Human Settlement Layer dataset. Please see the working paper for a more complete description of the methods. The dataset has a global coverage on the national level, while on the sub-national TL2 level (i.e. large subnational regions) results are reported for all OECD countries as well as for Argentina, Brazil, China, India, Indonesia and South Africa. The following country aggregates are included: Euro area, European Union, Advanced economies, Emerging market economies, G7, G20, OECD, OECD Europe, OECD Asia Oceania, OECD Americas, the LAC region and the World. Data source(s): Climate Change Initiative land cover data and Global Human Settlement Layer built-up area data. Contact: ENV.Stat@oecd.org Database documentation