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Global database of urban heat islands (UHI)

The Urban Heat Island

An urban heat island (UHI) occurs when a city experiences much warmer temperatures than nearby rural areas. The difference in temperature between urban and less-developed rural areas has to do with how well the surfaces in each environment absorb and hold heat.

(Source: NASA)


The Google Earth Engine App

This dataset is developed by Yale Center for Earth Observation (YCEO) . This center has developed a Google Earth Engine web app to visualize the global UHI data. This interactive web app is to monitor urban heat island (UHI) intensities of practically all urban clusters on Earth. The app allows users to query the UHI data of urban areas using a simple interface. The UHI dataset was created based on the simplified urban-extent (SUE) algorithm detailed in Chakraborty and Lee, 2019.


Earth Engine Snippet

This global dataset is now available via GEE platform for public use. Pixel-level composites of yearly summertime daytime and nighttime intensity can be accessed using following Earth Engine snippet-

ee.ImageCollection("YALE/YCEO/UHI/Summer_UHI_yearly_pixel/v4")

Description of Data

According to its description on GEE dataset page-

"'This dataset contains annual, summertime, and wintertime surface urban heat island (SUHI) intensities for day and night for over 10,000 urban clusters throughout the world. The dataset was created using the MODIS 8-day TERRA and AQUA land surface temperature (LST) products, the Landscan urban extent database, the Global Multi-resolution Terrain Elevation Data 2010, and the European Space Agency (ESA) Climate Change Initiative (CCI) land cover data using the Simplified Urban-Extent Algorithm. The product is available both at the pixel level (at 300 m resolution after downscaling) and as urban cluster means from 2003 to 2018."

The dataset is split into the following six components:

  1. UHI_all_averaged: Image containing cluster-mean composite daytime and nighttime SUHI intensity for annual, summer, and winter.

  2. UHI_monthly_averaged: Image containing cluster-mean monthly composites of daytime and nighttime SUHI intensity.

  3. UHI_yearly_averaged: Image collection of cluster-mean yearly composites of daytime and nighttime SUHI intensity from 2003. to 2018.

  4. UHI_yearly_pixel: Image collection of spatially disaggregated (nominal scale of 300 m) annual daytime and nighttime SUHI intensity from 2003 to 2018.

  5. Summer_UHI_yearly_pixel: Image collection of spatially disaggregated (nominal scale of 300 m) summertime daytime and nighttime SUHI intensity from 2003 to 2018.

  6. Winter_UHI_yearly_pixel: Image collection of spatially disaggregated (nominal scale of 300 m) wintertime daytime and nighttime SUHI intensity from 2003 to 2018.


Limitations of the data

There are of course some limitation of this data. 'UHI calculations by this app are done for urban clusters, not for individual cities. This is because there are a lost of issues with delineating urban areas at the city-scale.'


Observations

While visualizing this data through GEE app, I noticed that during 2018 surprisingly, Delhi and Mumbai metropolitans have lower UHI effect compared to rest two i.e. Chennai and Kolkata. Here is the snapshot of above mentioned four regions-


Delhi-

At the middle of Delhi following statistics was obtained during summertime daytime and nighttime surface urban heat island (SUHI) intensity from 2003 to 2018 -


Mumbai-

Chennai-

Kolkata-


All Four in one view


Author-

Dr. Gopal Krishna, PhD

Geoinformers

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Geoinformatics and Remote Sensing