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INSA applies Satellite and ground-based sensors for the Urban Heat Island and Heat wave analysis in the city of Madrid

“INSA has implemented an innovative geospatial system to improve the monitoring of high temperature events using MODIS and SEVIRI data in Madrid”.

Climate change will affect human health, either directly, in relation to the physiological effects of heat and cold, or indirectly, for example, through altered human behaviours. An increase in some of these impacts has already been observed in Europe over recent decades (for example, the summer heat waves in 2003 alone are believed to have resulted in more than 70 000 excess deaths, Robin et al., 2008). Spain is one of the most affected European countries by the increase of temperature, with an observed variation between +1 ºC and +2ºC in the 1970-2004 time period (IPCC Climate change report 2007). In addition, climate change scenarios suggest that other not Mediterranean European Countries could be affected in the future by heat waves. As extreme events (i.e. Urban Heat Islands) become more frequent and spatially distributed due to climate change, weather related deaths and diseases could rise. In addition, population ageing is changing disease patterns, and putting pressure on the sustainability of EU health systems.
EUROSTAT estimates that by 2050 the number of people in the EU aged 65+ will grow by 70% whereas the 80+ age group will grow by 170%. Therefore, the challenge for policy-makers, at both national and EU levels, is to understand these climate change impacts and to develop and implement policies to ensure an optimal level of adaptation and mitigation. In EU countries, it is estimated that mortality increases by 1-4% for each one-degree rise in temperature, meaning that heat related mortality could rise by 30 000 deaths per year by 2030s and by 50000 to 110000 deaths per year by the 2080s (PESETA project report).

Therefore EU policies suggest that healthy ageing must be supported by actions to promote health and prevent disease throughout the lifespan by tackling key issues including environmental risks. In this context INSA has implemented an innovative geospatial system in order to:

  • improve the monitoring of high temperature events (air temperature and urban heat islands products) using a combination of satellite data, static multisource information (synthetic products), and an on-line platform (geoportal) for the product delivery. This service helps to reduce the impact of heat waves on human health and giving a near real time identification of population on risk, its location.
  • support both decision making and planning processes in the short-, mid- and long-term and improving the efficient allocation of health resources with the provision of synthetic products about affected population, high risk zones and related health infrastructures; with this information, socio-economic impact can be reduced.
  • support future urban planning indicating the location of the high risk zones which need mitigation actions and verifying the effects of these activities.

In order to achieve these objectives, INSA has dedicated internal R&D resources to the definition of remote sensing applications and development of processing algorithms to monitoring of high-temperature events in order to reduce their impacts on human health.

Urban Heat Islands (UHI) in the city of Madrid

Over the last century, the world has witnessed a huge growth in its population; this intense and relatively fast spread of the urban areas changes the characteristics of the Earth’s surface and atmosphere. The anthropogenic activities induce changes in the physical characteristics of the surface (albedo, thermal capacities, heat conductivity, moisture) and have significant implications for energy budget (Oke, 1987). In metropolitan areas and more so in the city centres, the removal of natural land cover and the introduction of artificial materials, such as concrete and asphalt, modify the surface energy balance, resulting in an increase in surface temperature; in turn this creates an increase in sensible heat flux and a resultant rise in air temperature. In case of a heat wave, these factors usually associated with low wind speeds and high humidity put the population under strong thermal stress with dramatic consequences.

The above result in downtown areas being much warmer than its rural surroundings produces the Urban Heat Island (UHI) phenomenon. The UHI are typically detected by ground stations using thermometers in order to measure air temperature in the canopy layer. An alternative method uses infrared radiometry from aircraft or satellite platforms, which observe the surface heat island or, more specifically, they see the spatial patterns of upwelling thermal radiance received by the detector and use it to estimate the surface temperature. An advantage in using satellite data with respect to ground-based observations is to provide more spatially representative measurements of surface temperature over large areas of cities.

Different approaches have been published in the last years in order to retrieve land surface temperature (LST) from satellite-derived radiances. Among these methods, the two-channel or split-window algorithms have been the most commonly used. The split-window algorithms take advantage of the differential absorption in two close infrared channels to correct for the atmospheric effects, describing the surface temperature in terms of a linear combination of brightness temperatures measured in both thermal channels. The algorithm’s coefficients depend on the atmospheric state and on the surface emissivity and they are chosen in order to minimize the error in the LST determination.

Numerous studies have been done to estimate these coefficients; but, sometimes fixed values are utilized, imposing significant errors to the results.

In order to employ a method for the evaluation of the UHI in Madrid with less uncertainty, INSA has developed a local and more suitable algorithm for the estimation of the UHI with MODIS and SEVIRI data (Fabrizi et al., 2011). This innovation method exploits the availability of air temperature data from ground-based weather stations in the study’s area for the calibration and validation of the model. The following figure describes the UHI algorithm workflow:

Figure 1: UHI workflow of INSA’s method
The UHI maps are generated automatically and provided experimentally by the INSA geoportal ( The maps (Figure 2-3) contain semantic data (open street data, administrative data). The output product is a vector layer (shape file) including Air Temperature and UHI Spatial Extent and Intensity, as well the affected population (provided by the National Statistic Institute (, high risk zones and related health infrastructures.

Figure 2: Urban Heat Islands in the city of Madrid with MODIS data in August 25th 2010 at 22:00 UTC (Google Earth).

Figure 3: Urban Heat Islands in the city of Madrid with MODIS data in August 25th 2010 at 22:00 UTC (Google Earth 3D).


  • IPCC: Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Edited by: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL. United Kingdom and New York, NY, USA. Cambridge University Press:996.
  • Fabrizi, R., De Santis, A., Gomez, A. (2011) Satellite and ground-based sensors for the Urban Heat Island analysis of the city of Madrid. 10.1109/JURSE.2011.5764791
    Oke, T.R. Boundary Layer Climates, 2nd Ed.; Routledge, London, 1987; pp. 435
  • Robine, J., Cheung, S., Le Roy, S., Van Oyen, H., Griffiths, C., Michel, J.P., Herrmann, F., 2008. Death toll exceeded 70,000 in Europe during the summer of 2003. C. R. Biol. 331, 171–U175.