This gives credence to Dr. Roy Spencer’s population adjusted ISH surface temperature data for the USA
Impact of population density on the surface temperature and micro-climate
Javed Mallick1 and Atiqur Rahman2,* 1Department of Civil Engineering, King Khalid University, Abha, Kingdom of Saudi Arabia 2Remote Sensing and GIS Division, Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia University, New Delhi 110 025, India
Increasing urban surface temperature due to change of natural surfaces is one of the growing environmental problems in urban areas, especially in cities like Delhi. The present work is an attempt to assess the urban surface temperature in Delhi using remote sensing and GIS techniques. ASTER datasets of thermal bands were used to assess the land surface temperature (LST) using temperature emissivity separation technique. Ward-wise population density was calculated from the Census of India 2001 data to correlate the population density with LST. The study shows that surface temperature changes with the increase in the impervious surface area, which is related to the increase in the population density.
From the discussion:
Figure 4 shows the correlation between surface temperature and population density. A strong positive correlation between the two can be seen. The value of logarithmic regression (R2) is 0.748. The logarithmic regression equation between surface temperature and population density is Y = 1.059ln × Pop-density + 22.40. It means that with the increase in population density, surface temperature also increases. Furthermore, it is possible to predict night-time surface temperature on the basis of known population density.
Oke used the empirical method to represent the relationship between urban–rural temperatures as concentration on population. It is not easy to separate many contributors to the problem. However, one of the most noticeable and one that has proven to have an
extremely strong correlation with the UHI phenomenon or urban surface temperature is the population density of major cities32. The present study demonstrates a close
relationship between the population density, built-up area and surface temperature. The statistical analysis of nighttime surface temperature with population density indicates
that population growth tends to contribute to the urban surface temperature rise or UHI intensity and also to the micro-climate of Delhi.
In earlier times and even now, there are very few meteorological stations to record the surface temperature, and they may not be the true representative for the whole city. In such situations, LST derived from thermal satellite data are useful to study the variation of surface temperature over the entire city area that is an important parameter for micro-climate of urban areas. This study clearly shows spatial variation of LST over entire Delhi.
By superposing the population density map of Delhi over the surface temperature map, it can be clearly seen that high population density is one of the main contributing
factors for the high surface temperature, UHI intensity and also micro-climate of Delhi. To assess and address the issue of micro-climate and also to mitigate the impact of UHI on the city population, the outcome of such types of studies may be useful.
h/t to Dr. Willie Soon