Comparison Between Census and LandScan Population Counts
Population densities are higher around the larger cities and along the Northern belt (Gangatic plain) of India. Analysis reflects that highest population density is in lower Gangatic plain, mainly concentrated in two major states of India, i.e. Bihar (1102 persons/km2) and West Bengal (1029 persons/km2). Grid-based difference measures led to interesting insights on where the differences between datasets are the most significant. Analysis shows that, for the large majority of pixels, the absolute difference between LandScan and Census is lower than 4 persons per 1 x 1 km grid square (Bengtsson et al. 2006). For these pixels with very low differences, the human population density is generally close to zero. However, the absolute differences can be much higher in more densely and extreme sparsely populated places.
In the LandScan dataset, the construction methodology means that populations are clustered around roads and less concentrated in towns, but more diffuse in rural areas. The total population per district predicted by the LandScan dataset is closer to the Census estimates than the any other dataset, though overall R2s values are relatively high in LandScan. In this case value is near perfect positive correlation which shows that LandScan data at the state level sufficient for comparison purpose refer Fig. 1.
Delhi is one of the most ancient and historic cities of India. From British times to the present date, it has undergone several administrative changes due to its special characters as the National Capital. Delhi, which is more clearly depicted as Delhi region consisting various towns of nearby districts of several states. Expansion of Delhi to nearby regions also expands the boundaries of vulnerability. The built-up area in the National Capital Region, which includes residential, nonresidential, landfill sites, etc., has increased by 34.6 % from 1999 to 2012 as per the figures in the Draft Revised Regional Plan-2021. The built-up area in the NCR has gone up from 2,76,566 to 3,72,370 ha showing an increase of 95,803 ha or 34.6 %. While the area under agriculture use has reduced marginally from 26,65,622 to 26,45,022 ha, green areas and water bodies have decreased substantially. Particularly, the Yamuna river bed has been lost due to the various construction activities, like construction of Delhi metro Depot, Common wealth Games Village, railway bridges, and construction of NH-24, etc. As per provisions of Sect. 3 and 5 of the Delhi Municipal Corporation Act, 1957 (as amended till date), the powers of the Central Government for delimitation of wards in MCD were delegated to the Lt. Governor of Delhi. Accordingly, the first delimitation of wards subsequent to the creation of the State Election Commission for Delhi, took place in 1993 on the basis of provisional census figures for 1991 (as final figures of population were not available at that time). At the time of the 2001 Census, there were 134 municipal wards in the MCD. However after Delimitation in 2007, the MCD area is presently divided into 272 wards and Delhi Municipal Corporation is divided into three corporations, namely north, south and east Delhi. Connotation of vulnerability is more social, than natural. But here it is used to highlight the vulnerability of population, which got effected because of flooding, thus spatial vulnerability assessment of Delhi can be productive for Hazard planning of the region (Fig. 3).
During common wealth games major infrastructure development took place with a large number of bridges, flyovers and the metro project under construction. After severe floods, the transport infrastructure is generally vulnerable. Major projects require special studies on seismic design criteria. Moreover, the Indian seismic codal provisions on bridges as these exist today are obsolete and inadequate (Jain et al. 1999). Flood risk in Delhi has the potential to go well beyond the statistics of deaths and injuries. Such a disaster in the country’s capital, which also happens to be a major commercial and residential centre, will have huge economic and political implications which will affect the entire country and not just the population of Delhi. This adds an extra dimension to the flooding problem for Delhi.
Fig. 3 Delhi Urban Agglomeration and built-up area
