Population, Density & Accessibility Gaps

Population density is simply people per unit area - persons per hectare or per square kilometre - and it is the first thing a planner reads off a city, because it drives demand for everything: water, schools, road capacity, open space. Mapped as a choropleth (each area shaded by its density), it shows at a glance where the city is crowded and where it is sparse.

But density inherits a subtlety: it depends entirely on the area you divide by. The same population looks dense in a tightly-drawn ward and sparse in a large one. This is the Modifiable Areal Unit Problem (MAUP) - change the boundaries and you change the answer, without a single person moving. It is not a reason to distrust density; it is a reason to state your unit and be wary of comparing densities computed on different-sized areas.

Two sources anchor population work in India. The Census of India is the authoritative count - population and demographics down to ward and village level - but it is decadal, so between censuses it ages, and its data comes tied to administrative boundaries (with all the MAUP that implies). To fill the gaps, planners increasingly use WorldPop, a modelled gridded population surface at roughly 100 m resolution, released under a Creative Commons licence.

The two are complementary. Census gives you real, attributable counts on official units; WorldPop gives you a continuous grid you can slice by any shape - a catchment, a flood zone, a walking radius - without being trapped by administrative lines. A common technique, dasymetric mapping, refines a coarse census count using a finer layer (built-up area, buildings) so people are placed where they actually live rather than smeared evenly across a ward.

A park, school or clinic does not serve its ward; it serves a catchment - the area within a reasonable distance of it. URDPFI and similar norms set those distances (a neighbourhood park within a few hundred metres, a primary school within walking range), and GIS lets you draw them. The simplest catchment is a buffer - a distance ring around each facility - and a better one is a network service area from Lesson 8.3, following the streets people really walk.

Once you have catchments, coverage is a spatial question you can answer exactly: dissolve all the catchments together and you have the served area; whatever population falls outside it is un-served. This is the heart of provision planning - not 'how many parks does the city have', but 'how many people can reach one'.

Gap analysis puts density and catchments together. Take the population surface, subtract the served catchments, and what remains is the gap - the people, and the places, that no facility reaches within the standard. Overlay several amenities and the gaps compound into a map of relative disadvantage: areas short of parks and schools and clinics.

This is among the most powerful and equitable uses of GIS in planning, because it shifts the question from supply to access. A city can meet its per-capita park norm on paper while concentrating all the parks in prosperous wards; only a spatial gap analysis exposes that. Done with the population grid rather than ward averages, it names the shortfall in people, not polygons - the number that moves a budget.

The last refinement is to stop pretending people fly. A straight-line buffer overstates reach; a network catchment (or an isochrone - the area reachable within a travel time) follows the walkable street length and gives a truer, jagged shape. The difference is often large in Indian cities cut by rail lines, drains and gated layouts, where two homes 200 m apart may be a kilometre apart on foot.

Be honest about the limits. Census data ages and MAUP bends density; WorldPop is a model with its own error and should be validated where you can. Catchments assume an average walker on an average day, ignoring heat, safety, footpath quality and who is actually free to walk. And a gap map shows where provision is short, not why, nor whether new land is available to fix it. Used with those caveats stated, accessibility analysis is one of the strongest evidence tools a planner has; used as a black box, it launders assumptions into apparent fact.