Accessibility Analysis
Reach, Gravity, and Huff Model in Spatial Graph
Accessibility analysis has been researched in the field of physical planning and spatial modeling for over 50 years. The concept of accessibility explains both activity patterns in space and the connections between activities linked to Newton’s law of gravity. Hansen’s “How Accessibility Shapes Land Use” (1959) was the first defined paper about accessibility as a potential of using urban planning.
Accessibility analysis uses to investigate the relationship between land use cover type (e.g. distribution of land uses and activities) and transportation characteristics (e.g. transport network, speeds, and costs), retail business location, and demand forecast for transportation or patronage.
Reach
The sum of the number of accessible destinations (j) considering weight (w) (e.g. building GFA, transit connections at stations, number of jobs, retail sales, etc.) from origins (i) within a given radius (r) through shortest paths (d[i,j]).
Reach Index shows the cumulative opportunities that are accessible within a given radius. For the higher reach index, the destination value around each origin is higher.
Gravity
The model considers the general cost (e^beta, distance decay), the resistance factor of travel) of accessibility while reaching to destinations (j) from origins (i) within a given radius (r) through shortest paths (d[i,j]). is the exponential decay for adjusting the distance decay effect using a range of values from 0.001 to 0.005 for walking.
The result of the Gravity Index is lower than Reach Index due to the distance decay effect. For the higher gravity index, the destination value around each origin is higher.
Huff Model
The use of a gravity model to analyze market areas for retails. This model considers the probability (%) of demand between retails (j) from customers (i). w[j] is a measure of the attractiveness (size) of stores; d[i,j] is the distance from i to j; is an exponent distant decay usually between 1.5 and 2.
The Huff Index displays the probability as a percentage of consumers visiting within a given radius. The attractiveness of the store (store weight) and the distance you need to travel is competing. The higher the probability, the more attractive it is to the consumer.
Count Patronage
The number of potential customers in retail (j) can be estimated using the Huff Index. Considering the distance discounted patronage at each retail store (j), the distance decay value is applied to the model, resulting in less total sponsorship than the sum of the original demand.
Download NNA Toolbox Example Files for Accessibility Analysis — Link
