Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
149 tokens/sec
GPT-4o
9 tokens/sec
Gemini 2.5 Pro Pro
47 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

The Distance-Decay Function of Geographical Gravity Model: Power Law or Exponential Law? (1503.02915v1)

Published 10 Mar 2015 in physics.soc-ph

Abstract: The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be explained with the ideas from Euclidean geometry. This results in what is called dimension dilemma. In particular, the gravity model based on power law could not be derived from general principles by traditional ways. Consequently, a negative exponential function substituted for the inverse power function to serve for a distance-decay function for the gravity model. However, the exponential-based gravity model goes against the first law of geography. This paper is devoted to solve these kinds of problems by mathematical reasoning and empirical analysis. First, it can be proved that the distance exponent of the gravity model is essentially a fractal dimension. Thus the dimensional dilemma of the power-based gravity model can be resolved using the concepts from fractal geometry. Second, the exponential function indicates locality and localization, which violates the basic principle of spatial interaction. The power function implies action at a distance, which is the necessary condition of geographical gravitation. Third, the gravity model based on power law decay can be derived from the entropy- maximizing principle by introducing a proper postulate. The observational data of China's cities and regions are employed to verify the theoretical inferences, and the results support power-law distance decay. A conclusion can be reached that the preferred form of geographical gravity model is its original form, which is based on an inverse power law rather than a negative exponential law.

Summary

We haven't generated a summary for this paper yet.