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How Do ICTs Affect Urban Spatial Structure? A Systematic Literature Review
The Journal of urban technology, 2019This study attempts to shed light on the effects of ICTs on urban spatial structure through a systematic literature review by exploring the relationship between ICTs and the factors that shape this structure.
Zahed Yousefi, H. Dadashpoor
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Spatial structure and labour productivity: Evidence from prefectures in China
Urban studies, 2018This paper examines the effect of spatial structure, as measured on the monocentricity–polycentricity dimension, on labour productivity at the prefectural level in China.
Wan Li, Bindong Sun, Tinglin Zhang
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Spatial Problem Solving in Spatial Structures
2017The ability to solve spatial tasks is crucial for everyday life and therefore of great importance for cognitive agents. In artificial intelligence (AI) we model this ability by representing spatial configurations and spatial tasks in the form of knowledge about space and time.
Christian Freksa +4 more
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Spatially Oscillating Structures
2010This chapter illustrates applications of nonsmooth argument substitutions to modeling spatially oscillating structures such as one-dimensional elastic rods with periodic discrete inclusions, and two- or three-dimensional acoustic media with periodic nonsmooth boundary sources of waves.
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Structural Spatial Interaction∗
The Professional Geographer, 1993This paper identifies a concept of structural spatial interaction. Although it is defined differently from its counterpart of structural unemployment in economics, it attempts to define a similar idea. In economics, the focus is on equilibrium in the supply and demand of labor.
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2004
For any component in time series analysis (Natke 1983), the concept of covariance between components of a spatially distributed random vector Z(u) leads to: direct covariances, Cov[Zi(u),Zj(u)]; shifted covariances or spatial covariances, Cov [Zi(u), Zj-(u+ h)], also known as cross-covariance functions; and autocovariance functions, Cov[Zi(u),Zi(u + h)]
Vera Pawlowsky-Glahn, Richardo A. Olea
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For any component in time series analysis (Natke 1983), the concept of covariance between components of a spatially distributed random vector Z(u) leads to: direct covariances, Cov[Zi(u),Zj(u)]; shifted covariances or spatial covariances, Cov [Zi(u), Zj-(u+ h)], also known as cross-covariance functions; and autocovariance functions, Cov[Zi(u),Zi(u + h)]
Vera Pawlowsky-Glahn, Richardo A. Olea
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Spatial Structure and Spatial Interaction: A Simulation Approach
Environment and Planning A: Economy and Space, 1991In this paper, variations in the impedance parameter of the conventional spatial interaction models are examined in a quasi-empirical manner. In a previous paper, a spatial demand model based on the translog indirect utility function was simulated to provide interaction data.
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LISA: A Learned Index Structure for Spatial Data
SIGMOD Conference, 2020In spatial query processing, the popular index R-tree may incur large storage consumption and high IO cost. Inspired by the recent learned index [17] that replaces B-tree with machine learning models, we study an analogy problem for spatial data.
Pengfei Li +4 more
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Spatial Structure and Spatial-Temporal Processes
1983There are many ways of describing pattern and testing for structure in spatial data. The best known statistics have been discussed, together with a summary of earlier contributions and important extensions, in two books by Cliff and Ord (1973, 1981). The first of these was concerned largely with various indices for testing for significant structure in ...
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