Exploring the spatio-temporal dynamics of geographical processes with geographically weighted regression and geovisual analytics
Exploring the spatio-temporal dynamics of geographical processes with geographically weighted regression and geovisual analytics
复制标题
通过地理加权回归和地理视觉分析探索地理过程的时空动态
DOI：
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发表时间：
2008
影响因子：
2.3
通讯作者：
M. Charlton
中科院分区：
文献类型：
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作者：
Urška Demšar;A. Fotheringham;M. Charlton
本文探讨了空间统计方法-地理加权回归（GWR）-与地理视觉分析探索相结合，以帮助理解复杂的时空过程的潜力。这是通过将组合的统计-探索方法应用于模拟数据集来完成的，其中在空间和时间上控制回归参数的行为。各种复杂的时空过程是通过时空（即时空）变化的参数，其值是已知的。我们的任务是看看所提出的方法是否可以仅从数据中揭示这些复杂的过程。实验结果证实，该组合方法可以成功地识别时空模式的本地GWR参数估计，对应于原始参数的受控行为。
The paper examines the potential for combining a spatial statistical methodology – Geographically Weighted Regression (GWR) – with geovisual analytical exploration to help understand complex spatio-temporal processes. This is done by applying the combined statistical – exploratory methodology to a simulated data set in which the behaviour of regression parameters was controlled across space and time. A variety of complex spatio-temporal processes was captured through space-time (i.e. as spatio-temporal) varying parameters whose values were known. The task was to see if the proposed methodology could uncover these complex processes from the data alone. The results of the experiment confirm that the combined methodology can successfully identify spatio-temporal patterns in the local GWR parameter estimates that correspond to the controlled behaviour of the original parameters.