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Space-Time Cube×Mekân-Zaman Çekirdek Yoğunluk Tahmini (ST-KDE)×
AlanHuman GeographyMekânsal analiz
AileProcess / pipelineRegression model
Köken yılı19702010 (space-time extension); 1956 (KDE origin)
KökenTorsten Hägerstrand (time geography); cube popularized by Menno-Jan KraakNakaya & Yano (space-time formulation); KDE foundation by Rosenblatt and Parzen
TürSpatiotemporal data structure and visualization frameworkNon-parametric density estimation
Seminal kaynakHägerstrand, T. (1970). What about people in regional science? Papers of the Regional Science Association, 24(1), 6–21. DOI ↗Nakaya, T., & Yano, K. (2010). Visualising crime clusters in a space-time cube: An exploratory data-analysis approach using space-time kernel density estimation and scan statistics. Transactions in GIS, 14(3), 223-239. DOI ↗
Diğer adlarHägerstrand Space-Time Cube, Space-Time Aquarium, Spatiotemporal Cube, Time-Geographic CubeST-KDE, spatiotemporal kernel density estimation, space-time KDE, 3D kernel density estimation
İlişkili45
ÖzetThe space-time cube is a framework from time geography for representing and analyzing phenomena that move and change over both space and time. Two horizontal axes carry geographic location and a vertical axis carries time, so each observation becomes a point in a three-dimensional x–y–t volume and a moving object traces a continuous 'space-time path' through the cube. Introduced conceptually by Torsten Hägerstrand in 1970 and turned into a practical analytic and cartographic tool by Menno-Jan Kraak, it underpins modern spatiotemporal hot-spot and trajectory analysis.Space-Time Kernel Density Estimation extends classical KDE into three dimensions — two spatial and one temporal — to reveal how the intensity of point events (crimes, accidents, disease cases) varies continuously across both geographic space and time. It produces a smooth probabilistic surface that highlights where and when events concentrate most densely.
ScholarGateVeri seti
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  1. v1
  2. 2 Kaynaklar
  3. PUBLISHED

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ScholarGateYöntem Karşılaştırma: Space-Time Cube · Space-Time Kernel Density Estimation. 2026-06-24 tarihinde şu adresten erişildi: https://scholargate.app/tr/compare