Geospatial Theories and Methods

46 innovative methods across 26 research themes · 12 open-source R packages · 260,000+ downloads

Members

Yongze Song
Yongze Song
Supervisor
Yongze Song
Associate Professor
Curtin University
Email: yongze.song@curtin.edu.au
Homepage: yongzesong.com

Australian Young Tall Poppy Science Award winner
Fellow of Royal Geographical Society (UK)
Fellow of Harvard Spatial Data Lab (US)
Fellow of DAAD AInet (Germany)
Special Issue Editor (SIE) & Associate Editor – International Journal of Applied Earth Observation and Geoinformation
Associate Editor – GIScience & Remote Sensing
Special Issue Editor (SIE) – Geomatica
Editor – Geoscientific Model Development
Associate Editor – All Earth
Editor – Journal of Spatial Science
Zehua Zhang
Zehua Zhang
RID · HSA · RGD · GIGNN · LPI
Yang Li
Yang Li
GPI · LESH
Rui Qu
Rui Qu
LPA
Rui Qu
Research Associate:
Curtin University
PhD: Chengdu University of Technology
Email: rui.qu@curtin.edu.au
Xinyue Yang
Xinyue Yang
Anisotropy
Lai Chen
Lai Chen
ST-MST
Lab
Geospatial Intelligence Lab
PART I Spatial Prediction via Spatial Feature Modelling
1. Spatial fields
Value + Pattern + Distribution Yongze Song GCF
4. Spatial autocorrelation
8. Generalized heterogeneity
10. Spatial singularity
12. Spatial fusion
PART II Spatial Heterogeneity and Driver Analysis
PART III Spatial Urban Methods: Patterns, Accessibility, and Decisions

Important Concepts in Geospatial Analysis

  1. Spatial fields: generalized covariate field
  2. Spatial validation: degree of spatial interpretability, degree of geocomplexity, generalised spatial error
  3. Spatial association: second-dimension spatial association, explainable second-dimension spatial association
  4. Spatial autocorrelation: heterogeneous spatial autocorrelation
  5. Geocomplexity: geocomplexity
  6. Spatial outliers: second-dimension outliers, second-dimension outlier-driven heterogeneity, local outliers for context-aware prediction
  7. Geostatistics or kriging: segment-based regression kriging, focal-feature regression kriging
  8. Generalized heterogeneity: generalized heterogeneity
  9. Geographical similarity: geographically optimal similarity, pattern similarity learning
  10. Spatial singularity: singularity regression kriging
  11. Spatial graph network: geographically informed graph neural network, dynamic spatiotemporal graph network
  12. Spatial fusion: spatial context-aware fusion
  13. Spatial transformer: spatiotemporal multiscale transformer
  14. Spatial heterogeneity: spatial stratified heterogeneity, local stratified heterogeneity, geographically optimal zones-based heterogeneity, locally explained heterogeneity, spatial stratified heterogeneity family, wavelet geographically weighted regression
  15. Robust spatial models: robust geographical detector
  16. Spatial interaction: robust interaction detector, interactive detector for spatial association, geographical pattern interaction, local effects of pattern interaction
  17. Causal discovery: temporal empirical dynamic modeling, geographical cross mapping cardinality
  18. Spatial anisotropy: spatial irregular anisotropy
  19. Spatial path analysis: local pathways of association
  20. Spatial segmentation: spatial heterogeneity-based segmentation, gaussian mixture segmentation
  21. Spatial unmixing: spatio-temporal unmixing with heterogeneity
  22. Spatial accessibility: D2SFCA spatiotemporal accessibility
  23. Spatial trade-off: spatial trade-off relation, dynamic trade-off, spatial delta model
  24. Spatial boundary: spatial big data-based city redefinition
  25. Spatial decision-making: MFSD spatial decision making
  26. Spatial optimization: spatiotemporal particle swarm optimization for cost allocation
  27. Advanced geographical detector models: Optimal Parameters-based Geographical Detector (OPGD), Robust Interaction Detector (RID), Local Indicator of Stratified Power (LISP), Geographically Optimal Zones-based Heterogeneity (GOZH), Geographical Pattern Interaction (GPI), Interactive Detector for Spatial Associations (IDSA), Robust Geographical Detector (RGD), Locally Explained Heterogeneity model (LESH), Generalized Heterogeneity Model (GHM), Heterogeneous Spatial Autocorrelation (HSA)

Open-Source Geospatial Software (260,000+ downloads)

Optimal Parameters-based Geographical Detectors (OPGD) for spatial factor exploration. R package "GD" | publication | online OPGD calculator
– Highly Cited Paper · No. 1 Most Cited Article in GIScience & Remote Sensing in 2021–2023
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Geographically Optimal Similarity (GOS) for spatial prediction. R package "geosimilarity" | publication | online GOS calculator
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Second-Dimension Spatial Association (SDA) for spatial prediction. R package "SecDim" | publication
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Interactive Detector for Spatial Association (IDSA) for spatial factor exploration. R package "IDSA" | publication
– No. 2 Most Cited Article in IJGIS in 2021–2023
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Homogenous Segmentation (HS) for segmenting spatial lines data. R package "HS" | publication
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Segment-based Kriging (SK) for spatial prediction. R package "SK" | publication
– Highly Cited Paper
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Energy Decomposition Analysis (EDA) for analysing carbon emission factors. R package "EDA" | publication
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SDGdetector: Detecting Sustainable Development Goals (SDGs) in Text. R package "SDGdetector" | publication
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gdverse: Analysis of Spatial Stratified Heterogeneity. R package "gdverse" | publication
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localsp: Local Indicator of Stratified Power. R package "localsp" | publication
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cisp: A Correlation Indicator Based on Spatial Patterns. R package "cisp" | publication
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