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Everything about Spatial analysis

Techniques to study geometric data

Spatial analysis is any of the formal techniques which study entities using their topological, geometric, or geographic properties, primarily used in urban design. Spatial analysis includes a variety of techniques using different analytic approaches, especially spatial statistics. It may be applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, or to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures. In a more restricted sense, spatial analysis is geospatial analysis, the technique applied to structures at the human scale, most notably in the analysis of geographic data. It may also applied to genomics, as in transcriptomics data, but is primarily for spatial data. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Spatial analysisA 5-minute orientation
  2. Skim a recent paper: Squidpy: a scalable framework for spatial omics analysisInfluential work since 2022
  3. Pick up a classic book: Adjustment computationsThe most-reprinted book on the subject
  4. Read the landmark paper: Google Earth Engine: Planetary-scale geospatial analysis for everyoneCited 13,712 times
  5. Go sideways: Modifiable areal unit problemA closely related topic
  6. Go sideways: Boundary problem (spatial analysis)A closely related topic

📖 Definitions

No dictionary entry for this exact phrase.

🗂️ The subject at a glance

  1. History
  2. Fundamental issues
  3. Types
  4. Geospatial and hydrospatial analysis

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics