Abstract
GIScience inherits the spatial analysis tradition of geography. Given that "spatial is special", GIScience needs to highlight spatial effects when constructing methods for geographical analysis. The research presents an explicit definition of spatial effect. By formalizing core GIScience concepts including space, location, field, distance, and region, we identify four types of spatial effects, namely spatial heterogeneity effect, neighbor effect in spatial dependence, distance decay effect in spatial interactions, and scale effect in spatial zoning. A unified framework is constructed to cover the four spatial effects based on the inherent linkages among them. We argue that spatial heterogeneity effect is the most fundamental one. While spatial dependence and spatial interaction are two basic geographical processes that represent the second-order relationships between two locations, neighbor effect and distance decay effect reflect the impacts of space. Scale effect is raised when aggregating attributes using regional units. Hence, the four types of effects form a hierarchical system. From a methodological perspective, this paper summaries related GIScience tools that implement different effects, and emphasizes the value of geospatial artificial intelligence for revealing and quantifying spatial effects.
| Translated title of the contribution | On spatial effects in geographical analysis |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 517-531 |
| Number of pages | 15 |
| Journal | Dili Xuebao/Acta Geographica Sinica |
| Volume | 78 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2023 |
Bibliographical note
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Keywords
- distance decay effect
- geographical analysis
- geospatial artificial intelligence
- neighbor effect
- scale effect
- spatial effect
- spatial heterogeneity effect