An index for quantifying geometric point disorder in geospatial applications
| Autor: | R. Sky Jones, Henrique G. Momm |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Curvilinear coordinates
Data processing Geospatial analysis business.industry Computer science 0208 environmental biotechnology Pattern recognition 02 engineering and technology 010502 geochemistry & geophysics computer.software_genre 01 natural sciences 020801 environmental engineering Statistical classification Metric (mathematics) Point (geometry) Artificial intelligence Computers in Earth Sciences Wallpaper group business Spatial analysis computer 0105 earth and related environmental sciences Information Systems |
| Zdroj: | Computers & Geosciences. 151:104756 |
| ISSN: | 0098-3004 |
| Popis: | Many techniques have been developed to quantify different conceptualizations of self-interaction and patterns within spatial data. We propose a new metric and related algorithm that describes the geometric spatial disorder of geographic point sets, the “Index of Disorder” (IoD). The IoD algorithm was applied to synthetic and natural datasets and was shown to be able to differentiate between areas of high spatial disorder (randomly placed points) and low spatial disorder (e.g., curvilinear grids, wallpaper groups, and other repeating patterns). Because the IoD is a quantitative metric, it can be used on its own as an aid for identifying areas of unusually high or low spatial disorder or as enrichment for machine learning classification algorithms. |
| Databáze: | OpenAIRE |
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