An ArcGIS add-in for spatiotemporal data mining in climate data
| Autor: | Jisheng Xia, Kecheng Yang, Pinliang Dong, Jinne Li |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
DBSCAN
Geographic information system Environmental modelling 010504 meteorology & atmospheric sciences business.industry Computer science ArcObjects 010502 geochemistry & geophysics computer.software_genre 01 natural sciences User input Partition (database) Spatial clustering General Earth and Planetary Sciences Data mining business computer 0105 earth and related environmental sciences |
| Zdroj: | Earth Science Informatics. 13:185-190 |
| ISSN: | 1865-0481 1865-0473 |
| DOI: | 10.1007/s12145-019-00404-0 |
| Popis: | Spatiotemporal data mining has many important applications in environmental modelling. This paper introduces a modified algorithm for spatiotemporal data mining based on density-based spatial clustering of applications with noise (DBSCAN). Based on the modified algorithm, a geographic information system (GIS) add-in was developed using ArcObjects and C#, and is freely available for download. Compared with some existing methods, the new method can perform automated detection of spatiotemporal clusters using limited user input parameters. The application of the add-in was demonstrated using summer temperature data collected from 104 weather stations in southwest China from 1961 to 2011. The results suggest that the modified algorithm can provide more detailed partition of temperature zones compared with some existing methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink