Abstract
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.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China (No. 41461103) and a research fund of Yunnan University (C176240210019).
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Communicated by: H. Babaie
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Software files
The GIS add-in can be downloaded from http://www.srees.ynu.edu.cn/info/1040/2178.htm.
Right click the link to ArcMapAddin5.rar to download the archive, then extract files from the archive to get the add-in file “ArcMapAddin.esriAddin”. To install the add-in for ArcMap 10.x, users can open ArcMap, go to the Customize menu, then select Add-in Manager. Click the Options tab in the Add-in Manager, then click the Add Folder button to add the folder for “ArcMapAddin.esriAddin”. Click the Customize button at the bottom of the Add-in Manager, then select the second tab “Commands”. Select “Add-in Controls” in the Categories list, then drag “SMKDBSCAN” from the Commands list to an ArcMap toolbar. Click the SMKDBSCAN icon to start using the add-in.
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Xia, J., Li, J., Dong, P. et al. An ArcGIS add-in for spatiotemporal data mining in climate data. Earth Sci Inform 13, 185–190 (2020). https://doi.org/10.1007/s12145-019-00404-0
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DOI: https://doi.org/10.1007/s12145-019-00404-0