https://scholars.lib.ntu.edu.tw/handle/123456789/393480
標題: | A GIS tool for spatiotemporal modeling under a knowledge synthesis framework | 作者: | HWA-LUNG YU Ku, Shang-Chen Kolovos, Alexander |
關鍵字: | BME; Prediction; QGIS; Spatiotemporal analysis; Stochastic processes | 公開日期: | 2015 | 來源出版物: | Stochastic Environmental Research and Risk Assessment | 摘要: | In recent years, there has been a fast growing interest in the space–time data processing capacity of Geographic Information Systems (GIS). In this paper we present a new GIS-based tool for advanced geostatistical analysis of space–time data; it combines stochastic analysis, prediction, and GIS visualization technology. The proposed toolbox is based on the Bayesian Maximum Entropy theory that formulates its approach under a mature knowledge synthesis framework. We exhibit the toolbox features and use it for particulate matter spatiotemporal mapping in Taipei, in a proof-of-concept study where the serious preferential sampling issue is present. The proposed toolbox enables tight coupling of advanced spatiotemporal analysis functions with a GIS environment, i.e. QGIS. As a result, our contribution leads to a more seamless interaction between spatiotemporal analysis tools and GIS built-in functions; and utterly enhances the functionality of GIS software as a comprehensive knowledge processing and dissemination platform. © 2015, Springer-Verlag Berlin Heidelberg. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958124864&doi=10.1007%2fs00477-015-1078-5&partnerID=40&md5=001ecf6ec5d48536e5eeabb6364fdef8 http://scholars.lib.ntu.edu.tw/handle/123456789/393480 |
DOI: | 10.1007/s00477-015-1078-5 |
顯示於: | 生物環境系統工程學系 |
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