Titlebook: New Thinking in GIScience; Bin Li,Xun Shi,Hui Lin Book 2022 Higher Education Press 2022 GIS (Geographical Information System).GISci.GISc.R

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書目名稱New Thinking in GIScience網絡公開度學科排名




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書目名稱New Thinking in GIScience年度引用學科排名




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書目名稱New Thinking in GIScience讀者反饋學科排名

Metastasis

From Representation to Geocomputation: Some Theoretical Accounts of Geographic Information Science,pply existing ones from other disciplines or surround conceptual, logical, or ontological arguments. The lack of a well-defined theory for geographic information presents an excellent research opportunity. Theories for statistics and machine learning are exemplars.

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Neutral-Spine

Prospects on Causal Inferences in GIS,mising concepts. Spatially explicit causal models can be developed by integrating spatial statistical models with existing computational and statistical models for causal analysis. There are limits to quantitative approaches to causal inferences; a comprehensive causal analysis should include qualitative analysis.

evince

Deep Learning of Big Geospatial Data: Challenges and Opportunities,tiotemporal data and discusses the recent progresses in addressing them with a particular focus on the promises of deep learning and GeoAI methods. The chapter is then concluded with a discussion on possible future directions.

兇殘

GIScience from Viewpoint of Information Science,al information is a special type of information. Then, it is pointed out that the foundation of developing GIScience as a branch of information science has been laid down already and it is time to develop theories behind such a science. This article provides an insight into the future development of GIScience.

BLAZE

The Bottom-Up Approach and De-mapping Direction of GIS,ms of classification, assessment, estimation, and prediction to illustrate the distinction between the top-down and bottom-up approaches. We also point out that an outcome of this new expansion of GIS is that mapping is receding from its center-stage position in GIS.