ISSN: 1387-5868

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Spatial Cognition and Computation Q2 Unclaimed

Taylor and Francis Ltd. United States

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Spatial Cognition and Computation is a journal indexed in SJR in Modeling and Simulation and Computer Vision and Pattern Recognition with an H index of 44. It has an SJR impact factor of 0,343 and it has a best quartile of Q2. It has an SJR impact factor of 0,343.

Type: Journal

Type of Copyright:

Languages:

Open Access Policy:

Type of publications:

Publication frecuency: -

Categories: Computer Graphics and Computer-Aided Design (Q2) Earth-Surface Processes (Q2) Computer Vision and Pattern Recognition (Q3) Modeling and Simulation (Q3) Experimental and Cognitive Psychology (Q4)

Price

- €

Inmediate OA

NPD

Embargoed OA

- €

Non OA

Metrics

0,343

SJR Impact factor

44

H Index

16

Total Docs (Last Year)

36

Total Docs (3 years)

912

Total Refs

80

Total Cites (3 years)

36

Citable Docs (3 years)

2.67

Cites/Doc (2 years)

57.0

Ref/Doc

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Journal of Computational Science Q2
BMC Systems Biology Q2
Combustion Theory and Modelling Q2
Cellular and Molecular Bioengineering Q2
Journal of Physics A: Mathematical and Theoretical Q2

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Aims and Scope

Best articles by citations

Human Shortcut Performance in a Computer-Simulated Maze: A Comparative Study

Gaze behavior during incidental and intentional navigation in an outdoor environment

Path Complexity Does Not Impair Visual Path Integration

Gestures Accompanying Verbal Route Directions: Do They Point to a New Avenue for Examining Spatial Representations?

Route Aware Maps: Multigranular Wayfinding Assistance

Mental Representations Acquired Through Language: A Study of Orientation Specificity

Analyzing Spatio-Temporal Patterns and Their Evolution via Sequence Alignment

Editorial

Path Integration During a Neighborhood Walk

Topological and Geometric Operators for Ontological Classification of Vague Geographic Concepts

Cognitive Evidence of Vagueness Associated with some Linguistic Terms in Descriptions of Spatial Relations

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Discovering Order in Chaos: Using a Heuristic Ontology to Derive Spatio-Temporal Sequences for Cadastral Data

Vague Reference and Approximating Judgments

Inferencing From Spatial Information

Vague Reference and Approximating Judgments

Granularity-sensitive Spatial Attributes

Learning to Reach to Locations Encoded from Imaging Displays

Granularity-sensitive Spatial Attributes

Coordinating Gesture, Word, and Diagram: Explanations for Experts and Novices

Is Route Learning More Than Serial Learning?

Qualitative Extents for Spatio-Temporal Granularity

'Fine-to-Coarse' Route Planning and Navigation in Regionalized Environments