Identifying patterns in spatial information: A survey of methods

Shekhar, Shashi; Evans, Michael R.; Kang, James M.; Mohan, Pradeep

doi:10.1002/widm.25

Cited by 141 publications

(90 citation statements)

References 80 publications

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“…A multilevel Association Rule has been generated to find association between the data in a large database. [29] explain some patterns that are in spatial time series data.…”

Section: Geo-referenced Antecedent and Georeferenced Consequentmentioning

confidence: 98%

An Integrated Approach of GIS and Spatial Data Mining in Big Data

Goyal¹,

Sharma²,

Joshi³

2017

IJCA

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An explosive growth of spatial data has been demanding to Spatial Data Mining (SDM) technology, emerging as a innovative area for spatial data analysis. Geographical Information System (GIS) contains heterogeneous data from multidisciplinary sources in different formats. Geodatabase is the repository of GIS data, representing spatial attributes, with respect to location. Rapidly increasing satellite imagery and geodatabases generates huge data volume related to real world and natural resources such as soil, water, temperature, vegetation, forest cover etc. Inferring information from geodatabases has gained value using computational algorithms. The intent of this paper is to introduce with GIS, and spatial data mining, GIS and SDM tools, algorithmic approaches, issues and challenges, and role of spatial association rule mining in big data of GIS.

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“…A multilevel Association Rule has been generated to find association between the data in a large database. [29] explain some patterns that are in spatial time series data.…”

Section: Geo-referenced Antecedent and Georeferenced Consequentmentioning

confidence: 98%

An Integrated Approach of GIS and Spatial Data Mining in Big Data

Goyal¹,

Sharma²,

Joshi³

2017

IJCA

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“…Obviously, the quantitative data fields of different physical domains should be converted into a common measurable form before processing, for example, by various kinds of scaling, normalization or filtering (Ding and Meng, 2014). Now the purpose-oriented data fusion can be performed in a variety of ways such as visual analysis using special multidimensional visualization (Steed et al, 2013), geospatial and topological ontologies development (Du et al, 2011), applying geostatistical models, classifiers and anomaly detectors (Shekhar et al, 2011) and other. Advantages of mentioned methods are objectivity, logic consistency, easy algorithmization, wide possibilities of re-analysis.…”

Section: High-level Geospatial Analysis Based On Data Fusion For Smarmentioning

confidence: 99%

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

Popov¹,

Fedorovsky²,

Stankevich³

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The approach to implementing the remote sensing technologies and geospatial modelling for smart city support is presented. The hierarchical structure and basic components of the smart city information support subsystem are considered. Some of the already available useful practical developments are described. These include city land use planning, urban vegetation analysis, thermal condition forecasting, geohazard detection, flooding risk assessment. Remote sensing data fusion approach for comprehensive geospatial analysis is discussed. Long-term city development forecasting by Forrester -Graham system dynamics model is provided over Kiev urban area.

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“…A binarized approach for classification of data is obtained in order to perform online classification techniques, which finally results in identification of abnormal segments. Such forms of application can be seen in the work carried out by [34], [35]. …”

Section: Identification Of Abnormal Objectsmentioning

confidence: 99%

Insights to Video Analytic Modelling Approach with Future Line of Research

Chandra¹,

Reddy²

2016

IJCA

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The area of Video analytics has made some significant improvement due to advancement in image processing and datamining techniques. However, the inclination is still towards image contents and less to mined contents owing to many unsolved issues. Although concept of mining is more than 2 decade old, but mining approaches are yet to be standardized in the area of video surveillance system. With evolution of newer set of challenges in video capturing, existing mining models finds itself less applicable due to unstructured format of dynamic frames. Hence, this paper discusses about video analytics and presents a brief discussion of frequently used mining approaches in video as well as discussed some recent studies in this direction in order to scale the degree of effectiveness in existing system. The paper also presents research gap and provided solution as future line of research as a possible way to overcome the research gap.

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Identifying patterns in spatial information: A survey of methods

Cited by 141 publications

References 80 publications

An Integrated Approach of GIS and Spatial Data Mining in Big Data

An Integrated Approach of GIS and Spatial Data Mining in Big Data

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

Insights to Video Analytic Modelling Approach with Future Line of Research

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