scholarly journals GIS for Science: Applying Mapping and Spatial Analytics

2021 ◽  
Vol 87 (2) ◽  
pp. 75-76
Author(s):  
M. Kathryn Rocheford
Keyword(s):  
Spatial Analytics

scholarly journals Unified Spatial Analytics from Heterogeneous Sources with Amazon Redshift

2020 ◽  
Author(s):  
Nemanja Borić ◽  
Hinnerk Gildhoff ◽  
Menelaos Karavelas ◽  
Ippokratis Pandis ◽  
Ioanna Tsalouchidou
Keyword(s):  
Spatial Analytics

scholarly journals The locative imaginary: Classification, context and relevance in location analytics

2019 ◽  
Vol 68 (3) ◽  
pp. 641-658
Author(s):  
Harrison Smith
Keyword(s):  
Data Analytics ◽  
Urban Environments ◽  
Third Party ◽  
Future Research ◽  
The Social ◽  
Spatial Analytics ◽  
Recent Developments ◽  
Social Shaping ◽  
Cultural Economies ◽  
And Performance

The location analytics industry has the potential to stimulate critical sociological discussions concerning the credibility of data analytics to enact new spatial classifications and metrics of socio-economic phenomena. Key debates in the sociology of geodemographics are revisited in this article in light of recent developments in algorithmic culture to understand how location analytics impacts the structural contexts of classification and relevance in digital marketing. It situates this within a locative imaginary, where marketers are experimenting with consolidating the epistemes of behavioural targeting, classification and performance evaluation in urban environments through spatial analytics of movement. This opens up future research into the political and cultural economies of relevance in media landscapes and the social shaping of valuable subjects by third-party data brokers and analytics platforms that have become matters of public and regulatory concern.

Improving service responsiveness and delivery efficiency of retail networks

2017 ◽  
Vol 45 (3) ◽  
pp. 271-291 ◽  
Author(s):  
Prem Chhetri ◽  
Booi Kam ◽  
Kwok Hung Lau ◽  
Brian Corbitt ◽  
France Cheong
Keyword(s):  
Service Delivery ◽  
Spatial Clustering ◽  
Substantial Reduction ◽  
Market Area ◽  
Content Type ◽  
Segmentation Analysis ◽  
Spatial Analytics ◽  
Market Areas ◽  
Delivery Efficiency

Purpose The purpose of this paper is to explore how a retail distribution network can be rationalised from a spatial perspective to improve service responsiveness and delivery efficiency. Design/methodology/approach This paper applies spatial analytics to examine variability of demand, both spatially and from a service delivery perspective, for an auto-parts retail network. Spatial analytics are applied to map the location of stores and customers to represent demand and service delivery patterns and to delineate market areas. Findings Results show significant spatial clustering in customer demand; whilst the delivery of products to customers, in contrast, is spatially dispersed. There is a substantial gap between revenue generated and costs. Market area analysis shows significant overlap, whereby stores compete with each other for business. In total, 80 per cent of customers can be reached within a 15-minute-radius, whilst only 20 per cent lies outside the market areas. Segmentation analysis of customers, based on service delivery, also shows the prevalence of the Pareto principle or 80:20 rule whereby 80 per cent of the revenue is generated by 20 per cent of customers. Practical implications Spatially integrated strategies are suggested to improve the efficiency of the retail network. It is recommended that less accessible and unprofitable customers could be either charged extra delivery cost or outsourced without the risk of a substantial reduction in revenue or quality of service delivery. Originality/value Innovative application of spatial analytics is used to analyse and visualise unit-record sales data to generate practical solutions to improve retail network responsiveness and operational efficiency.

Geodemographies of Breastfeeding Support

2020 ◽  
pp. 089033442094141 ◽  
Author(s):  
Tony H. Grubesic ◽  
Kelly M. Durbin
Keyword(s):  
Support Groups ◽  
Spatial Data ◽  
Local Level ◽  
Spatial Data Analysis ◽  
Breastfeeding Support ◽  
Peer Counselors ◽  
Support Organizations ◽  
Support Resources ◽  
Spatial Analytics ◽  
La Leche League

Background Mother-to-mother breastfeeding support organizations provide important information and guidance for helping mothers initiate and maintain breastfeeding, postpartum. However, the availability of this support is limited by a constellation of barriers, including race, culture, socioeconomic status, and geography. Research aims To identify the geodemographic composition of communities where breastfeeding support was available from the mother-to-mother support organizations Breastfeeding USA and La Leche League, identify underlying issues of equity, and highlight locations where more support resources may be needed. Methods The locations of mother-to-mother support meetings were collected by ZIP code ( N = 180) and were combined with a geodemographic database and exploratory spatial data analysis to explore the compositional characteristics of communities served ( N = 1,173). Results Significant gaps in the geographic distribution of breastfeeding support existed. While many metropolitan areas benefited from numerous mother-to-mother support groups and peer counselors, the geographic footprint of this support favored communities that were white, affluent, and suburban. Conclusion Spatial analytics combined with geodemographic analysis provide a unique perspective into the diverse landscape of mother-to-mother breastfeeding support groups at a local level. Our results highlighted inequities in the distribution of support provided and prescriptive guidance regarding where more resources may be needed.

scholarly journals PostGIS-Based Heterogeneous Sensor Database Framework for the Sensor Observation Service

2012 ◽  
Vol 8 ◽  
pp. 55-72
Author(s):  
Ikechukwu Maduako
Keyword(s):  
Web Services ◽  
Work Load ◽  
Flat File ◽  
Time Dynamic ◽  
Remote Sensors ◽  
Remote Sensor ◽  
Spatial Analytics ◽  
In Situ Sensor ◽  
Geospatial Web Services

Environmental monitoring and management systems in most cases deal with models and spatial analytics that involve the integration of in-situ and remote sensor observations. In-situ sensor observations and those gathered by remote sensors are usually provided by different databases and services in real-time dynamic services such as the Geo-Web Services. Thus, data have to be pulled from different databases and transferred over the network before they are fused and processed on the service middleware. This process is very massive and unnecessary communication and work load on the service. Massive work load in large raster downloads from flat-file raster data sources each time a request is made and huge integration and geo-processing work load on the service middleware which could actually be better leveraged at the database level. In this paper, we propose and present a heterogeneous sensor database framework or model for integration, geo-processing and spatial analysis of remote and in-situ sensor observations at the database level.  And how this can be integrated in the Sensor Observation Service, SOS to reduce communication and massive workload on the Geospatial Web Services and as well make query request from the user end a lot more flexible.

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