ELSA: a new local indicator for spatial association

There are several local indicators of spatial association (LISA) that allow exploration of local patterns in spatial data. Despite numerous situations where categorical variables are encountered, few attempts have been devoted to the development of methods to explore the local spatial pattern in cat...

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Main Authors: Hamm, Nicholas A.S., Naimi, Babak, Groen, Thomas
Format: Conference or Workshop Item
Language:English
Published: 2021
Subjects:
Online Access:https://eprints.nottingham.ac.uk/65130/
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author Hamm, Nicholas A.S.
Naimi, Babak
Groen, Thomas
author_facet Hamm, Nicholas A.S.
Naimi, Babak
Groen, Thomas
author_sort Hamm, Nicholas A.S.
building Nottingham Research Data Repository
collection Online Access
description There are several local indicators of spatial association (LISA) that allow exploration of local patterns in spatial data. Despite numerous situations where categorical variables are encountered, few attempts have been devoted to the development of methods to explore the local spatial pattern in categorical data. To our knowledge, there is no indicator of local spatial association that can be used for both continuous and categorical data. We introduce ELSA, which can be used for exploring and testing local spatial association for continuous and categorical variables. We provide the R-package elsa for making these computations.
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institution University of Nottingham Malaysia Campus
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publishDate 2021
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spelling nottingham-651302021-04-20T06:28:55Z https://eprints.nottingham.ac.uk/65130/ ELSA: a new local indicator for spatial association Hamm, Nicholas A.S. Naimi, Babak Groen, Thomas There are several local indicators of spatial association (LISA) that allow exploration of local patterns in spatial data. Despite numerous situations where categorical variables are encountered, few attempts have been devoted to the development of methods to explore the local spatial pattern in categorical data. To our knowledge, there is no indicator of local spatial association that can be used for both continuous and categorical data. We introduce ELSA, which can be used for exploring and testing local spatial association for continuous and categorical variables. We provide the R-package elsa for making these computations. 2021-04-06 Conference or Workshop Item PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/65130/1/HammEtAl_GISRUK2021_paper_58.pdf Hamm, Nicholas A.S., Naimi, Babak and Groen, Thomas (2021) ELSA: a new local indicator for spatial association. In: The 29th Annual GIS Research UK Conference (GISRUK), 14-16 April 2021, Cardiff, Wales, UK (Online). LISA categorical data hierarchical classification continuous data http://doi.org/10.5281/zenodo.4665865
spellingShingle LISA
categorical data
hierarchical classification
continuous data
Hamm, Nicholas A.S.
Naimi, Babak
Groen, Thomas
ELSA: a new local indicator for spatial association
title ELSA: a new local indicator for spatial association
title_full ELSA: a new local indicator for spatial association
title_fullStr ELSA: a new local indicator for spatial association
title_full_unstemmed ELSA: a new local indicator for spatial association
title_short ELSA: a new local indicator for spatial association
title_sort elsa: a new local indicator for spatial association
topic LISA
categorical data
hierarchical classification
continuous data
url https://eprints.nottingham.ac.uk/65130/
https://eprints.nottingham.ac.uk/65130/