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Update reference DOIs and add PySAL GA reference #166

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Jun 17, 2021
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Update reference DOIs and add PySAL GA reference #166

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update & add JOSS reference DOIs
jGaboardi Jun 17, 2021
afea79e
add PySAL2021GA ref
jGaboardi Jun 17, 2021
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60 changes: 39 additions & 21 deletions paper/paper.bib
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Expand Up @@ -6,21 +6,22 @@ @article{assunccao2006efficient
number={7},
pages={797--811},
year={2006},
publisher={Taylor \& Francis}
publisher={Taylor \& Francis},
doi={10.1080/13658810600665111}
}

@article{duque2012max,
author = {Duque, Juan C. and Anselin, Luc and Rey, Sergio J.},
title = {THE MAX-P-REGIONS PROBLEM*},
journal = {Journal of Regional Science},
volume = {52},
number = {3},
pages = {397--419},
doi = {https://doi.org/10.1111/j.1467-9787.2011.00743.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-9787.2011.00743.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1467-9787.2011.00743.x},
abstract = {ABSTRACT In this paper, we introduce a new spatially constrained clustering problem called the max-p-regions problem. It involves the clustering of a set of geographic areas into the maximum number of homogeneous regions such that the value of a spatially extensive regional attribute is above a predefined threshold value. We formulate the max-p-regions problem as a mixed integer programming (MIP) problem, and propose a heuristic solution.},
year = {2012}
author={Duque, Juan C. and Anselin, Luc and Rey, Sergio J.},
title={THE MAX-P-REGIONS PROBLEM*},
journal={Journal of Regional Science},
volume={52},
number={3},
pages={397--419},
doi={10.1111/j.1467-9787.2011.00743.x},
url={https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-9787.2011.00743.x},
eprint={https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1467-9787.2011.00743.x},
abstract={ABSTRACT In this paper, we introduce a new spatially constrained clustering problem called the max-p-regions problem. It involves the clustering of a set of geographic areas into the maximum number of homogeneous regions such that the value of a spatially extensive regional attribute is above a predefined threshold value. We formulate the max-p-regions problem as a mixed integer programming (MIP) problem, and propose a heuristic solution.},
year={2012}
}

@article{koopmans1949optimum,
Expand All @@ -29,7 +30,8 @@ @article{koopmans1949optimum
journal={Econometrica: Journal of the Econometric Society},
pages={136--146},
year={1949},
publisher={JSTOR}
publisher={JSTOR},
doi={10.2307/1907301}
}

@article{miller1960integer,
Expand All @@ -40,7 +42,8 @@ @article{miller1960integer
number={4},
pages={326--329},
year={1960},
publisher={ACM New York, NY, USA}
publisher={ACM New York, NY, USA},
doi={10.1145/321043.321046}
}

@article{murray2019contemporary,
Expand All @@ -49,7 +52,8 @@ @article{murray2019contemporary
journal={Omega},
pages={102176},
year={2019},
publisher={Elsevier}
publisher={Elsevier},
doi={10.1016/j.omega.2019.102176}
}

@article{wei2020efficient,
Expand All @@ -58,7 +62,8 @@ @article{wei2020efficient
journal={International Journal of Geographical Information Science},
pages={1--17},
year={2020},
publisher={Taylor \& Francis}
publisher={Taylor \& Francis},
doi={10.1080/13658816.2020.1759806}
}

@article{openshaw1977geographical,
Expand All @@ -67,7 +72,8 @@ @article{openshaw1977geographical
journal={Transactions of the Institute of British Geographers},
pages={459--472},
year={1977},
publisher={JSTOR}
publisher={JSTOR},
doi={10.2307/622300}
}

@article{openshaw1995algorithms,
Expand All @@ -78,7 +84,8 @@ @article{openshaw1995algorithms
number={3},
pages={425--446},
year={1995},
publisher={SAGE Publications Sage UK: London, England}
publisher={SAGE Publications Sage UK: London, England},
doi={10.1068/a270425}
}

@incollection{rey2010pysal,
Expand All @@ -87,7 +94,8 @@ @incollection{rey2010pysal
booktitle={Handbook of applied spatial analysis},
pages={175--193},
year={2010},
publisher={Springer}
publisher={Springer},
doi={10.1007/978-3-642-03647-7_11}
}

@article{rey2015open,
Expand All @@ -98,12 +106,22 @@ @article{rey2015open
number={2},
pages={815--836},
year={2015},
publisher={Multidisciplinary Digital Publishing Institute}
publisher={Multidisciplinary Digital Publishing Institute},
doi={10.3390/ijgi4020815}
}

@article{wolf2020,
title={Spatially-encouraged spectral clustering: a technique for blending map typologies and regionalization},
author={Wolf, Levi},
url= {https://osf.io/yzt2p/}
url= {https://osf.io/yzt2p/},
doi={10.31219/osf.io/yzt2p}
}

@article{Rey2021,
author={Rey, Sergio J. and Anselin, Luc and Amaral, Pedro and Arribas-Bel, Dani and Cortes, Renan Xavier and Gaboardi, James David and Kang, Wei and Knaap, Elijah and Li, Ziqi and Lumnitz, Stefanie and Oshan, Taylor M. and Shao, Hu and Wolf, Levi John},
title={{The PySAL Ecosystem: Philosophy and Implementation}},
journal={Geographical Analysis},
year={2021},
doi={10.1111/gean.12276},
abstract={PySAL is a library for geocomputation and spatial data science. Written in Python, the library has a long history of supporting novel scholarship and broadening methodological impacts far afield of academic work. Recently, many new techniques, methods of analyses, and development modes have been implemented, making the library much larger and more encompassing than that previously discussed in the literature. As such, we provide an introduction to the library as it stands now, as well as the scientific and conceptual underpinnings of its core set of components. Finally, we provide a prospective look at the library's future evolution.}
}
2 changes: 1 addition & 1 deletion paper/paper.md
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Expand Up @@ -33,7 +33,7 @@ bibliography: paper.bib

# Summary

Spatial optimization is a major spatial analytical tool in management and planning, the significance of which cannot be overstated. Spatial optimization models play an important role in designing and managing effective and efficient service systems such as transportation, education, public health, environmental protection, and commercial investment among others. To this end, spopt (spatial optimization) is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions. Spopt is a submodule in the open-source spatial analysis library PySAL (Python Spatial Analysis Library) founded by Dr. Serge Rey and Dr. Luc Ancelin in 2005 [@rey2010pysal;@rey2015open]. The goal of developing spopt is to provide management and decision-making support to all relevant practitioners and to further promote the appropriate and meaningful application of spatial optimization models in practice.
Spatial optimization is a major spatial analytical tool in management and planning, the significance of which cannot be overstated. Spatial optimization models play an important role in designing and managing effective and efficient service systems such as transportation, education, public health, environmental protection, and commercial investment among others. To this end, spopt (spatial optimization) is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions. Spopt is a submodule in the open-source spatial analysis library PySAL (Python Spatial Analysis Library) founded by Dr. Serge Rey and Dr. Luc Ancelin in 2005 [@rey2010pysal;@rey2015open;@Rey2021]. The goal of developing spopt is to provide management and decision-making support to all relevant practitioners and to further promote the appropriate and meaningful application of spatial optimization models in practice.


# Statement of need
Expand Down