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2. GIS and Computational Notebooks

Author

Boeing, Geoff and Arribas-Bel, Dani

Subjects
Computer Science - Computers and Society, Statistics - Computation
Abstract

Researchers and practitioners across many disciplines have recently adopted computational notebooks to develop, document, and share their scientific workflows - and the GIS community is no exception. This chapter introduces computational notebooks in the geographical context. It begins by explaining the computational paradigm and philosophy that underlie notebooks. Next it unpacks their architecture to illustrate a notebook user's typical workflow. Then it discusses the main benefits notebooks offer GIS researchers and practitioners, including better integration with modern software, more natural access to new forms of data, and better alignment with the principles and benefits of open science. In this context, it identifies notebooks as the glue that binds together a broader ecosystem of open source packages and transferable platforms for computational geography. The chapter concludes with a brief illustration of using notebooks for a set of basic GIS operations. Compared to traditional desktop GIS, notebooks can make spatial analysis more nimble, extensible, and reproducible and have thus evolved into an important component of the geospatial science toolkit.

Published
2021

13. Spatial Data

Author

Rey, Sergio, primary, Arribas-Bel, Dani, additional, and Wolf, Levi John, additional

Published
2023
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30. Delineating urban areas through satellite-derived building footprints

Author

Samardzhiev, Karsen, Arribas-Bel, Dani, and Singleton, Alex

Abstract

Delineating the spatial extent of urban phenomena at different scales is one of the core challenges researchers, planners and policy makers are faced with. This paper proposes to use satellite-derived building footprints and a clustering approach to create a hierarchy of parcels of urban land in the contiguous United states. This hierarchy is used to analyse three urban phenomena - urban form, urban spatial extent and megaregional integration. The most stable parcels from the hierarchy capture 79% of the US population and are similar to census defined urban centres. Furthermore, the hierarchy is used to show the decentralised urban form of these parcels. Lastly, the hierarchy is used to measure the morphological integration of the parcels into large scale urban phenomena - megaregions.

Published
2022
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31. Spatio-Temporal Analysis of Housing Price Trajectories: The Case of Madrid (2010- 2019)

Author

Kenyon, Gladys, Arribas-Bel, Dani, and Robinson, Caitlin

Abstract

The first exploratory paper as part of the thesis ‘Hedonic models with machine learning’ will consider spatiotemporal variations in house prices and rents in the capital of Spain, Madrid. Ten years of property adverts in the city have been provided by online real estate company, Idealista. Divergence in house prices can provide a broader insight into geographic inequality in cities. The paper will analyse spatial house price variation over time, in order to identify clusters of high and low growth. In addition, the analysis can identify ripple effects and could be used to inform future housing policy.

Published
2022
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34. The PySAL Ecosystem: Philosophy and Implementation

Author

Rey, Sergio J., primary, Anselin, Luc, additional, Amaral, Pedro, additional, Arribas‐Bel, Dani, additional, Cortes, Renan Xavier, additional, Gaboardi, James David, additional, Kang, Wei, additional, Knaap, Elijah, additional, Li, Ziqi, additional, Lumnitz, Stefanie, additional, Oshan, Taylor M., additional, Shao, Hu, additional, and Wolf, Levi John, additional

Published
2021
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35. The PySAL Ecosystem: Philosophy and Implementation.

Author

Rey, Sergio J., Anselin, Luc, Amaral, Pedro, Arribas‐Bel, Dani, Cortes, Renan Xavier, Gaboardi, James David, Kang, Wei, Knaap, Elijah, Li, Ziqi, Lumnitz, Stefanie, Oshan, Taylor M., Shao, Hu, and Wolf, Levi John

Subjects
DATA science
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. [ABSTRACT FROM AUTHOR]

Published
2022
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36. Trajectories of neighbourhood inequality in Britain: Unpacking inter‐regional socioeconomic imbalances, 1971−2011.

Author

Patias, Nikos, Rowe, Francisco, and Arribas‐Bel, Dani

Subjects
NEIGHBORHOODS, SMALL cities, POLITICAL stability, EQUALITY, SOCIAL cohesion, SOCIAL stability
Abstract

Persistent spatial inequalities represent a menace to economic progress, social cohesion and political stability. The UK stands out as one of the most unequal countries in the industrialised world. This paper investigates intra‐regional and inter‐urban inequalities at the neighbourhood level in Britain during a 40‐year period, 1971−2011. Using a novel dataset containing a temporal classification of neighbourhoods, we analysed seven representative trajectories of neighbourhood persistence and change unveiling pathways of socioeconomic progress, decline, persistent affluence and disadvantage. Results highlight the extent of geographic unbalance in the distribution of these trajectories. Socioeconomic progress trajectories have been widespread across British cities. Yet a small handful of cities have concentrated persistent affluent neighbourhoods, and persistent struggling neighbourhoods have prevailed in northern cities. [ABSTRACT FROM AUTHOR]

Published
2022
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45. Classification and Regression via Integer Optimization for Neighborhood Change.

Author

Olson, Alexander W., Zhang, Kexin, Calderon‐Figueroa, Fernando, Yakubov, Ronen, Sanner, Scott, Silver, Daniel, and Arribas‐Bel, Dani

Subjects
NEIGHBORHOOD change, INTEGERS, NEIGHBORHOODS, CLASSIFICATION
Abstract

This article applies a method we term "predictive clustering" to cluster neighborhoods. Much of the literature in this direction is based on groupings built using intrinsic characteristics of each observation. Our approach departs from this framework by delineating clusters based on how the neighborhood's features respond to a particular outcome of interest (e.g., income change). To do so, we leverage a classification and regression via integer optimization (CRIO) method that groups neighborhoods according to their predictive characteristics and consistently outperforms traditional clustering methods along several metrics. The CRIO methodology contributes a novel methodological and conceptual capability to the literature on neighborhood dynamics that can provide useful insights for policymaking. [ABSTRACT FROM AUTHOR]

Published
2021
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47. Quantifying the value of data obtained from river gauging stations in Scotland : a users' perspective

Author

Thakar, K. P., Morrissey, Karyn, Macdonald, Neil, and Arribas-Bel, Dani

Subjects
551.48
Abstract

The Scottish Environment Protection Agency (SEPA) monitors river water levels and flow at 392 gauging stations throughout Scotland. Data on river levels and flow are used by a diverse range of interest groups including industry, water authorities, wildlife and water managers, hydrologists, recreational and industrial fishers among others; but most importantly Category 1 Emergency Responders and local populations are reliant on the data produced by gauging stations to provide flood warnings. Data from gauging stations inform the management of water resources to help meet EU Water Framework Directive objectives, the design of new infrastructure on and across flood plains and have been increasingly used by scientists and policy practitioners to evaluate the impact of changes in land use and climate change. The data obtained from river gauging stations are thus a public good that accrue benefits well above their market value, but to date no evaluation of the economic benefit has been made. As agencies responsible for the collection, maintenance and dissemination of such data face a growing demand for their services, the rising costs of network infrastructure needs to be compared with the economic benefits of hydrometric data in order to recognise the societal value of providing such information. The aim of this thesis was to examine the value of the data provided by river gauging stations in Scotland. It did so by eliciting the preferences of two key cohorts in Scotland, namely households and professional data users, for a set of competing hydrometric attributes using stated choice methods; in particular, Choice Experiments. User valuations were analysed across several choice occasions using conditional logit, mixed logit and latent class models. Results demonstrated that both households and professionals derived significant levels of utility from hydrometric gauging activity. Moreover, specific socio-economic and demographic groups were willing to contribute high premiums in order to secure network upgrades, and the effects of cognitive indicators of individual preference were also important determinants of user valuations. Figures aggregated across the two different cohorts revealed non-market benefit-to-cost ratios of at least 15:1, rising to 44:1 when potential value-added services were accounted for. These findings are encouraging for Measuring Authorities facing public sector pressures to downscale their activities by quantifying the magnitude of societal benefits that such activities generate.

Published
2018
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50. rocker/geospatial : a flexible runtime environment for geoscientific data analysis

Author

Nüst, Daniel, Boettiger, Carl, Eddelbuettel, Dirk, Challis, Andrew, Dokter, Adriaan, Ross, Noam, Marwick, Ben, and Arribas-Bel, Dani

Subjects
Virtual Laboratories, Docker, virtualisation, containerisation, Teaching, r-project, Reproducible Research, rstats
Abstract

R is a free software environment for statistical computing and graphics (https://r-project.org) and also a popular tool for geospatial analysis. Docker (https://docker.com) revolutionized the way applications and their dependencies are packaged and deployed. The Rocker project (https://www.rocker-project.org/) hosts a variety of Docker images for R. One of these images is rocker/geospatial with geospatial-related tools, particularly those that can be difficult or slow to add on-the-fly. This presentation showcases works based on rocker/geospatial and provides background how Rocker and Docker provide a basis for increased transparency and reproducibility in geosciences to tackle pressing challenges in data handling and data analysis in software development, research and teaching. Original conference abstract: http://meetingorganizer.copernicus.org/EGU2018/EGU2018-8500.pdf, {"references":["Pebesma E., D. Nüst and R. Bivand, 2012. The R software environment in reproducible geoscientific research, Eos Trans. AGU, 93(16), 163. doi: 10.1029/2012EO160003","Dietze M., S. Kreutzer, O. Korup, 2017. R's deliberate role in Earth sciences, PICO session at EGU 2017, http://meetingorganizer.copernicus.org/EGU2017/session/24971","Boettiger, C. and D. Eddelbuettel, 2017. An Introduction to Rocker: Docker Containers for R. The R Journal, RJ-2017-065. https://rjournal.github.io/archive/2017/RJ-2017-065/index.html","Rocker, 2017. rocker/geospatial on the Docker Hub image registry. https://hub.docker.com/r/rocker/geospatial/"]}

Published
2018
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