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@Book{neteler_open_2008,
address = {New York, NY},
edition = {Third},
title = {Open source {GIS}: a {GRASS} {GIS} approach},
isbn = {978-0-387-35767-6 978-0-387-68574-8},
shorttitle = {Open source {GIS}},
language = {eng},
publisher = {Springer},
author = {Markus Neteler and Helena Mitasova},
year = {2008},
note = {OCLC: 255568974
bibtex: neteler\_open\_2008},
keywords = {Analyse, Computerkartographie, GIS, GRASS, GRASS (Electronic computer system), Geographic information systems, Geoinformationssystem, Open source, Open source software, Programm, Programmierung, Raster, Software, Vektor, Visualisierung},
}
@Article{pebesma_r_2012,
title = {The {R} software environment in reproducible geoscientific research},
volume = {93},
issn = {2324-9250},
url = {http://onlinelibrary.wiley.com/doi/10.1029/2012EO160003/abstract},
doi = {10.1029/2012EO160003},
abstract = {Reproducibility is an important aspect of scientific research, because the credibility of science is at stake when research is not reproducible. Like science, the development of good, reliable scientific software is a social process. A mature and growing community relies on the R software environment for carrying out geoscientific research. Here we describe why people use R and how it helps in communicating and reproducing research.},
language = {en},
number = {16},
urldate = {2017-10-25},
journal = {Eos, Transactions American Geophysical Union},
author = {Edzer Pebesma and Daniel N{\"u}st and Roger Bivand},
month = {apr},
year = {2012},
note = {bibtex: pebesma\_r\_2012},
keywords = {0520 Data analysis: algorithms and implementation, 0530 Data presentation and visualization, 1694 Instruments and techniques, 1819 Hydrology: Geographic Information Systems (GIS), 1978 Software re-use, R project, reproducible research},
pages = {163--163},
}
@Book{gillespie_efficient_2016,
title = {Efficient {R} {Programming}: {A} {Practical} {Guide} to {Smarter} {Programming}},
isbn = {978-1-4919-5078-4},
url = {https://csgillespie.github.io/efficientR/},
publisher = {O'Reilly Media},
author = {Colin Gillespie and Robin Lovelace},
year = {2016},
}
@Article{lovelace_propensity_2017,
title = {The {Propensity} to {Cycle} {Tool}: {An} open source online system for sustainable transport planning},
volume = {10},
copyright = {Copyright (c) 2016 Robin Lovelace, Anna Goodman, Rachel Aldred, Nikolai Berkoff, Ali Abbas, James Woodcock},
issn = {1938-7849},
shorttitle = {The {Propensity} to {Cycle} {Tool}},
url = {https://www.jtlu.org/index.php/jtlu/article/view/862},
doi = {10.5198/jtlu.2016.862},
abstract = {Getting people cycling is an increasingly common objective in transport planning institutions worldwide. A growing evidence base indicates that high quality infrastructure can boost local cycling rates. Yet for infrastructure and other cycling measures to be effective, it is important to intervene in the right places, such as along ‘desire lines’ of high latent demand. This creates the need for tools and methods to help answer the question ‘where to build?’. Following a brief review of the policy and research context related to this question, this paper describes the design, features and potential applications of such a tool. The Propensity to Cycle Tool (PCT) is an online, interactive planning support system that was initially developed to explore and map cycling potential across England (see www.pct.bike). Based on origin-destination data it models cycling levels at area, desire line, route and route network levels, for current levels of cycling, and for scenario-based ‘cycling futures.’ Four scenarios are presented, including ‘Go Dutch’ and ‘Ebikes,’ which explore what would happen if English people had the same propensity to cycle as Dutch people and the potential impact of electric cycles on cycling uptake. The cost effectiveness of investment depends not only on the number of additional trips cycled, but on wider impacts such as health and carbon benefits. The PCT reports these at area, desire line, and route level for each scenario. The PCT is open source, facilitating the creation of scenarios and deployment in new contexts. We conclude that the PCT illustrates the potential of online tools to inform transport decisions and raises the wider issue of how models should be used in transport planning.},
language = {en},
number = {1},
urldate = {2017-06-01},
journal = {Journal of Transport and Land Use},
author = {Robin Lovelace and Anna Goodman and Rachel Aldred and Nikolai Berkoff and Ali Abbas and James Woodcock},
month = {jan},
year = {2017},
note = {bibtex:lovelace\_propensity\_2017},
keywords = {Cycling, Participatory, Planning, modelling},
}
@Book{grolemund_r_2016,
title = {R for {Data} {Science}},
isbn = {978-1-4919-1039-9},
language = {English},
publisher = {O'Reilly Media},
author = {Garrett Grolemund and Hadley Wickham},
month = {jul},
year = {2016},
note = {bibtex:grolemund\_r\_2016},
}
@Article{moreno-monroy_public_2017,
title = {Public transport and school location impacts on educational inequalities: {Insights} from {São} {Paulo}},
issn = {0966-6923},
shorttitle = {Public transport and school location impacts on educational inequalities},
url = {http://www.sciencedirect.com/science/article/pii/S0966692316303453},
doi = {10.1016/j.jtrangeo.2017.08.012},
abstract = {In many large Latin American urban areas such as the São Paulo Metropolitan Region (SPMR), growing social and economic inequalities are embedded through high spatial inequality in the provision of state schools and affordable public transport to these schools. This paper sheds light on the transport-education inequality nexus with reference to school accessibility by public transport in the SPMR. To assess school accessibility, we develop an accessibility index which combines information on the spatial distribution of adolescents, the location of existing schools, and the public transport provision serving the school catchment area into a single measure. The index is used to measure school accessibility locally across 633 areas within the SPMR. We use the index to simulate the impact of a policy aiming at increasing the centralisation of public secondary education provision, and find that it negatively affects public transport accessibility for students with the lowest levels of accessibility. These results illustrate how existing inequalities can be amplified by variable accessibility to schools across income groups and geographical space. The research suggests that educational inequality impacts of school agglomeration policies should be considered before centralisation takes place.},
urldate = {2017-10-15},
journal = {Journal of Transport Geography},
author = {Ana I. Moreno-Monroy and Robin Lovelace and Frederico R. Ramos},
month = {sep},
year = {2017},
note = {bibtex: moreno-monroy\_public\_2017},
keywords = {Accessibility, Inequality, Latin America, Public transport, Schools},
}
@Article{pebesma_simple_2018,
title = {Simple features for {R}: {Standardized} support for spatial vector data},
url = {https://journal.r-project.org/archive/2018/RJ-2018-009/index.html},
journal = {The R Journal},
author = {Edzer Pebesma},
year = {2018},
note = {bibtex:pebesma\_simple\_2018},
}
@Book{maling_coordinate_1992,
address = {Oxford ; New York},
edition = {Second},
title = {Coordinate systems and map projections},
isbn = {978-0-08-037234-1},
publisher = {Pergamon Press},
author = {D. H. Maling},
year = {1992},
keywords = {Grids (Cartography), Map projection},
}
@Book{brewer_designing_2015,
address = {Redlands, California},
edition = {Second},
title = {Designing {Better} {Maps}: {A} {Guide} for {GIS} {Users}},
isbn = {978-1-58948-440-5},
shorttitle = {Designing {Better} {Maps}},
url = {http://esripress.esri.com/storage/esripress/images/293/betmaped2_chapter%201.pdf},
language = {English},
publisher = {Esri Press},
author = {Cynthia A. Brewer},
month = {dec},
year = {2015},
}
@Book{wickham_ggplot2:_2016,
address = {New York, NY},
edition = {Second},
title = {ggplot2: {Elegant} {Graphics} for {Data} {Analysis}},
isbn = {978-3-319-24275-0},
shorttitle = {ggplot2},
abstract = {This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to: produce handsome, publication-quality plots with automatic legends created from the plot specification superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.},
language = {English},
publisher = {Springer},
author = {Hadley Wickham},
month = {jun},
year = {2016},
}
@Book{zuur_beginners_2017,
address = {Newburgh, United Kingdom},
title = {Beginner's guide to spatial, temporal and spatial-temporal ecological data analysis with {R}-{INLA}},
volume = {1},
isbn = {978-0-9571741-9-1},
language = {eng},
publisher = {Highland Statistics Ltd},
author = {Alain F. Zuur and Elena N. Ieno and Anatoly A. Saveliev and Alain F. Zuur},
year = {2017},
note = {OCLC: 993615802
bibtex: zuur\_beginners\_2017},
}
@Book{xiao_gis_2016,
address = {London},
title = {{GIS} {Algorithms}: {Theory} and {Applications} for {Geographic} {Information} {Science} \& {Technology}},
shorttitle = {{GIS} {Algorithms}},
url = {http://sk.sagepub.com/books/gis-algorithms},
abstract = {Geographic information systems (GIS) have become increasingly important in helping us understand complex social, economic, and natural dynamics where spatial components play a key role. The critical algorithms used in GIS, however, are notoriously difficult to both teach and understand, in part due to the lack of a coherent representation. GIS Algorithms attempts to address this problem by combining rigorous formal language with example case studies and student exercises. Using Python code throughout, Xiao breaks the subject down into three fundamental areas: • Geometric Algorithms • Spatial Indexing • Spatial Analysis and Modelling With its comprehensive coverage of the many algorithms involved, GIS Algorithms is a key new textbook in this complex and critical area of geography.},
urldate = {2018-05-07},
author = {Ningchuan Xiao},
year = {2016},
doi = {10.4135/9781473921498},
}
@Book{rodrigue_geography_2013,
address = {London, New York},
edition = {Third},
title = {The {Geography} of {Transport} {Systems}},
isbn = {978-0-415-82254-1},
language = {English},
publisher = {Routledge},
author = {Jean-Paul Rodrigue and Claude Comtois and Brian Slack},
month = {jun},
year = {2013},
note = {bibtex: rodrigue\_geography\_2013},
}
@Book{lamigueiro_displaying_2018,
address = {Boca Raton},
edition = {Second},
title = {Displaying {Time} {Series}, {Spatial}, and {Space}-{Time} {Data} with {R}},
isbn = {978-1-138-08998-3},
abstract = {Focusing on the exploration of data with visual methods, Displaying Time Series, Spatial, and Space-Time Data with R, Second Edition, presents methods and R code for producing high-quality static graphics, interactive visualizations, and animations of time series, spatial, and space-time data. Practical examples using real-world datasets help you understand how to apply the methods and code.The book illustrates how to display a dataset starting with an easy and direct approach, and progressively adds improvements that involve more complexity. Each of the three parts of the book is devoted to different types of data. In each part, the chapters are grouped according to the various visualization methods or data characteristics.The first edition of this book was mainly focused on static graphics. Four years later, recent developments in the {"}htmlwidgets{"} family of packages are covered in this second edition with many new interactive graphics. In addition, the {"}ggplot2{"} approach is now used in most of the spatial graphics, thanks to the new {"}sf{"} package. Finally, code has been cleaned and improved, and data has been updated.Features• Offers detailed information on producing high-quality graphics, interactive visualizations, and animations• Uses real data from meteorological, climate, economic, social science, energy, engineering, environmental, and epidemiological research in many practical examples• Shows how to improve graphics based on visualization theory• Provides the graphics, data, and R code on the author’s website, enabling you to practice with the methods and modify the code to suit your own needs.},
language = {English},
publisher = {Chapman and Hall/CRC},
author = {Oscar Perpinan Lamigueiro},
month = {aug},
year = {2018},
}
@Article{meulemans_small_2017,
title = {Small {Multiples} with {Gaps}},
volume = {23},
issn = {1077-2626},
url = {http://ieeexplore.ieee.org/document/7536128/},
doi = {10.1109/TVCG.2016.2598542},
abstract = {Small multiples enable comparison by providing different views of a single data set in a dense and aligned manner. A common frame defines each view, which varies based upon values of a conditioning variable. An increasingly popular use of this technique is to project two-dimensional locations into a gridded space (e.g. grid maps), using the underlying distribution both as the conditioning variable and to determine the grid layout. Using whitespace in this layout has the potential to carry information, especially in a geographic context. Yet, the effects of doing so on the spatial properties of the original units are not understood. We explore the design space offered by such small multiples with gaps. We do so by constructing a comprehensive suite of metrics that capture properties of the layout used to arrange the small multiples for comparison (e.g. compactness and alignment) and the preservation of the original data (e.g. distance, topology and shape). We study these metrics in geographic data sets with varying properties and numbers of gaps. We use simulated annealing to optimize for each metric and measure the effects on the others. To explore these effects systematically, we take a new approach, developing a system to visualize this design space using a set of interactive matrices. We find that adding small amounts of whitespace to small multiple arrays improves some of the characteristics of 2D layouts, such as shape, distance and direction. This comes at the cost of other metrics, such as the retention of topology. Effects vary according to the input maps, with degree of variation in size of input regions found to be a factor. Optima exist for particular metrics in many cases, but at different amounts of whitespace for different maps. We suggest multiple metrics be used in optimized layouts, finding topology to be a primary factor in existing manually-crafted solutions, followed by a trade-off between shape and displacement. But the rich range of possible optimized layouts leads us to challenge single-solution thinking; we suggest to consider alternative optimized layouts for small multiples with gaps. Key to our work is the systematic, quantified and visual approach to exploring design spaces when facing a trade-off between many competing criteria—an approach likely to be of value to the analysis of other design spaces.},
language = {en},
number = {1},
urldate = {2018-09-02},
journal = {IEEE Transactions on Visualization and Computer Graphics},
author = {Wouter Meulemans and Jason Dykes and Aidan Slingsby and Cagatay Turkay and Jo Wood},
month = {jan},
year = {2017},
pages = {381--390},
}
@Book{mccune_analysis_2002,
address = {Gleneden Beach, OR},
edition = {Second},
title = {Analysis of ecological communities},
isbn = {978-0-9721290-0-8},
language = {eng},
publisher = {MjM Software Design},
author = {Bruce McCune and James B. Grace and Dean L. Urban},
year = {2002},
note = {OCLC: 846056595},
}
@Book{wulf_invention_2015,
address = {New York},
title = {The invention of nature: {Alexander} von {Humboldt}'s new world},
isbn = {978-0-385-35066-2 978-0-345-80629-1},
shorttitle = {The invention of nature},
publisher = {Alfred A. Knopf},
author = {Andrea Wulf},
year = {2015},
keywords = {Germany, Humboldt, Alexander von, Naturalists, Scientists},
}
@Book{brunsdon_introduction_2015,
address = {Los Angeles},
title = {An {Introduction} to {R} for {Spatial} {Analysis} and {Mapping}},
isbn = {978-1-4462-7295-4},
abstract = {{"}In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using 'out of the box' software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical 'how to' guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses.{"} - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive 'how to' that takes students - of any discipline - from coding to actual applications and uses of R.},
language = {English},
publisher = {SAGE Publications Ltd},
author = {Chris Brunsdon and Lex Comber},
month = {feb},
year = {2015},
note = {bibtex:brunsdon\_introduction\_2015},
}
@Book{openshaw_geocomputation_2000,
address = {London ; New York},
title = {Geocomputation},
isbn = {978-0-7484-0900-6},
abstract = {Geocomputation is essentially the follow-on revolution from Geographic Information Science and is expected to gather speed and momentum in the first decade of the 21st century. It comes into use once a GIS database has been set up, with a digital data library, and expanded and linked to a global geographical two or three dimensional co-ordinate system. It exploits developments in IT and new data gathering and earth observing technologies, and takes the notion of GIS beyond data and towards its analysis, modelling, and use in problem solving. This book provides pointers on how to harness these technologies in tandem and in the context of multiple different subjects and problem areas. It seeks to establish the principles and set the foundations for subsequent growth.L},
language = {English},
publisher = {CRC Press},
editor = {Stan Openshaw and Robert J. Abrahart},
month = {may},
year = {2000},
}
@Book{longley_geocomputation:_1998,
address = {Chichester, Eng. ; New York},
title = {Geocomputation: {A} {Primer}},
isbn = {978-0-471-98576-1},
shorttitle = {Geocomputation},
abstract = {Geocomputation A Primer edited by Paul A Longley Sue M Brooks Rachael McDonnell School of Geographical Sciences, University of Bristol, UK and Bill Macmillan School of Geography, University of Oxford, UK This book encompasses all that is new in geocomputation. It is also a primer - that is, a book which sets out the foundations and scope of this important emergent area from the same contemporary perspective. The catalyst to the emergence of geocomputation is the new and creative application of computers to devise and depict digital representations of the Earth's surface. The environment for geocomputation is provided by geographical information systems (GIS), yet geocomputation is much more than GIS. Geocomputation is a blend of research-led applications which emphasise process over form, dynamics over statics, and interaction over passive response. This book presents a timely blend of current research and practice, written by the leading figures in the field. It provides insights to a new and rapidly developing area, and identifies the key foundations to future developments. It should be read by all who seek to use geocomputational methods for solving real world problems.},
language = {English},
publisher = {Wiley},
editor = {Paul A. Longley and Sue M. Brooks and Rachael McDonnell and Bill MacMillan},
month = {oct},
year = {1998},
}
@Book{brzustowicz_data_2017,
address = {Beijing Boston Farnham},
edition = {First},
title = {Data science with {Java}: [practical methods for scientists and engineers]},
isbn = {978-1-4919-3411-1},
shorttitle = {Data science with {Java}},
language = {eng},
publisher = {O´Reilly},
author = {Michael R. Brzustowicz},
year = {2017},
note = {OCLC: 993428657},
keywords = {Data Mining, Data mining Software, Datenanalyse, Java, Java (Computer program language)},
}
@Book{murrell_r_2016,
edition = {Second},
title = {R {Graphics}},
isbn = {978-1-4398-3177-9},
abstract = {Extensively updated to reflect the evolution of statistics and computing, the second edition of the bestselling R Graphics comes complete with new packages and new examples. Paul Murrell, widely known as the leading expert on R graphics, has developed an in-depth resource that helps both neophyte and seasoned users master the intricacies of R graphics. New in the Second Edition Updated information on the core graphics engine, the traditional graphics system, the grid graphics system, and the lattice package A new chapter on the ggplot2 package New chapters on applications and extensions of R Graphics, including geographic maps, dynamic and interactive graphics, and node-and-edge graphs Organized into five parts, R Graphics covers both {"}traditional{"} and newer, R-specific graphics systems. The book reviews the graphics facilities of the R language and describes R’s powerful grid graphics system. It then covers the graphics engine, which represents a common set of fundamental graphics facilities, and provides a series of brief overviews of the major areas of application for R graphics and the major extensions of R graphics.},
language = {en},
publisher = {CRC Press},
author = {Paul Murrell},
month = {apr},
year = {2016},
note = {bibtex: murrell\_r\_2016},
keywords = {Computers / Computer Graphics, Computers / General, Mathematics / Probability \& Statistics / General},
}
@Book{orourke_computational_1998,
address = {Cambridge, UK, ; New York, NY, USA},
edition = {Second},
title = {Computational {Geometry} in {C}},
isbn = {978-0-521-64976-6},
url = {http://cs.smith.edu/~jorourke/books/compgeom.html},
abstract = {This is the newly revised and expanded edition of the popular introduction to the design and implementation of geometry algorithms arising in areas such as computer graphics, robotics, and engineering design. The second edition contains material on several new topics, such as randomized algorithms for polygon triangulation, planar point location, 3D convex hull construction, intersection algorithms for ray-segment and ray-triangle, and point-in-polyhedron. A new {"}Sources{"} chapter points to supplemental literature for readers needing more information on any topic. A novel aspect is the inclusion of working C code for many of the algorithms, with discussion of practical implementation issues. The self-contained treatment presumes only an elementary knowledge of mathematics, but reaches topics on the frontier of current research, making it a useful reference for practitioners at all levels. The code in this new edition is significantly improved from the first edition, and four new routines are included. Java versions for this new edition are also available. All code is accessible from the book's Web site (http://cs.smith.edu/{\textasciitilde}orourke/) or by anonymous ftp.},
language = {English},
publisher = {Cambridge University Press},
author = {Joseph O'Rourke},
month = {oct},
year = {1998},
}
@Book{obe_postgis_2015,
address = {Shelter Island, NY},
edition = {Second},
title = {{PostGIS} in action},
isbn = {978-1-61729-139-5},
abstract = {{"}PostGIS in Action, Second Edition teaches you to solve real-world goedata problems. It first gives you a background in vector-, raster-, and topology-based GIS and then quickly moves into analyzing, viewing, and mapping data. You'll learn how to optimize queries for maximum speed, simplify geometrics for greater efficiency, and create custom functions for your own applications. You'll also learn how to apply your existing GIS knowledge to PostGIS and integrate with other GIS tools. What's Inside: An introduction to spatial databases -- geometry, geography, raster, and topology spatial types, functions, and queries -- Applying PostGIS to real-world problems -- Extending PostGIS to web and desktop applications -- Updated for PostGIS 2.x and PostgreSQL 9.x{"}--Back cover},
publisher = {Manning},
author = {Regina O. Obe and Leo S. Hsu},
year = {2015},
note = {OCLC: ocn872985108},
keywords = {Database searching, Geographic information systems},
}
@Book{liu_essential_2009,
address = {Chichester, West Sussex, UK, Hoboken, NJ},
title = {Essential image processing and {GIS} for remote sensing},
isbn = {978-0-470-51032-2 978-0-470-51031-5},
publisher = {Wiley-Blackwell},
author = {Jian-Guo Liu and Philippa J. Mason},
year = {2009},
note = {bibtex: liu\_essential\_2009},
keywords = {Earth (Planet), Geographic information systems, Image processing, Remote sensing, Surface Remote sensing},
}
@Book{krainski_advanced_2018,
title = {Advanced {Spatial} {Modeling} with {Stochastic} {Partial} {Differential} {Equations} {Using} {R} and {INLA}},
isbn = {978-1-138-36985-6},
url = {https://becarioprecario.bitbucket.io/spde-gitbook/},
abstract = {Book on spatial and spatio-temporal modeling with SPDEs and INLA. R code and free Gitbook version here: http://www.r-inla.org/spde-book .},
author = {Elias Krainski and Virgilio {G{\a'o}mez Rubio} and Haakon Bakka and Amanda Lenzi and Daniela Castro-Camilo and Daniel Simpson and Finn Lindgren and H{\r a}vard Rue},
month = {sep},
year = {2018},
}
@Book{burrough_principles_2015,
address = {Oxford, New York},
edition = {Third},
title = {Principles of geographical information systems},
isbn = {978-0-19-874284-5},
publisher = {Oxford University Press},
author = {P. A. Burrough and Rachael McDonnell and Christopher D. Lloyd},
year = {2015},
note = {OCLC: ocn915100245
bibtex: burrough\_principles\_2015},
keywords = {Geographic information systems},
}
@Article{breiman_random_2001,
title = {Random {Forests}},
volume = {45},
issn = {1573-0565},
url = {https://doi.org/10.1023/A:1010933404324},
doi = {10.1023/A:1010933404324},
number = {1},
journal = {Machine Learning},
author = {Leo Breiman},
month = {oct},
year = {2001},
pages = {5--32},
}
@Book{hollander_transport_2016,
title = {Transport {Modelling} for a {Complete} {Beginner}},
isbn = {978-0-9956624-1-4},
abstract = {Finally! A book about transport modelling which doesn’t require any previous knowledge. {"}Transport modelling for a complete beginner{"} explains the basics of transport modelling in a simple language, with lots of silly drawings, and without using any mathematics. Click here to watch a 3-minute introductory video (or search for the book name on YouTube if the link doesn't show). This book is aimed at transport planners, town planners, students in transport-related courses, policy advisors, economists, project managers, property developers, investors, politicians, journalists, and anyone else who wants to understand the process of making decisions on transport infrastructure. It is suitable for readers in any country. The book is split into two parts. The first part is about the principles of transport modelling. This part talks about travel demand, transport networks, zones, trip matrices, the value of time, trip generation, mode split, destination choice, model calibration – lots of scary words that need explaining in order to understand the role of models in the assessment of transport projects. All modes of transport are covered: cars, buses, trains, trucks, taxis, walking, cycling and others. Hot air balloons may be the only transport mode that is hardly mentioned. The second part of the book covers more strategic issues. It talks about the culture of transport modelling, including the management of transport modelling work, the way model outputs are communicated, and the professional environment where this is done. This part of the book also contains an honest discussion of common modelling practices which should be recommended and others which should not. “Transport modelling for a complete beginner” will help you ensure that anything you do with a transport model remains fair, effective and based on real evidence.},
language = {English},
publisher = {CTthink!},
author = {Yaron Hollander},
month = {dec},
year = {2016},
note = {bibtex:hollander\_transport\_2016},
}
@Book{horni_multi-agent_2016,
title = {The {Multi}-{Agent} {Transport} {Simulation} {MATSim}},
isbn = {978-1-909188-77-8 978-1-909188-75-4 978-1-909188-78-5 978-1-909188-76-1},
url = {https://www.ubiquitypress.com/site/books/10.5334/baw/},
abstract = {The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status.},
language = {en},
urldate = {2017-12-29},
publisher = {Ubiquity Press},
author = {Andreas Horni and Kai Nagel and Kay W. Axhausen},
month = {aug},
year = {2016},
note = {bibtex: horni\_multi-agent\_2016},
}
@Article{galletti_land_2016,
title = {Land changes and their drivers in the cloud forest and coastal zone of {Dhofar}, {Oman}, between 1988 and 2013},
volume = {16},
issn = {1436-3798, 1436-378X},
url = {http://link.springer.com/10.1007/s10113-016-0942-2},
doi = {10.1007/s10113-016-0942-2},
language = {en},
number = {7},
urldate = {2018-10-17},
journal = {Regional Environmental Change},
author = {Christopher S. Galletti and Billie L. Turner and Soe W. Myint},
year = {2016},
pages = {2141--2153},
}
@Article{baddeley_spatstat:_2005,
title = {Spatstat: an {R} package for analyzing spatial point patterns},
volume = {12},
url = {https://www.jstatsoft.org/article/view/v012i06},
number = {6},
journal = {Journal of statistical software},
author = {Adrian Baddeley and Rolf Turner},
year = {2005},
keywords = {Linear Models, conditional intensity, edge corrections, exploratory data analysis, generalised, hood, inhomogeneous point patterns, marked point patterns, maximum pseudolikeli-, spatial clustering},
pages = {1--42},
}
@Article{eddelbuettel_extending_2018,
title = {Extending {R} with {C}++: {A} {Brief} {Introduction} to {Rcpp}},
volume = {72},
issn = {0003-1305},
shorttitle = {Extending {R} with {C}++},
url = {https://amstat.tandfonline.com/doi/abs/10.1080/00031305.2017.1375990},
doi = {10.1080/00031305.2017.1375990},
abstract = {R has always provided an application programming interface (API) for extensions. Based on the C language, it uses a number of macros and other low-level constructs to exchange data structures between the R process and any dynamically loaded component modules authors added to it. With the introduction of the Rcpp package, and its later refinements, this process has become considerably easier yet also more robust. By now, Rcpp has become the most popular extension mechanism for R. This article introduces Rcpp, and illustrates with several examples how the Rcpp Attributes mechanism in particular eases the transition of objects between R and C++ code. Supplementary materials for this article are available online.},
number = {1},
urldate = {2018-10-01},
journal = {The American Statistician},
author = {Dirk Eddelbuettel and James Joseph Balamuta},
month = {jan},
year = {2018},
pages = {28--36},
}
@Article{pezanowski_senseplace3:_2018,
title = {{SensePlace}3: a geovisual framework to analyze place–time–attribute information in social media},
volume = {45},
issn = {1523-0406, 1545-0465},
shorttitle = {{SensePlace}3},
url = {https://www.tandfonline.com/doi/full/10.1080/15230406.2017.1370391},
doi = {10.1080/15230406.2017.1370391},
abstract = {SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted about, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources.},
language = {en},
number = {5},
urldate = {2018-09-30},
journal = {Cartography and Geographic Information Science},
author = {Scott Pezanowski and Alan M MacEachren and Alexander Savelyev and Anthony C Robinson},
month = {sep},
year = {2018},
pages = {420--437},
}
@Article{hengl_random_2018,
title = {Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables},
volume = {6},
issn = {2167-8359},
url = {https://peerj.com/articles/5518},
doi = {10.7717/peerj.5518},
language = {en},
urldate = {2018-09-25},
journal = {PeerJ},
author = {Tomislav Hengl and Madlene Nussbaum and Marvin N. Wright and Gerard B.M. Heuvelink and Benedikt Gr{\"a}ler},
month = {aug},
year = {2018},
note = {bibtex:hengl\_random\_2018},
pages = {e5518},
}
@Article{brus_sampling_2018,
title = {Sampling for digital soil mapping: {A} tutorial supported by {R} scripts},
issn = {0016-7061},
shorttitle = {Sampling for digital soil mapping},
url = {http://www.sciencedirect.com/science/article/pii/S0016706118308425},
doi = {10.1016/j.geoderma.2018.07.036},
abstract = {In the past decade, substantial progress has been made in model-based optimization of sampling designs for mapping. This paper is an update of the overview of sampling designs for mapping presented by de Gruijter et al. (2006). For model-based estimation of values at unobserved points (mapping), probability sampling is not required, which opens up the possibility of optimized non-probability sampling. Non-probability sampling designs for mapping are regular grid sampling, spatial coverage sampling, k-means sampling, conditioned Latin hypercube sampling, response surface sampling, Kennard-Stone sampling and model-based sampling. In model-based sampling a preliminary model of the spatial variation of the soil variable of interest is used for optimizing the sample size and or the spatial coordinates of the sampling locations. Kriging requires knowledge of the variogram. Sampling designs for variogram estimation are nested sampling, independent random sampling of pairs of points, and model-based designs in which either the uncertainty about the variogram parameters, or the uncertainty about the kriging variance is minimized. Various minimization criteria have been proposed for designing a single sample that is suitable both for estimating the variogram and for mapping. For map validation, additional probability sampling is recommended, so that unbiased estimates of map quality indices and their standard errors can be obtained. For all sampling designs, R scripts are available in the supplement. Further research is recommended on sampling designs for mapping with machine learning techniques, designs that are robust against deviations of modeling assumptions, designs tailored at mapping multiple soil variables of interest and soil classes or fuzzy memberships, and probability sampling designs that are efficient both for design-based estimation of populations means and for model-based mapping.},
urldate = {2018-09-11},
journal = {Geoderma},
author = {D. J. Brus},
month = {aug},
year = {2018},
keywords = {K-means sampling, Kriging, Latin hypercube sampling, Model-based sampling, Spatial coverage sampling, Spatial simulated annealing, Variogram},
}
@Book{wegmann_remote_2016,
address = {Exeter},
series = {Data in the wild},
title = {Remote sensing and {GIS} for ecologists: using open source software},
isbn = {978-1-78427-022-3 978-1-78427-023-0 978-1-78427-024-7 978-1-78427-025-4 978-1-78427-028-5},
shorttitle = {Remote sensing and {GIS} for ecologists},
language = {eng},
publisher = {Pelagic Publishing},
editor = {Martin Wegmann and Benjamin Leutner and Stefan Dech},
year = {2016},
note = {OCLC: 945979372},
}
@Article{landa_new_2008,
title = {New {GUI} for {GRASS} {GIS} based on {wxPython}},
journal = {Departament of Geodesy and Cartography},
author = {Martin Landa},
year = {2008},
pages = {1--17},
}
@Article{wickham_tidy_2014,
title = {Tidy {Data}},
volume = {59},
issn = {1548-7660},
url = {http://www.jstatsoft.org/v59/i10/},
doi = {10.18637/jss.v059.i10},
language = {en},
number = {10},
urldate = {2018-08-20},
journal = {Journal of Statistical Software},
author = {Hadley Wickham},
year = {2014},
}
@Article{pebesma_classes_2005,
title = {Classes and methods for spatial data in {R}},
volume = {5},
url = {https://cran.r-project.org/doc/Rnews/Rnews_2005-2.pdf},
number = {2},
journal = {R news},
author = {Edzer J Pebesma and Roger S Bivand},
year = {2005},
note = {bibtex:pebesma\_classes\_2005},
pages = {9--13},
}
@Article{probst_hyperparameters_2018,
title = {Hyperparameters and {Tuning} {Strategies} for {Random} {Forest}},
url = {http://arxiv.org/abs/1804.03515},
abstract = {The random forest algorithm (RF) has several hyperparameters that have to be set by the user, e.g., the number of observations drawn randomly for each tree and whether they are drawn with or without replacement, the number of variables drawn randomly for each split, the splitting rule, the minimum number of samples that a node must contain and the number of trees. In this paper, we first provide a literature review on the parameters' influence on the prediction performance and on variable importance measures, also considering interactions between hyperparameters. It is well known that in most cases RF works reasonably well with the default values of the hyperparameters specified in software packages. Nevertheless, tuning the hyperparameters can improve the performance of RF. In the second part of this paper, after a brief overview of tuning strategies we demonstrate the application of one of the most established tuning strategies, model-based optimization (MBO). To make it easier to use, we provide the tuneRanger R package that tunes RF with MBO automatically. In a benchmark study on several datasets, we compare the prediction performance and runtime of tuneRanger with other tuning implementations in R and RF with default hyperparameters.},
urldate = {2018-08-02},
journal = {arXiv:1804.03515 [cs, stat]},
author = {Philipp Probst and Marvin Wright and Anne-Laure Boulesteix},
month = {apr},
year = {2018},
note = {arXiv: 1804.03515},
keywords = {Computer Science - Machine Learning, Statistics - Machine Learning},
}
@Article{von_wehrden_pluralism_2009,
title = {Pluralism and diversity: trends in the use and application of ordination methods 1990-2007},
volume = {20},
issn = {11009233, 16541103},
shorttitle = {Pluralism and diversity},
url = {http://doi.wiley.com/10.1111/j.1654-1103.2009.01063.x},
doi = {10.1111/j.1654-1103.2009.01063.x},
language = {en},
number = {4},
urldate = {2018-07-25},
journal = {Journal of Vegetation Science},
author = {Henrik {von Wehrden} and Jan Hanspach and Helge Bruelheide and Karsten Wesche},
month = {aug},
year = {2009},
pages = {695--705},
}
@Book{nolan_xml_2014,
address = {New York, NY},
series = {Use {R}!},
title = {{XML} and web technologies for data sciences with {R}},
isbn = {978-1-4614-7900-0 978-1-4614-7899-7},
abstract = {Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. The XML and JSON data formats are widely used in Web services, regular Web pages and JavaScript code, and visualization formats such as SVG and KML for Google Earth and Google Maps. In addition, scientists use HTTP and other network protocols to scrape data from Web pages, access REST and SOAP Web Services, and interact with NoSQL databases and text search applications. This book provides a practical hands-on introduction to these technologies, including high-level functions the authors have developed for data scientists. It describes strategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web. Along with these general skills, the authors illustrate several applications that are relevant to data scientists, such as reading and writing spreadsheet documents both locally and via GoogleDocs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code from descriptions of data structures to read and write data. These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies. The book contains many examples and case-studies that readers can use directly and adapt to their own work},
language = {eng},
publisher = {Springer},
author = {Deborah Nolan and Duncan Temple Lang},
year = {2014},
note = {OCLC: 841520665
bibtex: nolan\_xml\_2014},
}
@Article{kahle_ggmap:_2013,
title = {ggmap: {Spatial} {Visualization} with ggplot2},
volume = {5},
url = {http://stat405.had.co.nz/ggmap.pdf},
journal = {The R Journal},
author = {D Kahle and Hadley Wickham},
year = {2013},
note = {bibtex:kahle\_ggmap\_2013},
pages = {144--161},
}
@Article{hickman_transitions_2011,
series = {Special section on {Alternative} {Travel} futures},
title = {Transitions to low carbon transport futures: strategic conversations from {London} and {Delhi}},
volume = {19},
issn = {0966-6923},
shorttitle = {Transitions to low carbon transport futures},
url = {http://www.sciencedirect.com/science/article/pii/S096669231100130X},
doi = {10.1016/j.jtrangeo.2011.03.013},
abstract = {Climate change is a global problem and across the world there are major difficulties being experienced in reducing carbon dioxide (CO2) emissions. The transport sector in particular is finding it difficult to reduce CO2 emissions. This paper reports on two studies carried out by the authors in London (UK) and Delhi (India). It considers the common objectives for transport CO2 reduction, but the very different contexts and baselines, potentials for change, and some possible synergies.
Different packages of measures are selected and scenarios developed for each context which are consistent with contraction and convergence objectives. CO2 reduction potentials are modelled and quantified by package and scenario. London is considering deep reductions on current transport CO2 emission levels; Delhi is seeking to break the huge projected rise in transport CO2 emissions.
The scale of policy intervention required to achieve these goals is huge and there is certainly little public discussion of the magnitude of the changes required. The paper argues for a ‘strategic conversation’ at the city level, using scenario analysis, to discuss the priorities for intervention in delivering low carbon transport futures. A greater focus is required in developing participatory approaches to decision making, alongside network investments, urban planning, low emission vehicles and wider initiatives. Aspirations towards equitable target emissions may assist in setting sufficiently demanding targets. Only then is a wider awareness and ownership of potential carbon efficient transport futures likely to take place.},
number = {6},
urldate = {2016-05-14},
journal = {Journal of Transport Geography},
author = {Robin Hickman and Olu Ashiru and David Banister},
month = {nov},
year = {2011},
note = {bibtex:hickman\_transitions\_2011},
keywords = {CO2, City planning, Delhi, London, Sustainable, Transport},
pages = {1553--1562},
}
@Article{calenge_package_2006,
title = {The package adehabitat for the {R} software: tool for the analysis of space and habitat use by animals},
volume = {197},
journal = {Ecological Modelling},
author = {C. Calenge},
year = {2006},
note = {bibtex:calenge\_package\_2006},
pages = {1035},
}
@Book{abelson_structure_1996,
address = {Cambridge, Massachusetts},
edition = {Second},
series = {The {MIT} electrical engineering and computer science series},
title = {Structure and interpretation of computer programs},
isbn = {0-262-01153-0},
url = {http://web.mit.edu/alexmv/6.037/sicp.pdf},
publisher = {MIT Press},
author = {Harold Abelson and Gerald Jay Sussman and Julie Sussman},
year = {1996},
keywords = {Computer programming, LISP (Computer program language)},
}
@Article{krug_clearing_2010,
title = {Clearing of invasive alien plants under different budget scenarios: using a simulation model to test efficiency},
volume = {12},
shorttitle = {Clearing of invasive alien plants under different budget scenarios},
url = {http://link.springer.com/article/10.1007/s10530-010-9827-3},
number = {12},
urldate = {2017-08-24},
journal = {Biological invasions},
author = {Rainer M. Krug and N{\a'u}ria Roura-Pascual and David M. Richardson},
year = {2010},
note = {bibtex:krug\_clearing\_2010},
pages = {4099--4112},
}
@Book{bivand_applied_2013,
title = {Applied spatial data analysis with {R}},
volume = {747248717},
publisher = {Springer},
author = {Roger Bivand and Edzer J Pebesma and Virgilio G{\a'o}mez-Rubio},
year = {2013},
note = {bibtex:bivand\_applied\_2013},
keywords = {Mathematics / Probability \& Statistics / General, Medical / Biostatistics, Medical / General, Science / Earth Sciences / Geography, Science / Environmental Science, Technology \& Engineering / Environmental / General},
}
@Book{lovelace_spatial_2016,
title = {Spatial microsimulation with {R}},
url = {http://robinlovelace.net/spatial-microsim-book/},
publisher = {CRC Press},
author = {Robin Lovelace and Morgane Dumont},
year = {2016},
}
@Book{baddeley_spatial_2015,
title = {Spatial point patterns: methodology and applications with {R}},
publisher = {CRC Press},
author = {Adrian Baddeley and Ege Rubak and Rolf Turner},
year = {2015},
}
@Article{knuth_computer_1974,
title = {Computer {Programming} {As} an {Art}},
volume = {17},
issn = {0001-0782},
url = {http://doi.acm.org/10.1145/361604.361612},
doi = {10.1145/361604.361612},
abstract = {When Communications of the ACM began publication in 1959, the members of ACM's Editorial Board made the following remark as they described the purposes of ACM's periodicals [2]: “If computer programming is to become an important part of computer research and development, a transition of programming from an art to a disciplined science must be effected.” Such a goal has been a continually recurring theme during the ensuing years; for example, we read in 1970 of the “first steps toward transforming the art of programming into a science” [26]. Meanwhile we have actually succeeded in making our discipline a science, and in a remarkably simple way: merely by deciding to call it “computer science.”},
number = {12},
urldate = {2018-07-11},
journal = {Commun. ACM},
author = {Donald E. Knuth},
month = {dec},
year = {1974},
pages = {667--673},
}
@Article{kaiser_algorithms_1993,
title = {Algorithms for computing centroids},
volume = {20},
issn = {03050548},
url = {http://linkinghub.elsevier.com/retrieve/pii/030505489390071P},
doi = {10.1016/0305-0548(93)90071-P},
abstract = {Algorithms are given for the computation of centroids of discrete, polygonal, and continuous convex regions in the plane. These include the zero-dimensional center-of-gravity for discrete systems, and the area, perimeter, and curvature centroids for both discrete and continuous regions. The zero-dimensional inter-of-gravity is motivated through analytic, arithmetic, and geometric fo{\textasciitilde}ulations, and is an integral part of the computations of the area, perimeter, and curvature centroids. Several remarks are made that connect the computation of the centoid points to optimization theory and their practical application in various fields. The complexity of each algorithm is aho examined.},
language = {en},
number = {2},
urldate = {2018-07-10},
journal = {Computers \& Operations Research},
author = {M.J. Kaiser and T.L. Morin},
month = {feb},
year = {1993},
pages = {151--165},
}
@Book{wise_gis_2001,
title = {{GIS} basics},
publisher = {CRC Press},
author = {Stephen Wise},
year = {2001},
}
@Article{huang_geospark_2017,
title = {{GeoSpark} {SQL}: {An} {Effective} {Framework} {Enabling} {Spatial} {Queries} on {Spark}},
volume = {6},
issn = {2220-9964},
shorttitle = {{GeoSpark} {SQL}},
url = {http://www.mdpi.com/2220-9964/6/9/285},
doi = {10.3390/ijgi6090285},
language = {en},
number = {9},
urldate = {2018-06-29},
journal = {ISPRS International Journal of Geo-Information},
author = {Zhou Huang and Yiran Chen and Lin Wan and Xia Peng},
month = {sep},
year = {2017},
pages = {285},
}
@Article{bucklin_rpostgis:_2018,
title = {rpostgis: {Linking} {R} with a {PostGIS} {Spatial} {Database}},
url = {https://journal.r-project.org/archive/2018/RJ-2018-025/index.html},
journal = {The R Journal},
author = {David Bucklin and Mathieu Basille},
year = {2018},
}
@Book{wilkinson_grammar_2005,
title = {The grammar of graphics},
publisher = {Springer Science+ Business Media},
author = {Leland Wilkinson and Graham Wills},
year = {2005},
}
@Book{berg_computational_2008,
title = {Computational {Geometry}: {Algorithms} and {Applications}},
isbn = {978-3-540-77973-5},
shorttitle = {Computational {Geometry}},
abstract = {Computational geometry emerged from the field of algorithms design and analysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The success of the ?eld as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains—computer graphics, geographic information systems (GIS), robotics, and others—in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or dif?cult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simpli?ed many of the previous approaches. In this textbook we have tried to make these modern algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can also be used for self-study.},
language = {en},
publisher = {Springer Science \& Business Media},
author = {Mark de Berg and Otfried Cheong and Marc van Kreveld and Mark Overmars},
month = {mar},
year = {2008},
note = {Google-Books-ID: tkyG8W2163YC},
keywords = {Computers / Computer Graphics, Computers / Computer Science, Computers / Data Processing, Computers / Databases / General, Computers / Information Technology, Computers / Programming / Algorithms, Mathematics / Discrete Mathematics, Mathematics / Geometry / General, Science / Earth Sciences / General, Technology \& Engineering / General},
}
@Book{majure_sgeostat:_2016,
title = {sgeostat: {An} {Object}-{Oriented} {Framework} for {Geostatistical} {Modeling} in {S}+},
url = {https://CRAN.R-project.org/package=sgeostat},
author = {James J. Majure and Albrecht Gebhardt},
year = {2016},
}
@Article{the_economist_autonomous_2016,
title = {The autonomous car’s reality check},
issn = {0013-0613},
url = {https://www.economist.com/news/science-and-technology/21696925-building-highly-detailed-maps-robotic-vehicles-autonomous-cars-reality},
abstract = {Building highly detailed maps for robotic vehicles},
urldate = {2018-05-11},
journal = {The Economist},
author = {{The Economist}},
year = {2016},
}
@Book{bellos_alexs_2011,
address = {London},
title = {Alex's {Adventures} in {Numberland}},
isbn = {978-1-4088-0959-4},
abstract = {The world of maths can seem mind-boggling, irrelevant and, let's face it, boring. This groundbreaking book reclaims maths from the geeks. Mathematical ideas underpin just about everything in our lives: from the surprising geometry of the 50p piece to how probability can help you win in any casino. In search of weird and wonderful mathematical phenomena, Alex Bellos travels across the globe and meets the world's fastest mental calculators in Germany and a startlingly numerate chimpanzee in Japan. Packed with fascinating, eye-opening anecdotes, Alex's Adventures in Numberland is an exhilarating cocktail of history, reportage and mathematical proofs that will leave you awestruck.},
language = {English},
publisher = {Bloomsbury Paperbacks},
author = {Alex Bellos},
month = {apr},
year = {2011},
}
@Article{borland_rainbow_2007,
title = {Rainbow color map (still) considered harmful},
volume = {27},
number = {2},
journal = {IEEE computer graphics and applications},
author = {David Borland and Russell M {Taylor II}},
year = {2007},
note = {bibtex[publisher=IEEE]},
}
@Article{tennekes_tmap:_2018,
title = {tmap: {Thematic} {Maps} in {R}},
volume = {84},
issn = {1548-7660},
url = {https://www.jstatsoft.org/v084/i06},
doi = {10.18637/jss.v084.i06},
abstract = {Thematic maps show spatial distributions. The theme refers to the phenomena that is shown, which is often demographical, social, cultural, or economic. The best known thematic map type is the choropleth, in which regions are colored according to the distribution of a data variable. The R package tmap offers a coherent plotting system for thematic maps that is based on the layered grammar of graphics. Thematic maps are created by stacking layers, where per layer, data can be mapped to one or more aesthetics. It is also possible to generate small multiples. Thematic maps can be further embellished by configuring the map layout and by adding map attributes, such as a scale bar and a compass. Besides plotting thematic maps on the graphics device, they can also be made interactive as an HTML widget. In addition, the R package tmaptools contains several convenient functions for reading and processing spatial data.},
number = {6},
journal = {Journal of Statistical Software, Articles},
author = {Martijn Tennekes},
year = {2018},
keywords = {R, spatial data, thematic maps},
pages = {1--39},
}
@Article{meyer_improving_2018,
title = {Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation},
volume = {101},
issn = {13648152},
url = {http://linkinghub.elsevier.com/retrieve/pii/S1364815217310976},
doi = {10.1016/j.envsoft.2017.12.001},
language = {en},
urldate = {2018-04-18},
journal = {Environmental Modelling \& Software},
author = {Hanna Meyer and Christoph Reudenbach and Tomislav Hengl and Marwan Katurji and Thomas Nauss},
month = {mar},
year = {2018},
pages = {1--9},
}
@Book{gelfand_handbook_2010,
title = {Handbook of spatial statistics},
isbn = {1-4200-7288-9},
publisher = {CRC press},
author = {Alan E Gelfand and Peter Diggle and Peter Guttorp and Montserrat Fuentes},
year = {2010},
}
@Book{diggle_model-based_2007,
title = {Model-based geostatistics},
publisher = {Springer},
author = {Peter Diggle and Paulo Justiniano Ribeiro},
year = {2007},
}
@Article{muenchow_geomorphic_2012,
title = {Geomorphic process rates of landslides along a humidity gradient in the tropical {Andes}},
volume = {139-140},
issn = {0169555X},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0169555X11005551},
doi = {10.1016/j.geomorph.2011.10.029},
language = {en},
urldate = {2017-06-23},
journal = {Geomorphology},
author = {Jannes Muenchow and Alexander Brenning and Michael Richter},
month = {feb},
year = {2012},
pages = {271--284},
}
@Book{goovaerts_geostatistics_1997,
address = {New York},
series = {Applied geostatistics series},
title = {Geostatistics for natural resources evaluation},
isbn = {978-0-19-511538-3},
publisher = {Oxford University Press},
author = {Pierre Goovaerts},
year = {1997},
keywords = {Geology, Statistical methods},
}
@Book{hengl_practical_2007,
address = {Luxembourg},
title = {A practical guide to geostatistical mapping of environmental variables},
isbn = {978-92-79-06904-8},
abstract = {Geostatistical mapping can be defined as analytical production of maps by using field observations, auxiliary information and a computer program that calculates values at locations of interest. Today, increasingly the heart of a mapping project is, in fact, the computer program that implements some (geo)statistical algorithm to a given point data set. Purpose of this guide is to assist you in producing quality maps by using fully-operational tools, without a need for serious additional investments. It will first introduce you the to the basic principles of geostatistical mapping and regression-kriging, as the key prediction technique, then it will guide you through four software packages: ILWIS GIS, R+gstat, SAGA GIS and Google Earth, which will be used to prepare the data, run analysis and make final layouts. These materials have been used for the five-days advanced training course {"}Hands-on-geostatistics: merging GIS and spatial statistics{"}, that is regularly organized by the author and collaborators. Visit the course website to obtain a copy of the datasets used in this exercise. [Résumé de l'auteur].},
language = {English},
publisher = {Publications Office},
author = {Tomislav Hengl},
year = {2007},
note = {OCLC: 758643236},
}
@Article{karatzoglou_kernlab_2004,
title = {kernlab - {An} {S}4 {Package} for {Kernel} {Methods} in {R}},
volume = {11},
issn = {1548-7660},
url = {http://www.jstatsoft.org/v11/i09/},
doi = {10.18637/jss.v011.i09},
language = {en},
number = {9},
urldate = {2018-03-28},
journal = {Journal of Statistical Software},
author = {Alexandros Karatzoglou and Alex Smola and Kurt Hornik and Achim Zeileis},
year = {2004},
}
@Article{lefkowitz_identification_1975,
title = {Identification of adenylate cyclase-coupled beta-adrenergic receptors with radiolabeled beta-adrenergic antagonists},
volume = {24},
issn = {0006-2952},
language = {eng},
number = {18},
journal = {Biochemical Pharmacology},
author = {R. J. Lefkowitz},
month = {sep},
year = {1975},
pmid = {11},
keywords = {Adenylyl Cyclases, Adrenergic beta-Antagonists, Alprenolol, Animals, Anura, Binding Sites, Catecholamines, Cattle, Cell Membrane, Eels, Erythrocytes, Guinea Pigs, In Vitro Techniques, Isoproterenol, Kinetics, Propranolol, Receptors, Adrenergic, Stereoisomerism, Tritium},
pages = {1651--1658},
}
@Article{cawley_over-fitting_2010,
title = {On over-fitting in model selection and subsequent selection bias in performance evaluation},
volume = {11},
number = {Jul},
journal = {Journal of Machine Learning Research},
author = {Gavin C. Cawley and Nicola LC Talbot},
year = {2010},
pages = {2079--2107},
}
@Article{muenchow_rqgis:_2017,
title = {{RQGIS}: {Integrating} {R} with {QGIS} for statistical geocomputing},
volume = {9},
number = {2},
journal = {The R Journal},
author = {Jannes Muenchow and Patrick Schratz and Alexander Brenning},
year = {2017},
note = {bibtex: muenchow\_rqgis:\_2017},
pages = {409--428},
}
@Article{bischl_mlr:_2016,
title = {mlr: {Machine} {Learning} in {R}},
volume = {17},
url = {http://jmlr.org/papers/v17/15-066.html},
number = {170},
journal = {Journal of Machine Learning Research},
author = {Bernd Bischl and Michel Lang and Lars Kotthoff and Julia Schiffner and Jakob Richter and Erich Studerus and Giuseppe Casalicchio and Zachary M. Jones},
year = {2016},
note = {bibtex: bischl\_mlr:\_2016},
pages = {1--5},
}
@Book{hunziker_velox:_2017,
title = {velox: {Fast} {Raster} {Manipulation} and {Extraction}},
url = {https://CRAN.R-project.org/package=velox},
author = {Philipp Hunziker},
year = {2017},
note = {bibtex: hunziker\_velox:\_2017},
}
@Article{wieland_market_2017,
title = {Market {Area} {Analysis} for {Retail} and {Service} {Locations} with {MCI}},
volume = {9},
url = {https://journal.r-project.org/archive/2017/RJ-2017-020/index.html},
number = {1},
journal = {The R Journal},
author = {Thomas Wieland},
year = {2017},
note = {bibtex: wieland\_market\_2017},
pages = {298--323},
}
@Misc{office_for_national_statistics_workplace_2014,
title = {Workplace {Zones}: {A} new geography for workplace statistics - {Datasets}},
url = {https://data.gov.uk/dataset/workplace-zones-a-new-geography-for-workplace-statistics3},
urldate = {2018-01-13},
author = {{Office for National Statistics}},
year = {2014},
note = {bibtex: office\_for\_national\_statistics\_workplace\_2014},
}
@TechReport{bristol_city_council_deprivation_2015,
title = {Deprivation in {Bristol} 2015},
url = {https://www.bristol.gov.uk/statistics-census-information/deprivation},
institution = {Bristol City Council},
author = {{Bristol City Council}},
year = {2015},
note = {bibtex: bristol\_city\_council\_deprivation\_2015},
}
@Article{thiele_r_2014,
title = {R {Marries} {NetLogo}: {Introduction} to the {RNetLogo} {Package}},
volume = {58},
url = {http://www.jstatsoft.org/v58/i02/paper},
number = {2},
journal = {Journal of Statistical Software},
author = {J Thiele},
year = {2014},
note = {bibtex: thiele\_r\_2014},
pages = {1--41},
}
@Article{pebesma_measurement_2016,
title = {Measurement {Units} in {R}},