Geographer with a computer. @WorldPopProject, #rstats

Joined July 2019
🥳The Breheny Prize for the most innovative @envplanb article published in 2021 has been awarded to @ChrisJochem , Douglas Leasure, Oliver Pannell, @HeatherCh100 , Patricia Jones, @AndyTatem from the @WorldPopProject Congratulations to all👏Find out more: doi.org/10.1177/239980832211…
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Thank you @evnplanb and congratulations to my co-authors!
🥳The Breheny Prize for the most innovative @envplanb article published in 2021 has been awarded to @ChrisJochem , Douglas Leasure, Oliver Pannell, @HeatherCh100 , Patricia Jones, @AndyTatem from the @WorldPopProject Congratulations to all👏Find out more: doi.org/10.1177/239980832211…
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Our paper looks at a way to classify and map potential settlement types from the spatial patterns of building footprints using Gaussian mixture models.
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New random forest informed population modelling package in R (CRAN.R-project.org/package=p… ). Vignette/tutorial can be found (for now) at (dx.doi.org/10.13140/RG.2.2.2…) @geodatascience @WorldPopProject #Population #rspatial
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Got excited and took it out for a spin, all looking great! Here's how you can read/write geospatial data between R and Python like it's the XXIst Century (also, in the same notebook thanks to the darribas.org/gds_env). Notebook at: gist.github.com/darribas/95b…
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My first #rstats 📦on CRAN! {sfarrow} Reading/writing spatial objects with coordinate reference system info from/to Parquet files and partitioned datasets #rspatial cran.r-project.org/package=s…
Experimental #rstats 📦 {sfarrow} for reading/writing `sf` objects from/to Parquet files with {arrow}. Using consistent geo metadata to work with @GeoPandas. Currently quite simple; feedback and ideas welcome #rspatial github.com/wcjochem/sfarrow
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Excited that there will be not one but TWO Bayesian demography sessions at #PAA2021 on Wed 5 May! - 10:45PM CT: @AdrianRaftery1 @DrEmmaZang @mr_wheldon @jonathanbearak discussant @NCahill_Stat - 2:30PM CT: @caseyfbreen @sinafala @ChrisJochem @jonwakeblue discussant @CSchmert
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New paper now out with @AndyTatem @WorldPopProject. We introduce our #rstats 📦foot for calculating gridded morphology measures of building footprints doi.org/10.1371/journal.pone…
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The paper also presents an example of generating a gridded classification of settlements for England, Scotland, and Wales using only patterns in buildings and unsupervised clustering
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The package has flexibility to calculate morphology metrics on grids, in polygon zones, and using focal windows. Check out the code/docs here: wpgp.github.io/foot/ All the data and settlement classification from our paper are available! dx.doi.org/10.5258/SOTON/D16…
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Developing methods for classifying residential status of urban buildings: mdpi.com/2072-4292/12/23/384…
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Experimental #rstats 📦 {sfarrow} for reading/writing `sf` objects from/to Parquet files with {arrow}. Using consistent geo metadata to work with @GeoPandas. Currently quite simple; feedback and ideas welcome #rspatial github.com/wcjochem/sfarrow
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New WorldPop paper in @PNASNews as part of @grid3global - National population mapping from sparse survey data: pnas.org/content/early/2020/… - explore outputs at: apps.worldpop.org/woprVision…
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Explore our new Bayesian population estimate datasets produced as part of the @grid3global program through the woprVision app: apps.worldpop.org/woprVision…
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New @WorldPopProject paper led by @ChrisJochem - Classifying settlement types from multi-scale spatial patterns of building footprints, with @Need4GIS @AndyTatem Doug Leasure, Pat Jones @geogsouthampton @grid3global #openaccess #geospatial #urbananalytics journals.sagepub.com/doi/10.…
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At what time on New Year's had most of the world's people started the year 2020? A little trivia, and a fun use for @WorldPopProject data. github.com/wcjochem/newyear_… Happy (belated) New Year to all!
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Finishing up the last day at @efgs2019 with a session on Future #geospatial thinking. @ChrisJochem from @WorldPopProject @geogsouthampton presented on settlement classification from multi-scale spatial patterns of building footprints using a machine learning approach #efgs2019
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