{"action":"created","issue":{"url":"https://api.github.com/repos/Robinlovelace/geocompr/issues/12","repository_url":"https://api.github.com/repos/Robinlovelace/geocompr","labels_url":"https://api.github.com/repos/Robinlovelace/geocompr/issues/12/labels{/name}","comments_url":"https://api.github.com/repos/Robinlovelace/geocompr/issues/12/comments","events_url":"https://api.github.com/repos/Robinlovelace/geocompr/issues/12/events","html_url":"https://github.com/Robinlovelace/geocompr/issues/12","id":222020926,"number":12,"title":"Ideas for additional topics to include","user":{"login":"Robinlovelace","id":1825120,"avatar_url":"https://avatars2.githubusercontent.com/u/1825120?v=4","gravatar_id":"","url":"https://api.github.com/users/Robinlovelace","html_url":"https://github.com/Robinlovelace","followers_url":"https://api.github.com/users/Robinlovelace/followers","following_url":"https://api.github.com/users/Robinlovelace/following{/other_user}","gists_url":"https://api.github.com/users/Robinlovelace/gists{/gist_id}","starred_url":"https://api.github.com/users/Robinlovelace/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Robinlovelace/subscriptions","organizations_url":"https://api.github.com/users/Robinlovelace/orgs","repos_url":"https://api.github.com/users/Robinlovelace/repos","events_url":"https://api.github.com/users/Robinlovelace/events{/privacy}","received_events_url":"https://api.github.com/users/Robinlovelace/received_events","type":"User","site_admin":false},"labels":[{"id":555350156,"url":"https://api.github.com/repos/Robinlovelace/geocompr/labels/enhancement","name":"enhancement","color":"84b6eb","default":true}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":21,"created_at":"2017-04-16T17:04:02Z","updated_at":"2018-03-01T23:38:17Z","closed_at":null,"author_association":"OWNER","body":"List of suggests we aim to include. Further suggests below welcome - we'll put them in the check-list if do-able in the time available.\r\n\r\n## Part I\r\n\r\n- [ ] Short discussion of PostGIS\r\n- [ ] Additional operations on vector data: `st_convex_hull`, `st_triangulate`, `st_polygonize`, `st_segmentize`, `st_boundary` and `st_node` - see https://github.com/Robinlovelace/geocompr/commit/c1d1c0e1737fc090fa8e6c7ebb743083b5c618db\r\n\r\n## Part II\r\n- [x] Import and preparation of messy data (done in c7 - tidying the German Census)\r\n- [x] store location analysis\r\n- [ ] Mention serving routing (and other?) geo* services locally - see https://github.com/Robinlovelace/geocompr/commit/8891b7d1831fb336cc62d92db11a83b9903ab869\r\n\r\n## Part III\r\n\r\n- [ ] Content in the algorithms chapter building on work by [Stan Openshaw](https://scholar.google.com/citations?user=gqrgKhkAAAAJ&hl=en&oi=ao), father of 'geocomputation' e.g. a function that implements GAM, with reference to the series of conferences called GeoCompution. [aka how to implement spatial ideas in R]\r\n- [x] An integration with a GIS software - GRASS GIS (rgrass7), SAGA (RSAGA), QGIS (RQGIS), and ArcGIS (arcgisbinding)\r\n- [ ] Add opacity variability to help overcome issues with thematic maps - see #32 \r\n- [ ] Include something on facets ordered by location\r\n- [ ] mapedit: https://github.com/r-spatial/mapedit \r\n- [ ] 3d maps\r\n\r\n## Other\r\n\r\n- [ ] A section of a current GIS limitations/missing pieces (mesh-based models (triangulations and quad meshes), multi-dimensional linear data (any time-recording based sensor, tracking data), and dense scanning data (LiDaR and other remote sensing.)\r\n- [ ] ~~A chapter on~~ Link to resources on spatial regression, spatial autocorrelation\r\n- [ ] An outlook to the future of geostatistical computing in the cloud and related techniques \r\n- [ ] Activity tracking example, e.g. based on GPS data from OSM\r\n- [ ] Ecological movement / 'homerange' example\r\n- [ ] Weather data, e.g. from http://data.ceda.ac.uk/badc/ukcp09/data/gridded-land-obs/gridded-land-obs-daily/grid/netcdf/minimum-temperature/\r\n- [ ] Not a topic but an idea: add disqus comments, described here: https://github.com/rstudio/bookdown/blob/master/inst/examples/05-editing.Rmd#collaboration"},"comment":{"url":"https://api.github.com/repos/Robinlovelace/geocompr/issues/comments/369769631","html_url":"https://github.com/Robinlovelace/geocompr/issues/12#issuecomment-369769631","issue_url":"https://api.github.com/repos/Robinlovelace/geocompr/issues/12","id":369769631,"user":{"login":"gisma","id":2327278,"avatar_url":"https://avatars2.githubusercontent.com/u/2327278?v=4","gravatar_id":"","url":"https://api.github.com/users/gisma","html_url":"https://github.com/gisma","followers_url":"https://api.github.com/users/gisma/followers","following_url":"https://api.github.com/users/gisma/following{/other_user}","gists_url":"https://api.github.com/users/gisma/gists{/gist_id}","starred_url":"https://api.github.com/users/gisma/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gisma/subscriptions","organizations_url":"https://api.github.com/users/gisma/orgs","repos_url":"https://api.github.com/users/gisma/repos","events_url":"https://api.github.com/users/gisma/events{/privacy}","received_events_url":"https://api.github.com/users/gisma/received_events","type":"User","site_admin":false},"created_at":"2018-03-01T23:38:17Z","updated_at":"2018-03-01T23:38:17Z","author_association":"NONE","body":"few weeks ago Hanna Meyer @HannaMeyer from the Envrionmental Informatics working group in Marburg  had her Phd defense which was btw awesome.... \r\nHer central methodological aspect was the spatio-temporal cross-validation in machine learning methods. she developed the concept and method to avoid overfitting by leave location out and or leave locationtime out cv and improved the model performance including a forward feature selection approach. This part is just published [Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation](https://www.sciencedirect.com/science/article/pii/S1364815217310976?via%3Dihub).\r\nI think it is an very important issue to deal! Hanna has impressively proved that the vast majority of studies that use machine learning techniques for prediction issues do not consider spatio-temporal dependencies so as a result they mercilessly overestimate the quality of their models.\r\nWould be fine to integrate some of this stuff if somehow possible @HannaMeyer"}}
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