Publications by mikerspencer
Hydrological uncertainty – Manning’s equation
John Yagecic put out a great little blog post with accompanying app this week. He looked at the uncertainty from using vague parameters in Manning’s equation to estimate river flow. He made the great step of making the source code available. I forked this to the Open Hydrology repository and converted the project to metric units! Amazing! This ...
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EARL 2016 talk
I spoke on 14th September at the EARL (Effective Applications of the R Language) conference in London. This is event is concerned exclusively with the R programming language and it was the first time I’ve attended an event like this (user group meetings excluded). It was excellent, with a diverse range of interesting talks, I certainly plan to ...
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Converting (British) National Grid references
I was supplied spatial point data this summer where the locations were detailed in Ordnance Survey’s National Grid (NGR) format. If you’re not familiar with it, rather than using eastings and northings (in metres) to define location – it splits the Great Britain into lettered grid squares and then defines locations within each lettered grid...
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R – Change columns names in a spatial dataframe
Ordnance Survey have a great OpenRoads dataset, but unfortunately it contains a column called ‘primary’, which is a keyword in SQL. This makes it challenging/impossible to import the OpenRoads dataset into a SQL database (e.g. GRASS), without changing the offending column name. Enter R! Or any other capable programming language. The following...
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R – iteratively changing column classes
When you write an ESRI Shapefile from R, writeOGR assumes your numeric fields are real numbers and so you get a lot of redundant zeros appended. This is misleading and distracting when you present data to third parties. You can fix this by changing column class from numeric to integer: class(df$col) = "integer" However, this only changes one col...
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R with GRASS GIS – easiest Munros
I’ve been having a more sustained play with R and GRASS together. I’ve previously used them, in tandem, for processing satellite images, but haven’t been much further. In this post I’ll look at finding the nearest roads to mountain summits, querying their elevations and presenting summary statistics. First off, you can run R in GRASS or G...
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RPostgreSQL and schemas
The database PostgreSQL can have different schemas. These work like a window for users, where they get to see specific things within a database, e.g. tables. In this post we’ll look at how we can access a database with a specific schema. You’ll know you need this page if you get errors like: `Error in `[.data.frame`(dbGetQuery(conn, paste("se...
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Spatial networks – case study St James centre, Edinburgh (1/3)
Last year I spent a bit of time learning about routing and network analysis. I created a map of distance from each GB postcode to the nearest railway station. At the time my local council were also looking at changing school catchments and building new schools. This also seemed like an excellent project for routing analysis. I made some progress ...
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Celebrating 20 years of CRAN
In April I spoke for the Royal Statistical Society (Glasgow branch) at their event celebrating 20 years of CRAN. The other speakers were Charis Chanialidis and Colin Gillespie. Like most people I find watching myself speak really cringe worthy, but perhaps it’s not so bad! The three talks are here: Related To leave a comment for the author, p...
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Spatial networks – case study St James centre, Edinburgh (2/3)
This is part two in a series I’m writing on network analysis. The first part is here. In this section I’m going to cover allocating resources, again using the St James’ development in Edinburgh as an example. Most excitingly (for me), the end of this post covers the impact of changes in resource allocation. Edinburgh (and surrounds) has mor...
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