{"id":4571,"date":"2024-06-06T03:14:39","date_gmt":"2024-06-06T03:14:39","guid":{"rendered":"https:\/\/blogs.lincoln.ac.nz\/gis\/?p=4571"},"modified":"2024-06-06T03:14:40","modified_gmt":"2024-06-06T03:14:40","slug":"vector-makes-its-mark","status":"publish","type":"post","link":"https:\/\/blogs.lincoln.ac.nz\/gis\/vector-makes-its-mark\/","title":{"rendered":"Vector Makes Its Mark"},"content":{"rendered":"\n

A cornucopia of vector tools help with some marking<\/em><\/p>\n\n\n\n

While both students and academics are celebrating the end of another semester, it may well be a bit short-lived. Poor students have exams to cope with and poor academics have scads of marking to endure. One of the GIS courses has recently done a project on sea level rise impacts, and as I set out to get the marking done, it was clear that I was going to have to have do some analysis to help make that as painless as possible.<\/p>\n\n\n\n

Let me explain: for this project, we were looking at a rise in sea level of 1.0 m (as projected by the CCC by 2051) plus an additional 1.08 m to account for high tide effects (as outlined by NIWA), for a total of 2.08 m above current sea level. As a first part of this, I used a LiDAR DEM to identify all those areas up to that height, ran some filters (Focal Statistics<\/a>, for those playing at home) to weed out some of the very small (but numerous) unconnected areas and then converted that to a polygon layer (called SLRZone), as shown below:<\/p>\n\n\n\n

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Are study area extends from the Waimakariri River, all the way around Banks Peninsula and out to Akaroa. Rather than look at all these areas, I chose to break things down so students could look at the impact for a selected suburb, chosen from a layer called AffectedAreas, here shown with purpley boundaries (these are the SA2<\/a> areas from the 2018 census via StatsNZ):<\/p>\n\n\n\n

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With these two layers, students can then pick one of the suburbs and then for each, create a bit of an inventory of the roads, buildings, landcovers and people affected – classic GIS stuff, yes?<\/p>\n\n\n\n

For most, that meant selecting a suburb, exporting it to a new layer, then using that to Clip <\/a>the SLRZone layer, thus giving them the flooded extent within each suburb. This can then be used to clip out each of the important features from the right data layer and total up the important elements.<\/p>\n\n\n\n

When it came to marking, things were a bit different, as I will need to know the “correct” values for each suburb so I can check their results. Rather than do each one individually, I wanted to optimise my time by doing this analysis for all suburbs at once. Along the way, I ended up using a range of some of the more useful vector tools, so I thought it might be helpful to cover them here. There are the key steps I’ll cover:<\/p>\n\n\n\n