LIDAR data and flooding

I’ve been visiting my family in northern England over Christmas. We had a lot of rain. Fortunately, no houses in my village flooded, but others in the region were devastated and further extreme weather is forecast for the next few days.

Information on the risk of flooding at a property is required before action to defend against floods or to minimise the harm that floods cause, can be undertaken.

The UK Environment Agency produces flood risk maps. These are very useful, but if you want to know more details – how high is your property above the river, do you live in a floodable depression – you need to get your hands on a digital terrain (or elevation) model.

LIDAR (similar to RADAR, but with light rather than radiowaves) can be used to generate very high resolution digital terrain models. The Environment Agency has done this for most of England and Wales. The data can be downloaded free of charge under the Open Government Licence. You want the digital terrain model rather than the digital surface model (which shows the height of roofs rather than the ground).

The data are easy to process in R to make maps using the raster package after they have been unzipped (yes, you can do this with R with unzip() if you really want to).

This code imports the data from four tiles, merges and plots them.

 
library(raster)
ny5816<-raster("d:/temp/LIDAR-DTM-2M-NY51/ny5816_DTM_2m.asc")
ny5716<-raster("d:/temp/LIDAR-DTM-2M-NY51/ny5716_DTM_2m.asc")
ny5817<-raster("d:/temp/LIDAR-DTM-2M-NY51/ny5817_DTM_2m.asc")
ny5717<-raster("d:/temp/LIDAR-DTM-2M-NY51/ny5717_DTM_2m.asc")

f1<-merge(ny5816, ny5716, ny5817, ny5717)
plot(f1)
points(358330, 516976, pch = 16, col = 2)
#numbers are grid reference from http://gridreferencefinder.com/

A legend, scale bar, etc could be added. The question here is whether Winter Tarn Farm (at the red triangle) is at risk of flooding by the epynonymous tarn. Winter Tarn, as its name suggests, is a transient water body that occurs after wet weather, usually in winter.

I’m going to use filledContour() to make a map that is easier to interpret. Rather than using the default contour levels, I’m going to focus in on the elevation range of most interest, from the bottom of the depression upto the farm. For orientation, I’m going to add some road and streams using shapefiles downloaded from the Ordnance Survey.

filledContour() is a wrapper for filled.contour() and shares its somewhat unusual syntax. The output is actually a combination the filled contour plot and a legend. The coordinate system for these plots is only used internally: you cannot annotate the contour plot (easily) after it is produced. Any annotation needs to be specified in the plot.axes argument.

library(sp)
library(rgdal)
surfacewater <- readOGR("d:/temp/opmplc_essh_ny/OSOpenMapLocal (ESRI Shape File) NY/data", "NY_SurfaceWater_Line")
road <- readOGR("d:/temp/opmplc_essh_ny/OSOpenMapLocal (ESRI Shape File) NY/data", "NY_Road")

f2<-crop(f1, extent(c(357223,358993,516008,517764)))#restrict to area of interest
f1
f2

x11(7.9, 7)
par(mar=c(3, 3, 3, 3))
filledContour(f2,  
              plot.axes = { 
                points(357947, 517092, pch = 17, col = 2)
                arrows(x0 = 358100, x1 = 358600, y0 = 516100, y1 = 516100, length = 0, lwd = 2)
                text(x = 358350, y = 516150, label = "500 m")
                arrows(x0 = 358900, x1 = 358900, y0 = 517450, y1 = 517650, length = .2, lwd = 2, code = 2)
                text(x = 358900, y = 517700, label = "N")
                lines(surfacewater, col = 4)
                lines(road, col = 2)
                },
                asp = 1 ,
                levels = c(263, 270:280, 290,305, 315), 
                nlevels = 15,
                color.palette = topo.colors)
par(xpd = TRUE)
text(x=358890, y=515940, label="Elevation\nm")
Topographic map of Winter Tarn

Topographic map of Winter Tarn

Winter Tarn Farm appears to be higher than the overflow from Winter Tarn to the northwest, so is not at risk of being flooded by the tarn.

It would be possible to extract height for specific locations, or along transects using extract() from the raster package. Something for another day perhaps.

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About richard telford

Ecologist with interests in quantitative methods and palaeoenvironments
This entry was posted in Uncategorized and tagged . Bookmark the permalink.

3 Responses to LIDAR data and flooding

  1. Looking at the map, I’d just make sure that the overflow from the tarn doesn’t become blocked, as it looks like it could be quite narrow. Having said that, people in the ‘olden days’ were quite switched on when it came to flooding and rarely put up buildings where they could be inundated. It seems to be an awareness we ‘moderns’ have lost. 🙂

    • The channel looks like a perfect place to hide building rubble!

      The area is on limestone so I suspect a lot of the draining could be underground.

      I wonder whether they were better at siting buildings centuries ago. They could have built in random places and we see only the surviving buildings, not those lost to floods.

  2. Magma says:

    I’ve used lidar data for years, and it’s both deeply fun to play with and highly useful. But I think it’s a stretch to expect the public in general to use them, or even to look at hazard maps generated using lidar and other data sets by municipal, county/state/district or federal government bodies.
    I don’t know that matters will change until insurers refusing to cover houses at too great a risk combines with the general practice of lenders refusing to issue mortgages to uninsured houses.

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