[GIS] Looking for QGIS equivalent of ArcGIS “Convex Hull” and “Circle” under Minimum Bounding Geometry (Data Management)

convex hullqgisqgis-3qgis-processing

I have the opportunity to run ArcGIS and QGIS side by side for a few months and was looking to see what comparisons there are.

So I'm interested to know if there is a similar tool on QGIS?

Best Answer

Yes, there is the "Convex hull", located under Vector > Geoprocessing tools > Convex hull.

Related Solutions

QGIS – Finding Equivalent of ArcGIS Shift Tool

The Rasmover plugin should do what you want.

You have to allow for experimental plugins to get it in the plugin list.

The result is a virtual raster file, which you can edit with a text editor to adjust the parameters if needed.

R Language – Creating Minimum Bounding Geometry Using the Convex Hull Method

I have a hidden function for calculating the Alpha Convex Hull (Pateiro-Lopez & Rodriguez-Casal 2009) in the development version of spatialEco. The reason this function is not in the CRAN release is due to licensing issues in the alphahull package.

Please note that this statistic only works for [x,y] data. Polygons are tricky because the bounding geometry is based on the vertices of each polygons, functionally making it based on points ([x,y] vertices). Because of this, if you want an alpha hull, it takes some extra data prep to get points representing the polygon boundaries.

Please install alphahull and remotes packages from CRAN and then install the development version of spatialEco using remotes::install_github.

remotes::install_github("jeffreyevans/spatialEco")
library(sp)
library(sf)
library(spatialEco)
library(dplyr)

Here we add some example data and create your polygons

data(meuse)
  sp::coordinates(meuse) = ~x+y
  meuse <- as(meuse, "sf")
  meuse_poly <- sf::st_buffer(meuse, dist = meuse$elev*15)

Now, we can get [x,y] data from the polygons using the sf::st_segmentize function.

poly_points <- sf::st_segmentize(meuse_poly, dfMaxLength = 5) %>% 
  sf::st_coordinates() %>% 
  as.data.frame() %>% 
  dplyr::select(X, Y) %>% 
  sf::st_as_sf(coords = c("X", "Y"))

We can then pass the points the the convexHull function

a <- spatialEco::convexHull(poly_points,alpha = 100000, sp=FALSE)
 plot(sf::st_geometry(a), cex=1.5, col="red") 
    plot(sf::st_geometry(meuse_poly), add=TRUE)

Let's test multiple alpha values to find an optima.

  par(mfcol=c(2,2))
    for (a in c(500, 1500, 5000, 100000)) {
    ch <- spatialEco::convexHull(poly_points, alpha = a, sp = FALSE)
      plot(sf::st_geometry(ch), cex=1.5, col="red") 
        plot(sf::st_geometry(meuse_poly), add=TRUE)
         title(paste0("alpha=", a))      
    }

References

Pateiro-Lopez & Rodriguez-Casal (2009) Generalizing the Convex Hull of a Sample: The R Package alphahull. Journal of Statistical Software 34(5):1-28 http://www.jstatsoft.org/v34/i05/paper

Best Answer

Related Solutions

QGIS – Finding Equivalent of ArcGIS Shift Tool

R Language – Creating Minimum Bounding Geometry Using the Convex Hull Method

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