CONVERT VECTOR TO RASTER HOW TO
CONVERT VECTOR TO RASTER UPDATE

GDAL is written in C++, with bindings for Python, so it is computationally efficient and can easily be scaled to supercomputing projects. The rasterize functionality from GDAL is a quick and easy way to automate polygon conversion with Python. Now you can see that each reach has been rasterized according to the channel id (chn_id) value. gdal.RasterizeLayer(chn_ras_ds,, lyr, options=) You may want to review the documentation for the rasterize options. This can easily be accomplished with gdal.RaterizeLayer() using the options, or attribute argument. Sometimes you may want to preserve a value from the vector attribute, like an identification value. gdal.RasterizeLayer(chn_ras_ds,, lyr)Ĭhn_ras_ds.GetRasterBand(1).SetNoDataValue(0.0)Ĭhn_ras_ds = None Rasterized channel network. By assigning a no-data a value, we get the output image below. In this case, the result is a value of ‘1’ inside of polygons, and ‘0’ outside of polygons.

CONVERT VECTOR TO RASTER UPDATE

We’re simply going to pass the new, empty raster, the band number of the new raster to update (band 1, the only band in our case), and the layer to rasterize to gdal.RasterizeLayer(). RasterYSize, 1, gdal.GDT_Float32)Ĭhn_ras_ds.SetGeoTransform(geot) GDAL.RasterizeLayer() drv_tiff = gdal.GetDriverByName('GTiff')Ĭhn_ras_ds = drv_tiff.Create(out_net, ras_ds. You can see my zonal statistics tutorial for an example of dynamically adjusting raster size for polygons. In this case, I’m making the new raster concurrent and orthogonal with the input raster. Now use gdal to create a new raster for the rasterized polygons. Geot = ras_ds.GetGeoTransform() Setup the New Raster For best results, ensure that both the raster and vector datasets use the same coordinate reference system. We’ll also need the geotransform values for the raster. Then we need to load a raster and a polygon layer. We’ll use the OSGEO Python modules to handle geographic data: gdal for raster data and ogr for vector data. Polygon stream network shown on hillshade. This is a simple example because the channel network is concurrent with the underlying grid, so no resampling of either layer needs to occur.

CONVERT VECTOR TO RASTER HOW TO

This article demonstrates multiple usages of gdal.RasterizeLayer().įor this example, we’ll consider how to rasterize the channel network, shown below, which is represented by polygons. In Python, the root of polygon (vector) to raster conversion lies with the gdal.RasterizeLayer() function. In a previous example, I demonstrated how vector to raster conversion can be implemented to calculate raster statistics within polygon boundaries. In such situations, conversion from vector to raster (or sometimes vice versa) is often the best option. Discrete, irregularly shaped polygons do not always play nice with structured, rectangular grids. This task can easily be accomplished manually, but it often becomes quite cumbersome when the process must be automated across a large number of features, time periods, and/or datasets. When you work with spatial data it’s inevitable that you will need to implement information from both a vector and raster data source for the same location.

Convert vector to raster