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Results tagged with python
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user 97137
Python is an open source interpreted programming language used in many GIS programs.
0
votes
2
answers
1k
views
Sum of values in raster
Upon importing a raster file, how can I get the sum of all values given in the raster file?
import rioxarray as rxr
raster= rxr.open_rasterio(
'raster.tif',
masked=True
).squeeze()
raste …
- 541
9
votes
1
answer
875
views
Assigning new values to polygon based on overlapping area with other polygons
I have two square polygons df1 and df2. Both polygons are assigned a value of 10 (df1) and 20 (df2) in the "content" column. Let's assume, I have a circle with the midpoint 1.5,1.5 and a radius of 1. …
- 541
-1
votes
1
answer
2k
views
Convert Esri ASCII grid raster format to GeoJSON
I received data as *.asc file. How can I convert the ASCII data into a *.GeoJson file including polygons and the band data? I've tried various approaches with rasterio and gdal but they always returne …
- 541
1
vote
Accepted
Convert Esri ASCII grid raster format to GeoJSON
I am not great with Python so please forgive me the style of code. I am sure, there are nicer way to achieve the same results. …
- 541
1
vote
2
answers
10k
views
How to apply GDAL polygonize?
To me, the input parameters are cryptic and I failed to figure out the exact commands required for application in Python.
** Edit**
With help of Ben's comment I got to this point:
from osgeo import gdal … , ogr
import sys
# this allows GDAL to throw Python Exceptions
gdal.UseExceptions()
# get raster datasource
src_ds = gdal.Open(inputFilename)
srcband = src_ds.GetRasterBand(1)
# create output datasource …
- 541
1
vote
2
answers
2k
views
Extract population count from GeoTIFF based on mask layer
I downloaded Population Count data from Gridded Population of the World (GPW), v4 as a *.GeoTIFF file. In a next step, I would like to extract the population count of a given area based on a mask laye …
- 541
5
votes
1
answer
648
views
Robinson projection in GeoPandas
How can I apply Robinson projection in a GeoPandas plot?
import geopandas as gpd
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
world.plot(column='pop_est')
- 541