Conversion

Convert Tools for GIS

• convert file format from shp to geojson or geojson to shp
• convert the CRS of vector and raster file

Import package

import geopandas as gpd 
import rasterio as rio
from Godream.plotimg import overlay_map
from Godream.convertool import convert_crs, convert_format

Convert file format

This tool work for vector data to convert file formate from shp to geojson or geojson to shp.

# set input/output
input_path = 'D:\DGEO\data\Rectan.geojson'
output_path = 'D:\DGEO\data\Rectan.shp'
output_format = 'ESRI Shapefile'

Convert file format Tool

This example, convert from geojson to shp file format.

If you want to convert from shp to geojson format. Please change this one:

output_format = 'GeoJSON'

and change input_path and output_path follow your approach.

convert_format(input_path, output_path, output_format)

Explore result

# read file
gdf = gpd.read_file(output_path)

CRS_file = gdf.crs
Info = gdf.info()

print(CRS_file,Info)

<class 'geopandas.geodataframe.GeoDataFrame'>
RangeIndex: 1 entries, 0 to 0
Data columns (total 2 columns):
 #   Column    Non-Null Count  Dtype   
---  ------    --------------  -----   
 0   FID       1 non-null      int64   
 1   geometry  1 non-null      geometry
dtypes: geometry(1), int64(1)
memory usage: 144.0 bytes
epsg:4326 None

Convert CRS

Convert Geographic Coodinate System(CRS)

This example will change the crs from EPSG:32647 to EPSG:4326

# set input/output path
input_path = 'D:\DGEO\data\Landsat8_stack.TIF'  # Replace with the path to your input GeoTIFF file
output_path = 'D:\DGEO\data\Landsat8_stack44.tif'  # Replace with the desired output file path
new_crs = 4326  # EPSG:4326

Explore CRS of file input

You can see the crs of input file is EPSG:32647

# read file
ds=rio.open(input_path)

# see metedata
ds.meta

{'driver': 'GTiff',
 'dtype': 'uint16',
 'nodata': None,
 'width': 7551,
 'height': 7711,
 'count': 3,
 'crs': CRS.from_epsg(32647),
 'transform': Affine(30.0, 0.0, 575085.0,
        0.0, -30.0, 1714215.0)}

Convert CRS Tool

convert_crs(input_path, output_path, new_crs)

Explore result

Now the crs of output is EPSG:4326

# read file
ds=rio.open(output_path)

# show meta data to see the result crs
ds.meta

{'driver': 'GTiff',
 'dtype': 'uint16',
 'nodata': None,
 'width': 7712,
 'height': 7670,
 'count': 3,
 'crs': CRS.from_epsg(4326),
 'transform': Affine(0.00027457111894358207, 0.0, 99.69355065482286,
        0.0, -0.00027457111894358207, 15.504185371111015)}

raster_path = [output_path]
overlay_map(raster_file=raster_path, zoom=9)