Python gdal.RasterizeLayer() Examples

The following are 7 code examples of gdal.RasterizeLayer(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module gdal , or try the search function .
Example #1
Source File: function_dataraster.py    From dzetsaka with GNU General Public License v3.0 8 votes vote down vote up 
def rasterize(data, vectorSrc, field, outFile):
    dataSrc = gdal.Open(data)
    import ogr
    shp = ogr.Open(vectorSrc)

    lyr = shp.GetLayer()

    driver = gdal.GetDriverByName('GTiff')
    dst_ds = driver.Create(
        outFile,
        dataSrc.RasterXSize,
        dataSrc.RasterYSize,
        1,
        gdal.GDT_UInt16)
    dst_ds.SetGeoTransform(dataSrc.GetGeoTransform())
    dst_ds.SetProjection(dataSrc.GetProjection())
    if field is None:
        gdal.RasterizeLayer(dst_ds, [1], lyr, None)
    else:
        OPTIONS = ['ATTRIBUTE=' + field]
        gdal.RasterizeLayer(dst_ds, [1], lyr, None, options=OPTIONS)

    data, dst_ds, shp, lyr = None, None, None, None
    return outFile
Example #2
Source File: terrain_helper.py    From CityEnergyAnalyst with MIT License 6 votes vote down vote up 
def calc_raster_terrain_fixed_elevation(crs, elevation, grid_size, raster_path, locator, x_max, x_min, y_max,
                                        y_min):
    # local variables:
    temp_shapefile = locator.get_temporary_file("terrain.shp")
    cols = int((x_max - x_min) / grid_size)
    rows = int((y_max - y_min) / grid_size)
    shapes = Polygon([[x_min, y_min], [x_max, y_min], [x_max, y_max], [x_min, y_max], [x_min, y_min]])
    geodataframe = Gdf(index=[0], crs=crs, geometry=[shapes])
    geodataframe.to_file(temp_shapefile)
    # 1) opening the shapefile
    source_ds = ogr.Open(temp_shapefile)
    source_layer = source_ds.GetLayer()
    target_ds = gdal.GetDriverByName('GTiff').Create(raster_path, cols, rows, 1, gdal.GDT_Float32)  ##COMMENT 2
    target_ds.SetGeoTransform((x_min, grid_size, 0, y_max, 0, -grid_size))  ##COMMENT 3
    # 5) Adding a spatial reference ##COMMENT 4
    target_dsSRS = osr.SpatialReference()
    target_dsSRS.ImportFromProj4(crs)
    target_ds.SetProjection(target_dsSRS.ExportToWkt())
    band = target_ds.GetRasterBand(1)
    band.SetNoDataValue(-9999)  ##COMMENT 5
    gdal.RasterizeLayer(target_ds, [1], source_layer, burn_values=[elevation])  ##COMMENT 6
    target_ds = None  # closing the file
Example #3
Source File: Exploratory Spatial Data Analysis in PySAL.py    From python-urbanPlanning with MIT License 5 votes vote down vote up 
def Feature_to_Raster(input_shp, output_tiff, cellsize, field_name=False, NoData_value=-9999):
    """
    Converts a shapefile into a raster
    """

    # Input
    inp_driver = ogr.GetDriverByName('ESRI Shapefile')
    inp_source = inp_driver.Open(input_shp, 0)
    inp_lyr = inp_source.GetLayer()
    inp_srs = inp_lyr.GetSpatialRef()

    # Extent
    x_min, x_max, y_min, y_max = inp_lyr.GetExtent()
    x_ncells = int((x_max - x_min) / cellsize)
    y_ncells = int((y_max - y_min) / cellsize)

    # Output
    out_driver = gdal.GetDriverByName('GTiff')
    if os.path.exists(output_tiff):
        out_driver.Delete(output_tiff)
    out_source = out_driver.Create(output_tiff, x_ncells, y_ncells,1, gdal.GDT_Int16)
    print("+"*50)
    print(x_ncells, y_ncells,1, gdal.GDT_Int16)

    out_source.SetGeoTransform((x_min, cellsize, 0, y_max, 0, -cellsize))
    out_source.SetProjection(inp_srs.ExportToWkt())
    out_lyr = out_source.GetRasterBand(1)
    out_lyr.SetNoDataValue(NoData_value)

    # Rasterize
    # print(inp_lyr)
    if field_name:
        gdal.RasterizeLayer(out_source, [1], inp_lyr,options=["ATTRIBUTE={0}".format(field_name)])
    else:
        gdal.RasterizeLayer(out_source, [1], inp_lyr, burn_values=[1])

    # Save and/or close the data sources
    inp_source = None
    out_source = None

    # Return
    return output_tiff 

#geo_silhouettes
Example #4
Source File: pointsClustering.py    From python-urbanPlanning with MIT License 5 votes vote down vote up 
def pts2raster(shapefile,RASTER_PATH,cellSize,field_name=False):
    from osgeo import gdal, ogr

    # Define pixel_size and NoData value of new raster
    pixel_size = cellSize
    NoData_value = -9999
    
    # Filename of input OGR file
    vector_ptsShp_fn = shapefile
    
    # Filename of the raster Tiff that will be created
    raster_ptsShp_fn = RASTER_PATH
    
    # Open the data source and read in the extent
    source_ds = ogr.Open(vector_ptsShp_fn)
    source_layer = source_ds.GetLayer()
    x_min, x_max, y_min, y_max = source_layer.GetExtent()
    
    # Create the destination data source
    x_res = int((x_max - x_min) / pixel_size)
    y_res = int((y_max - y_min) / pixel_size)
    target_ds = gdal.GetDriverByName('GTiff').Create(raster_ptsShp_fn, x_res, y_res, 1, gdal.GDT_Int32 )
    target_ds.SetGeoTransform((x_min, pixel_size, 0, y_max, 0, -pixel_size))
    band = target_ds.GetRasterBand(1)
    band.SetNoDataValue(NoData_value)
    
    # Rasterize
    # gdal.RasterizeLayer(target_ds, [1], source_layer, burn_values=[0])
    # Rasterize
    if field_name:
        gdal.RasterizeLayer(target_ds,[1], source_layer,options=["ATTRIBUTE={0}".format(field_name)])
        # print("write:",field_name)
    else:
        gdal.RasterizeLayer(target_ds,[1], source_layer,burn_values=[-1])   
    return gdal.Open(RASTER_PATH).ReadAsArray() 

#批量计算
Example #5
Source File: functions.py    From hants with Apache License 2.0 4 votes vote down vote up 
def Feature_to_Raster(input_shp, output_tiff,
                      cellsize, field_name=False, NoData_value=-9999):
    """
    Converts a shapefile into a raster
    """

    # Input
    inp_driver = ogr.GetDriverByName('ESRI Shapefile')
    inp_source = inp_driver.Open(input_shp, 0)
    inp_lyr = inp_source.GetLayer()
    inp_srs = inp_lyr.GetSpatialRef()

    # Extent
    x_min, x_max, y_min, y_max = inp_lyr.GetExtent()
    x_ncells = int((x_max - x_min) / cellsize)
    y_ncells = int((y_max - y_min) / cellsize)

    # Output
    out_driver = gdal.GetDriverByName('GTiff')
    if os.path.exists(output_tiff):
        out_driver.Delete(output_tiff)
    out_source = out_driver.Create(output_tiff, x_ncells, y_ncells,
                                   1, gdal.GDT_Int16)

    out_source.SetGeoTransform((x_min, cellsize, 0, y_max, 0, -cellsize))
    out_source.SetProjection(inp_srs.ExportToWkt())
    out_lyr = out_source.GetRasterBand(1)
    out_lyr.SetNoDataValue(NoData_value)

    # Rasterize
    if field_name:
        gdal.RasterizeLayer(out_source, [1], inp_lyr,
                            options=["ATTRIBUTE={0}".format(field_name)])
    else:
        gdal.RasterizeLayer(out_source, [1], inp_lyr, burn_values=[1])

    # Save and/or close the data sources
    inp_source = None
    out_source = None

    # Return
    return output_tiff
Example #6
Source File: raster_conversions.py    From wa with Apache License 2.0 4 votes vote down vote up 
def Vector_to_Raster(Dir, shapefile_name, reference_raster_data_name):
    """
    This function creates a raster of a shp file

    Keyword arguments:
    Dir --
        str: path to the basin folder
    shapefile_name -- 'C:/....../.shp'
        str: Path from the shape file
    reference_raster_data_name -- 'C:/....../.tif'
        str: Path to an example tiff file (all arrays will be reprojected to this example)
    """

    from osgeo import gdal, ogr

    geo, proj, size_X, size_Y=Open_array_info(reference_raster_data_name)

    x_min = geo[0]
    x_max = geo[0] + size_X * geo[1]
    y_min = geo[3] + size_Y * geo[5]
    y_max = geo[3]
    pixel_size = geo[1]

    # Filename of the raster Tiff that will be created
    Dir_Basin_Shape = os.path.join(Dir,'Basin')
    if not os.path.exists(Dir_Basin_Shape):
        os.mkdir(Dir_Basin_Shape)

    Basename = os.path.basename(shapefile_name)
    Dir_Raster_end = os.path.join(Dir_Basin_Shape, os.path.splitext(Basename)[0]+'.tif')

    # Open the data source and read in the extent
    source_ds = ogr.Open(shapefile_name)
    source_layer = source_ds.GetLayer()

    # Create the destination data source
    x_res = int(round((x_max - x_min) / pixel_size))
    y_res = int(round((y_max - y_min) / pixel_size))

    # Create tiff file
    target_ds = gdal.GetDriverByName('GTiff').Create(Dir_Raster_end, x_res, y_res, 1, gdal.GDT_Float32, ['COMPRESS=LZW'])
    target_ds.SetGeoTransform(geo)
    srse = osr.SpatialReference()
    srse.SetWellKnownGeogCS(proj)
    target_ds.SetProjection(srse.ExportToWkt())
    band = target_ds.GetRasterBand(1)
    target_ds.GetRasterBand(1).SetNoDataValue(-9999)
    band.Fill(-9999)

    # Rasterize the shape and save it as band in tiff file
    gdal.RasterizeLayer(target_ds, [1], source_layer, None, None, [1], ['ALL_TOUCHED=TRUE'])
    target_ds = None

    # Open array
    Raster_Basin = Open_tiff_array(Dir_Raster_end)

    return(Raster_Basin)
Example #7
Source File: functions.py    From wa with Apache License 2.0 4 votes vote down vote up 
def Feature_to_Raster(input_shp, output_tiff,
                      cellsize, field_name=False, NoData_value=-9999):
    """
    Converts a shapefile into a raster
    """

    # Input
    inp_driver = ogr.GetDriverByName('ESRI Shapefile')
    inp_source = inp_driver.Open(input_shp, 0)
    inp_lyr = inp_source.GetLayer()
    inp_srs = inp_lyr.GetSpatialRef()

    # Extent
    x_min, x_max, y_min, y_max = inp_lyr.GetExtent()
    x_ncells = int((x_max - x_min) / cellsize)
    y_ncells = int((y_max - y_min) / cellsize)

    # Output
    out_driver = gdal.GetDriverByName('GTiff')
    if os.path.exists(output_tiff):
        out_driver.Delete(output_tiff)
    out_source = out_driver.Create(output_tiff, x_ncells, y_ncells,
                                   1, gdal.GDT_Int16)

    out_source.SetGeoTransform((x_min, cellsize, 0, y_max, 0, -cellsize))
    out_source.SetProjection(inp_srs.ExportToWkt())
    out_lyr = out_source.GetRasterBand(1)
    out_lyr.SetNoDataValue(NoData_value)

    # Rasterize
    if field_name:
        gdal.RasterizeLayer(out_source, [1], inp_lyr,
                            options=["ATTRIBUTE={0}".format(field_name)])
    else:
        gdal.RasterizeLayer(out_source, [1], inp_lyr, burn_values=[1])

    # Save and/or close the data sources
    inp_source = None
    out_source = None

    # Return
    return output_tiff