我们如何创建输入栅格的掩膜版本，其中落在其中一个字段中的像素设置为 ' 而其他设置为 0？

Question

我以为一切都写得很好，但似乎我遗漏了一些东西。当我试图断言它时，我仍然得到了错误的答案。参见代码

def masked_raster(input_file, raster_file):
# Create a masked version of the input raster where pixels falling within one of the fields are set to `1` and pixels outside the fields are set to `0`

with fiona.open(input_file, "r") as shapefile:
geoms = [feature["geometry"] for feature in shapefile]
with rasterio.open(raster_file) as src:
out_img, out_transform = mask(src, geoms, invert = True, crop=False, all_touched= True)
out_meta = src.meta.copy()
out_meta.update({"driver": "GTiff",
"height": out_img.shape[1],
"width": out_img.shape[2],
"transform": out_transform})

return out_img
def reproject_raster(raster_file, dst_crs):
# Reproject the input raster to the provided CRS
with rasterio.open('masked2.tif', "w", **out_meta) as dst:
dst.write(out_image)

dst = src

return dst

要测试我使用的代码：

assert masked_raster('crops.geojson', 'crops.tif')[0].sum() == 1144636.0, "Sorry wrong answer"
assert str(reproject_raster('crops.tif', 'EPSG:4326').crs) == 'EPSG:4326', "Sorry wrong answer"

Answer 1

这里有一个详细的解决方案，我使用内联注释来回答

"""
Solution
"""
import fiona
import rasterio
import rasterio.mask
import pycrs

def masked_raster(input_file, raster_file):
# Create a masked version of the input raster where pixels falling within one of the fields are set to `1` and pixels outside the fields are set to `0`

#open the geojson file with fiona
with fiona.open("crops.geojson", "r") as geojson:
#creating features
features = [feature["geometry"] for feature in geojson]
#open raster file with rasterio
with rasterio.open("crops.tif") as src:
#clip the raster with polygon
out_img, out_transform = rasterio.mask.mask(src, features, crop=True)
#copy meta data of the src
out_meta = src.meta.copy()
return out_img
def reproject_raster(raster_file, dst_crs):
# Reproject the input raster to the provided CRS

#import rioxarray module and crs
import rioxarray
from rasterio.crs import CRS
#open raster file ("crops.tif") using rioxaarray
raster_file = rioxarray.open_rasterio(raster_file, masked=True).squeeze()

#create the crs object
crs_wgs84 = CRS.from_string(dst_crs)
raster_4326 = raster_file.rio.set_crs(crs_wgs84) 
#convert DataArray to RasterArray to be able to use .crs on the output
dst = raster_4326.rio

return dst