$ pip3 install --index-url https://mirrors.aliyun.com/pypi/simple --trusted-host mirrors.aliyun.com rioxarray
$ pip3 install GDAL-3.4.3-cp310-cp310-win_amd64.whl$ pip3 install rasterio-1.2.10-cp310-cp310-win_amd64.whl$ pip3 install --index-url https://mirrors.aliyun.com/pypi/simple --trusted-host mirrors.aliyun.com rioxarray
#!/usr/bin/python3
# -*- encoding: utf-8 -*-
"""
@File : gis_util.py
@Desc : GIS 文件格式转换工具
@Version : v1.0
@Time : 2023/02/23
@Author : xiaoQQya
@Contact : xiaoQQya@126.com
"""
import numpy as np
import rioxarray
import xarray as xrdef ascii_to_tiff(asc_path: str, tif_path: str, tif_attrs: dict = {}) -> None:"""ASCII 文件转 TIFF 文件:param asc_path: ASCII 文件路径, 例如: ./test.asc:type asc_path: str:param tif_path: TIFF 文件输出路径, 例如: ./test.tif:type tif_path: str:param tif_attrs: TIFF 文件属性, 例如: {"unit": "m"}, defaults to {}:type tif_attrs: dict, optional"""# 获取 ASCII 文件前 6 行属性值attrs: dict = {}with open(asc_path, "r") as file:for _ in range(6):line: str = file.readline().strip().split(" ")attrs[line[0].lower()] = eval(line[-1])if "xllcenter" not in attrs.keys():attrs["xllcenter"] = attrs["xllcorner"] + 0.5 * attrs["cellsize"]attrs["yllcenter"] = attrs["yllcorner"] + 0.5 * attrs["cellsize"]# 计算每个点经纬度坐标longitudes = [attrs["xllcenter"] + i * attrs["cellsize"] for i in range(attrs["ncols"])]latitudes = [attrs["yllcenter"] + i * attrs["cellsize"] for i in range(attrs["nrows"])]latitudes.reverse()# 读取 ASCII 文件矩阵数值data = np.loadtxt(asc_path, skiprows=6)data[data == attrs["nodata_value"]] = np.nanda = xr.DataArray(data, coords=[latitudes, longitudes], dims=["y", "x"])# 设置 TIFF 文件属性值tif_attrs["NODATA_VALUE"] = attrs["nodata_value"]da.attrs = tif_attrs# 设置 TIFF 文件参考系信息rioxarray.raster_array.RasterArray(da)da.rio.write_crs("epsg:4326", inplace=True)da.rio.to_raster(tif_path)def tiff_to_ascii(tif_path: str, asc_path: str) -> None:"""TIFF 文件转 ASCII 文件:param tif_path: TIFF 文件路径, 例如: ./test.tif:type tif_path: str:param asc_path: ASCII 输出文件路径, 例如: ./test.asc:type asc_path: str"""# 读取 TIFF 文件tif = rioxarray.open_rasterio(tif_path)shape = tif.rio.shapetransform = tif.rio.transform()# 获取 ASCII 文件前 6 行属性attrs: dict = {}attrs["ncols"] = shape[1]attrs["nrows"] = shape[0]attrs["xllcorner"] = transform[2]attrs["yllcorner"] = transform[5] + shape[0] * transform[4]attrs["cellsize"] = transform[0]attrs["nodata_value"] = tif.rio.nodata if tif.rio.nodata else -9999# 获取数据data = tif.values[0]data[np.isnan(data)] = attrs["nodata_value"]# 写入文件with open(asc_path, "w") as file:for key, value in attrs.items():file.write(f"{key.upper():14}{value}\n")np.savetxt(fname=file, X=data, fmt="%.2f")if __name__ == "__main__":ascii_to_tiff("./ascs/dem.asc", "./tifs/dem.tif", {"UNIT": "m"})tiff_to_ascii("./tifs/dem.tif", "./ascs/dem2.asc")
注意:ASCII 文件与 TIFF 文件除了存在格式差异,还存在元空间表达方式的差异。ASCII 文件坐标值在像元的左下角,而 TIFF 文件坐标值在像元的左上角,因此在格式转换时需要注意坐标转换问题。
参考资料: