python gdal 读取影像通过无效值，识别影像有效边界并生成shapefile文件

要通过无效值识别影像的有效边界并生成shapefile文件，你可以使用GDAL库和OGR库。以下是一个示例代码：

from osgeo import gdal, ogr
import numpy as np

# 打开影像文件
dataset = gdal.Open('path_to_your_image.tif')

# 获取第一个波段
band = dataset.GetRasterBand(1)

# 读取影像数据为NumPy数组
data = band.ReadAsArray()

# 获取无效值
no_data_value = band.GetNoDataValue()

# 创建掩码数组
mask = np.not_equal(data, no_data_value)

# 获取有效边界
rows = np.any(mask, axis=1)
cols = np.any(mask, axis=0)
min_row, max_row = np.where(rows)[0][[0, -1]]
min_col, max_col = np.where(cols)[0][[0, -1]]

# 计算有效边界的地理坐标
transform = dataset.GetGeoTransform()
ulx = transform[0] + min_col * transform[1] + min_row * transform[2]
uly = transform[3] + min_col * transform[4] + min_row * transform[5]
lrx = transform[0] + (max_col + 1) * transform[1] + (max_row + 1) * transform[2]
lry = transform[3] + (max_col + 1) * transform[4] + (max_row + 1) * transform[5]

# 创建shapefile文件
driver = ogr.GetDriverByName('ESRI Shapefile')
shapefile_path = 'path_to_output_shapefile.shp'
shapefile = driver.CreateDataSource(shapefile_path)
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