def resampling_by_scale(input_path, target_file, refer_img_path):
    """
    按照缩放比例对影像重采样
    :param input_path: GDAL地理数据路径
    :param target_file: 输出影像
    :param refer_img_path:参考影像
    :return: True or False
    """
    ref_dataset = gdal.Open(refer_img_path)
    ref_cols = ref_dataset.RasterXSize  # 列数
    ref_rows = ref_dataset.RasterYSize  # 行数

    dataset = gdal.Open(input_path)
    if dataset is None:
        logger.error('resampling_by_scale:dataset is None!')
        return False

    band_count = dataset.RasterCount  # 波段数
    if (band_count == 0) or (target_file == ""):
        logger.error("resampling_by_scale:Parameters of the abnormal!")
        return False

    cols = dataset.RasterXSize  # 列数
    scale = ref_cols/cols

    # rows = dataset.RasterYSize  # 行数
    # cols = int(cols * scale)  # 计算新的行列数
    # rows = int(rows * scale)
    cols = ref_cols
    rows = ref_rows

    geotrans = list(dataset.GetGeoTransform())
    geotrans[1] = geotrans[1] / scale  # 像元宽度变为原来的scale倍
    geotrans[5] = geotrans[5] / scale  # 像元高度变为原来的scale倍

    if os.path.exists(target_file) and os.path.isfile(target_file):  # 如果已存在同名影像
        os.remove(target_file)  # 则删除之
    if not os.path.exists(os.path.split(target_file)[0]):
        os.makedirs(os.path.split(target_file)[0])

    band1 = dataset.GetRasterBand(1)
    data_type = band1.DataType
    target = dataset.GetDriver().Create(target_file, xsize=cols, ysize=rows, bands=band_count,
                                        eType=data_type)
    target.SetProjection(dataset.GetProjection())  # 设置投影坐标
    target.SetGeoTransform(geotrans)  # 设置地理变换参数
    total = band_count + 1
    for index in range(1, total):
        # 读取波段数据
        data = dataset.GetRasterBand(index).ReadAsArray(buf_xsize=cols, buf_ysize=rows)
        out_band = target.GetRasterBand(index)

        no_data_value = dataset.GetRasterBand(index).GetNoDataValue()  # 获取没有数据的点
        if not (no_data_value is None):
            out_band.SetNoDataValue(no_data_value)

        out_band.WriteArray(data)  #