surface reflectance data and meta data only about landsatxplore HOT 1 OPEN

This might not be the most efficient method, but I am in a similar situation as I want to download the image with the least amount of cloud cover. Once I find all images with the API search that are in the path/row region of interested I am interested I use the metadata from the search to decide which one to select for download. I save the search to a list and then removed from the list based on my criteria and the metadata provided.

For example the metadata I get some a search is below. This is one scene's meta data. I then use the cloud_cover attribute in this list and sort then grab the smallest value. I recommend printing to the console all of the elements and looking for the attribute ID you want to use to pick your scenes. Hope this helps a bit.

{'cloud_cover': 19, 'entity_id': 'LC80290202020197LGN01', 'display_id': 'LC08_L1TP_029020_20200715_20210330_02_T1', 'ordering_id': 'None', 'landsat_product_id': 'LC08_L1TP_029020_20200715_20210330_02_T1', 'landsat_scene_id': 'LC80290202020197LGN01', 'acquisition_date': datetime.datetime(2020, 7, 15, 0, 0), 'collection_category': datetime.datetime(2023, 2, 1, 0, 0), 'collection_number': 2, 'wrs_path': 29, 'wrs_row': 20, 'nadir-off_nadir': 'NADIR', 'roll_angle': 0.0, 'date_product_generated': datetime.datetime(2021, 3, 30, 0, 0), 'land_cloud_cover': 40.74, 'scene_cloud_cover': 19.22, 'start_time': datetime.datetime(2020, 7, 15, 17, 7, 24, 634020), 'stop_time': datetime.datetime(2020, 7, 15, 17, 7, 56, 404020), 'station_id': 'LGN', 'day-night_indicator': 'DAY', 'ground_control_points_model': 347, 'ground_control_points_version': 5, 'geometric_rmse_model': 7.325, 'geometric_rmse_model_x': 5.505, 'geometric_rmse_model_y': 4.833, 'image_quality': 9, 'processing_software_version': 'LPGS_15.4.0', 'sun_elevation_l0ra': 52.30272974, 'sun_azimuth_l0ra': 155.9665622, 'tirs_ssm_model': 'FINAL', 'data_type': 'OLI_TIRS_L1TP', 'sensor_id': 'OLI_TIRS', 'satellite': 8, 'panchromatic_lines': 16021, 'panchromatic_samples': 15841, 'reflective_lines': 8011, 'reflective_samples': 7921, 'thermal_lines': 8011, 'thermal_samples': 7921, 'product_map_projection': 'UTM', 'utm_zone': 15, 'datum': 'WGS84', 'ellipsoid': 'WGS84', 'grid_cell_size_panchromatic': 15.0, 'grid_cell_size_reflective': 30.0, 'grid_cell_size_thermal': 30.0, 'bias_parameter_file_name_oli': 'LO8BPF20200715151302_20200715171921.01', 'bias_parameter_file_name_tirs': 'LT8BPF20200705192819_20200719110031.01', 'calibration_parameter_file': 'LC08CPF_20200701_20200930_02.04', 'rlut_file_name': 'LC08RLUT_20150303_20431231_02_01.h5', 'scene_center_latitude': 57.30975, 'scene_center_longitude': -90.91495, 'corner_upper_left_latitude': 58.40134, 'corner_upper_left_longitude': -92.88536, 'corner_upper_right_latitude': 58.33333, 'corner_upper_right_longitude': -88.82648, 'corner_lower_left_latitude': 56.24272, 'corner_lower_left_longitude': -92.89189, 'corner_lower_right_latitude': 56.18009, 'corner_lower_right_longitude': -89.06342, 'has_customized_metadata': None, 'options': {'bulk': True, 'download': True, 'order': False, 'secondary': False}, 'selected': {'bulk': False, 'compare': False, 'order': False}, 'spatial_bounds': (-92.89023, 56.20468, -88.87987, 58.39652), 'spatial_coverage': <shapely.geometry.polygon.Polygon object at 0x0000019E49A00C10>, 'temporal_coverage': [datetime.datetime(2020, 7, 15, 0, 0), datetime.datetime(2020, 7, 15, 0, 0)], 'publish_date': datetime.datetime(2022, 6, 22, 18, 27, 47, tzinfo=tzoffset(None, -18000))}

from landsatxplore.