Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

71 results

Time (local)	Label
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-16 09:47:05	ga_ls9c_ard_3-2-1_095073_2021-12-16_final.stac-item
2022-01-13 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-01-13_final.stac-item
2022-01-14 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-01-14_final.stac-item
2022-01-23 09:16:47	ga_ls9c_ard_3-2-1_089090_2022-01-22_final.stac-item
2022-02-05 10:19:10	ga_ls9c_ard_3-2-1_100076_2022-02-05_final.stac-item
2022-02-21 10:19:02	ga_ls9c_ard_3-2-1_100076_2022-02-21_final.stac-item
2022-02-22 09:28:12	ga_ls9c_ard_3-2-1_091088_2022-02-21_final.stac-item
2022-02-23 11:47:08	ga_ls9c_ard_3-2-1_114080_2022-02-23_final.stac-item
2022-03-05 10:40:27	ga_ls9c_ard_3-2-1_104068_2022-03-05_final.stac-item
2022-03-24 11:12:30	ga_ls9c_ard_3-2-1_109071_2022-03-24_final.stac-item
2022-03-26 10:59:43	ga_ls9c_ard_3-2-1_107070_2022-03-26_final.stac-item
2022-04-02 09:32:36	ga_ls9c_ard_3-2-1_092084_2022-04-02_final.stac-item
2022-04-04 10:53:08	ga_ls9c_ard_3-2-1_106069_2022-04-04_final.stac-item
2022-04-13 09:09:59	ga_ls9c_ard_3-2-1_089074_2022-04-12_final.stac-item
2022-04-13 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-04-13_final.stac-item
2022-05-20 09:32:33	ga_ls9c_ard_3-2-1_092085_2022-05-20_final.stac-item
2022-06-19 11:19:12	ga_ls9c_ard_3-2-1_110073_2022-06-19_final.stac-item
2022-07-05 09:46:04	ga_ls9c_ard_3-2-1_094087_2022-07-05_final.stac-item
2022-07-05 11:19:22	ga_ls9c_ard_3-2-1_110073_2022-07-05_final.stac-item
2022-07-27 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-07-27_final.stac-item
2022-07-31 10:21:45	ga_ls9c_ard_3-2-1_100083_2022-07-31_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-09-29 10:46:23	ga_ls9c_ard_3-2-1_104082_2022-09-29_final.stac-item
2022-09-30 11:26:27	ga_ls9c_ard_3-2-1_111074_2022-09-30_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-25 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-25_final.stac-item
2022-12-05 09:34:52	ga_ls9c_ard_3-2-1_093073_2022-12-05_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2022-12-29 10:23:55	ga_ls9c_ard_3-2-1_101072_2022-12-29_final.stac-item
2022-12-29 10:24:43	ga_ls9c_ard_3-2-1_101074_2022-12-29_final.stac-item
2023-01-01 09:18:45	ga_ls9c_ard_3-2-1_090079_2022-12-31_final.stac-item
2023-01-19 09:06:39	ga_ls9c_ard_3-2-1_088080_2023-01-18_final.stac-item
2023-01-20 11:25:10	ga_ls9c_ard_3-2-1_111071_2023-01-20_final.stac-item
2023-01-22 11:16:50	ga_ls9c_ard_3-2-1_109081_2023-01-22_final.stac-item
2023-03-03 10:28:07	ga_ls9c_ard_3-2-1_101083_2023-03-03_final.stac-item
2023-03-16 11:31:37	ga_ls9c_ard_3-2-1_112072_2023-03-16_final.stac-item
2023-03-20 11:09:40	ga_ls9c_ard_3-2-1_108079_2023-03-20_final.stac-item
2023-03-21 11:51:43	ga_ls9c_ard_3-2-1_115076_2023-03-21_final.stac-item
2023-05-07 09:29:07	ga_ls9c_ard_3-2-1_092076_2023-05-06_final.stac-item
2023-06-01 09:24:45	ga_ls9c_ard_3-2-1_091081_2023-05-31_final.stac-item
2023-06-06 11:20:09	ga_ls9c_ard_3-2-1_110076_2023-06-06_final.stac-item
2023-06-11 09:56:09	ga_ls9c_ard_3-2-1_097067_2023-06-11_final.stac-item
2023-07-10 09:28:14	ga_ls9c_ard_3-2-1_092074_2023-07-09_final.stac-item
2023-07-13 09:59:09	ga_ls9c_ard_3-2-1_097074_2023-07-13_final.stac-item
2023-08-22 09:13:57	ga_ls9c_ard_3-2-1_089084_2023-08-21_final.stac-item
2023-08-29 10:55:54	ga_ls9c_ard_3-2-1_106076_2023-08-29_final.stac-item
2023-09-05 09:22:52	ga_ls9c_ard_3-2-1_091075_2023-09-04_final.stac-item
2023-09-05 09:23:40	ga_ls9c_ard_3-2-1_091077_2023-09-04_final.stac-item
2023-09-17 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-09-17_final.stac-item
2023-10-02 09:06:24	ga_ls9c_ard_3-2-1_088080_2023-10-01_final.stac-item
2023-10-04 10:28:10	ga_ls9c_ard_3-2-1_102068_2023-10-04_final.stac-item
2023-10-25 09:11:33	ga_ls9c_ard_3-2-1_089077_2023-10-24_final.stac-item
2023-10-29 10:28:04	ga_ls9c_ard_3-2-1_101083_2023-10-29_final.stac-item
2023-10-30 11:08:31	ga_ls9c_ard_3-2-1_108076_2023-10-30_final.stac-item
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final.stac-item
2023-12-01 09:28:10	ga_ls9c_ard_3-2-1_092072_2023-11-30_final.stac-item
2023-12-25 10:22:26	ga_ls9c_ard_3-2-1_100084_2023-12-25_final.stac-item
2023-12-26 11:01:42	ga_ls9c_ard_3-2-1_107074_2023-12-26_final.stac-item
2024-01-08 10:29:31	ga_ls9c_ard_3-2-1_102071_2024-01-08_final.stac-item
2024-01-20 10:56:14	ga_ls9c_ard_3-2-1_106076_2024-01-20_final.stac-item
2024-01-23 09:52:36	ga_ls9c_ard_3-2-1_095087_2024-01-23_final.stac-item
2024-02-05 09:23:00	ga_ls9c_ard_3-2-1_090090_2024-02-04_final.stac-item
2024-02-12 09:21:58	ga_ls9c_ard_3-2-1_091072_2024-02-11_final.stac-item
2024-02-22 11:38:32	ga_ls9c_ard_3-2-1_113074_2024-02-22_final.stac-item
2024-03-04 11:24:04	ga_ls9c_ard_3-2-1_110084_2024-03-04_final.stac-item
2024-03-26 09:07:12	ga_ls9c_ard_3-2-1_088082_2024-03-25_final.stac-item
2024-04-08 11:53:11	ga_ls9c_ard_3-2-1_115080_2024-04-08_final.stac-item
2024-04-10 10:01:31	ga_ls9c_ard_3-2-1_097079_2024-04-10_final.stac-item
2024-04-12 11:30:01	ga_ls9c_ard_3-2-1_111084_2024-04-12_final.stac-item
2024-05-14 11:28:25	ga_ls9c_ard_3-2-1_111081_2024-05-14_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years