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

First 100 results (query limit)

Time (local)	Label
2021-11-05 09:40:12	ga_ls9c_ard_3-2-1_093085_2021-11-05_final.stac-item
2021-11-12 09:22:20	ga_ls9c_ard_3-2-1_091081_2021-11-11_final.stac-item
2021-11-22 11:03:08	ga_ls9c_ard_3-2-1_107074_2021-11-22_final.stac-item
2021-12-30 11:42:20	ga_ls9c_ard_3-2-1_113083_2021-12-30_final.stac-item
2022-01-06 10:08:00	ga_ls9c_ard_3-2-1_098079_2022-01-06_final.stac-item
2022-01-08 11:36:31	ga_ls9c_ard_3-2-1_112084_2022-01-08_final.stac-item
2022-01-21 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-01-20_final.stac-item
2022-02-11 09:46:27	ga_ls9c_ard_3-2-1_094087_2022-02-11_final.stac-item
2022-02-28 10:22:44	ga_ls9c_ard_3-2-1_101070_2022-02-28_final.stac-item
2022-03-02 10:09:56	ga_ls9c_ard_3-2-1_099069_2022-03-02_final.stac-item
2022-03-03 10:53:36	ga_ls9c_ard_3-2-1_106070_2022-03-03_final.stac-item
2022-03-08 09:34:52	ga_ls9c_ard_3-2-1_093074_2022-03-08_final.stac-item
2022-03-08 11:14:57	ga_ls9c_ard_3-2-1_109077_2022-03-08_final.stac-item
2022-03-10 11:04:59	ga_ls9c_ard_3-2-1_107083_2022-03-10_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-03-30 10:34:12	ga_ls9c_ard_3-2-1_103068_2022-03-30_final.stac-item
2022-03-31 09:40:34	ga_ls9c_ard_3-2-1_094073_2022-03-31_final.stac-item
2022-04-20 10:57:21	ga_ls9c_ard_3-2-1_106080_2022-04-20_final.stac-item
2022-05-15 09:12:30	ga_ls9c_ard_3-2-1_089081_2022-05-14_final.stac-item
2022-06-07 10:58:19	ga_ls9c_ard_3-2-1_106083_2022-06-07_final.stac-item
2022-06-08 10:03:05	ga_ls9c_ard_3-2-1_097084_2022-06-08_final.stac-item
2022-06-09 10:45:33	ga_ls9c_ard_3-2-1_104082_2022-06-09_final.stac-item
2022-06-13 10:19:17	ga_ls9c_ard_3-2-1_100078_2022-06-13_final.stac-item
2022-06-29 10:16:47	ga_ls9c_ard_3-2-1_100071_2022-06-29_final.stac-item
2022-07-19 11:31:44	ga_ls9c_ard_3-2-1_112073_2022-07-19_final.stac-item
2022-07-21 11:20:13	ga_ls9c_ard_3-2-1_110075_2022-07-21_final.stac-item
2022-07-28 11:28:06	ga_ls9c_ard_3-2-1_111079_2022-07-28_final.stac-item
2022-08-19 09:13:32	ga_ls9c_ard_3-2-1_089082_2022-08-18_final.stac-item
2022-08-29 11:24:20	ga_ls9c_ard_3-2-1_111069_2022-08-29_final.stac-item
2022-09-02 11:01:36	ga_ls9c_ard_3-2-1_107074_2022-09-02_final.stac-item
2022-09-07 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-09-07_final.stac-item
2022-09-09 09:30:29	ga_ls9c_ard_3-2-1_092078_2022-09-09_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-09-15 10:33:57	ga_ls9c_ard_3-2-1_102082_2022-09-15_final.stac-item
2022-09-23 11:18:39	ga_ls9c_ard_3-2-1_110070_2022-09-23_final.stac-item
2022-10-18 09:38:29	ga_ls9c_ard_3-2-1_093082_2022-10-18_final.stac-item
2022-11-09 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-09_final.stac-item
2022-11-23 10:51:04	ga_ls9c_ard_3-2-1_105078_2022-11-23_final.stac-item
2022-11-28 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-11-27_final.stac-item
2022-12-04 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-04_final.stac-item
2022-12-05 09:35:40	ga_ls9c_ard_3-2-1_093075_2022-12-05_final.stac-item
2022-12-19 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-12-19_final.stac-item
2022-12-20 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-20_final.stac-item
2022-12-23 09:22:52	ga_ls9c_ard_3-2-1_091074_2022-12-22_final.stac-item
2023-01-03 10:41:17	ga_ls9c_ard_3-2-1_104069_2023-01-03_final.stac-item
2023-01-08 09:27:19	ga_ls9c_ard_3-2-1_091085_2023-01-07_final.stac-item
2023-01-09 10:03:48	ga_ls9c_ard_3-2-1_098068_2023-01-09_final.stac-item
2023-01-10 10:52:14	ga_ls9c_ard_3-2-1_105081_2023-01-10_final.stac-item
2023-01-11 11:36:17	ga_ls9c_ard_3-2-1_112083_2023-01-11_final.stac-item
2023-01-18 11:39:11	ga_ls9c_ard_3-2-1_113075_2023-01-18_final.stac-item
2023-01-21 10:28:21	ga_ls9c_ard_3-2-1_102068_2023-01-21_final.stac-item
2023-01-29 11:18:44	ga_ls9c_ard_3-2-1_110070_2023-01-29_final.stac-item
2023-02-04 09:07:37	ga_ls9c_ard_3-2-1_088082_2023-02-03_final.stac-item
2023-02-05 09:50:54	ga_ls9c_ard_3-2-1_095082_2023-02-05_final.stac-item
2023-02-06 10:28:58	ga_ls9c_ard_3-2-1_102069_2023-02-06_final.stac-item
2023-02-19 09:59:09	ga_ls9c_ard_3-2-1_097072_2023-02-19_final.stac-item
2023-02-25 09:23:33	ga_ls9c_ard_3-2-1_091076_2023-02-24_final.stac-item
2023-03-03 10:26:07	ga_ls9c_ard_3-2-1_101078_2023-03-03_final.stac-item
2023-03-07 11:38:38	ga_ls9c_ard_3-2-1_113074_2023-03-07_final.stac-item
2023-03-17 10:34:24	ga_ls9c_ard_3-2-1_103068_2023-03-17_final.stac-item
2023-03-30 10:03:42	ga_ls9c_ard_3-2-1_098069_2023-03-30_final.stac-item
2023-04-09 10:42:21	ga_ls9c_ard_3-2-1_104073_2023-04-09_final.stac-item
2023-04-19 11:23:45	ga_ls9c_ard_3-2-1_110084_2023-04-19_final.stac-item
2023-05-01 11:47:08	ga_ls9c_ard_3-2-1_114081_2023-05-01_final.stac-item
2023-05-12 09:51:38	ga_ls9c_ard_3-2-1_095086_2023-05-12_final.stac-item
2023-05-18 10:48:35	ga_ls9c_ard_3-2-1_105074_2023-05-18_final.stac-item
2023-05-27 09:07:00	ga_ls9c_ard_3-2-1_088083_2023-05-26_final.stac-item
2023-05-29 10:27:33	ga_ls9c_ard_3-2-1_102068_2023-05-29_final.stac-item
2023-06-03 09:15:34	ga_ls9c_ard_3-2-1_089089_2023-06-02_final.stac-item
2023-06-04 11:35:43	ga_ls9c_ard_3-2-1_112084_2023-06-04_final.stac-item
2023-06-30 10:27:31	ga_ls9c_ard_3-2-1_102068_2023-06-30_final.stac-item
2023-07-01 09:39:06	ga_ls9c_ard_3-2-1_093086_2023-07-01_final.stac-item
2023-07-21 10:48:36	ga_ls9c_ard_3-2-1_105074_2023-07-21_final.stac-item
2023-08-21 10:04:46	ga_ls9c_ard_3-2-1_098072_2023-08-21_final.stac-item
2023-08-24 10:36:54	ga_ls9c_ard_3-2-1_103075_2023-08-24_final.stac-item
2023-09-03 11:16:04	ga_ls9c_ard_3-2-1_109080_2023-09-03_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_final.stac-item
2023-10-25 10:49:14	ga_ls9c_ard_3-2-1_105074_2023-10-25_final.stac-item
2023-10-30 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-10-29_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-11-16 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-11-16_final.stac-item
2023-11-21 10:28:43	ga_ls9c_ard_3-2-1_102069_2023-11-21_final.stac-item
2023-11-30 10:23:00	ga_ls9c_ard_3-2-1_101070_2023-11-30_final.stac-item
2023-12-01 09:29:22	ga_ls9c_ard_3-2-1_092075_2023-11-30_final.stac-item
2023-12-03 10:53:28	ga_ls9c_ard_3-2-1_106069_2023-12-03_final.stac-item
2023-12-03 10:55:52	ga_ls9c_ard_3-2-1_106075_2023-12-03_final.stac-item
2023-12-17 11:07:28	ga_ls9c_ard_3-2-1_108073_2023-12-17_final.stac-item
2023-12-22 11:24:50	ga_ls9c_ard_3-2-1_111070_2023-12-22_final.stac-item
2023-12-26 09:23:37	ga_ls9c_ard_3-2-1_091076_2023-12-25_final.stac-item
2023-12-26 09:26:49	ga_ls9c_ard_3-2-1_091084_2023-12-25_final.stac-item
2024-01-14 11:36:08	ga_ls9c_ard_3-2-1_112083_2024-01-14_final.stac-item
2024-01-23 11:25:06	ga_ls9c_ard_3-2-1_111071_2024-01-23_final.stac-item
2024-01-28 11:47:41	ga_ls9c_ard_3-2-1_114081_2024-01-28_final.stac-item
2024-02-05 10:55:30	ga_ls9c_ard_3-2-1_106074_2024-02-05_final.stac-item
2024-02-14 10:50:04	ga_ls9c_ard_3-2-1_105076_2024-02-14_final.stac-item
2024-02-27 08:42:32	ga_ls9c_ard_3-2-1_084082_2024-02-26_final.stac-item
2024-02-29 10:09:29	ga_ls9c_ard_3-2-1_098083_2024-02-29_final.stac-item
2024-03-16 10:07:30	ga_ls9c_ard_3-2-1_098078_2024-03-16_final.stac-item
2024-03-16 11:47:35	ga_ls9c_ard_3-2-1_114081_2024-03-16_final.stac-item
2024-03-20 11:24:27	ga_ls9c_ard_3-2-1_110085_2024-03-20_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years