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

81 results

Time (local)	Label
2021-11-16 10:19:31	ga_ls9c_ard_3-2-1_100071_2021-11-16_final.stac-item
2021-12-06 09:14:54	ga_ls9c_ard_3-2-1_089085_2021-12-05_final.stac-item
2021-12-23 11:36:09	ga_ls9c_ard_3-2-1_112083_2021-12-23_final.stac-item
2021-12-28 11:53:05	ga_ls9c_ard_3-2-1_115079_2021-12-28_final.stac-item
2022-01-03 09:34:43	ga_ls9c_ard_3-2-1_093073_2022-01-03_final.stac-item
2022-01-03 09:40:42	ga_ls9c_ard_3-2-1_093088_2022-01-03_final.stac-item
2022-01-07 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-07_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-01-28 09:32:08	ga_ls9c_ard_3-2-1_092082_2022-01-28_final.stac-item
2022-02-13 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-02-12_final.stac-item
2022-02-18 09:46:10	ga_ls9c_ard_3-2-1_095071_2022-02-18_final.stac-item
2022-02-22 09:28:12	ga_ls9c_ard_3-2-1_091088_2022-02-21_final.stac-item
2022-03-01 09:29:05	ga_ls9c_ard_3-2-1_092075_2022-02-28_final.stac-item
2022-03-31 11:18:15	ga_ls9c_ard_3-2-1_110070_2022-03-31_final.stac-item
2022-04-23 11:25:26	ga_ls9c_ard_3-2-1_111073_2022-04-23_final.stac-item
2022-04-27 11:02:43	ga_ls9c_ard_3-2-1_107078_2022-04-27_final.stac-item
2022-05-23 09:56:17	ga_ls9c_ard_3-2-1_097067_2022-05-23_final.stac-item
2022-05-30 11:46:56	ga_ls9c_ard_3-2-1_114081_2022-05-30_final.stac-item
2022-06-10 11:29:13	ga_ls9c_ard_3-2-1_111083_2022-06-10_final.stac-item
2022-06-24 09:56:38	ga_ls9c_ard_3-2-1_097067_2022-06-24_final.stac-item
2022-06-30 09:23:09	ga_ls9c_ard_3-2-1_091076_2022-06-29_final.stac-item
2022-08-01 09:26:08	ga_ls9c_ard_3-2-1_091083_2022-07-31_final.stac-item
2022-08-13 09:46:11	ga_ls9c_ard_3-2-1_095071_2022-08-13_final.stac-item
2022-09-04 09:16:20	ga_ls9c_ard_3-2-1_089089_2022-09-03_final.stac-item
2022-09-05 09:58:24	ga_ls9c_ard_3-2-1_096086_2022-09-05_final.stac-item
2022-09-21 11:36:35	ga_ls9c_ard_3-2-1_112084_2022-09-21_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-09-23 11:18:39	ga_ls9c_ard_3-2-1_110070_2022-09-23_final.stac-item
2022-10-09 11:24:16	ga_ls9c_ard_3-2-1_110084_2022-10-09_final.stac-item
2022-10-28 10:09:11	ga_ls9c_ard_3-2-1_099066_2022-10-28_final.stac-item
2022-10-28 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-10-28_final.stac-item
2022-11-05 09:22:54	ga_ls9c_ard_3-2-1_091074_2022-11-04_final.stac-item
2022-11-07 10:50:14	ga_ls9c_ard_3-2-1_105076_2022-11-07_final.stac-item
2022-11-21 09:28:08	ga_ls9c_ard_3-2-1_091087_2022-11-20_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-12-01 09:58:22	ga_ls9c_ard_3-2-1_097070_2022-12-01_final.stac-item
2023-01-11 11:36:17	ga_ls9c_ard_3-2-1_112083_2023-01-11_final.stac-item
2023-01-23 08:42:45	ga_ls9c_ard_3-2-1_084082_2023-01-22_final.stac-item
2023-03-05 10:08:57	ga_ls9c_ard_3-2-1_099066_2023-03-05_final.stac-item
2023-03-15 10:49:57	ga_ls9c_ard_3-2-1_105076_2023-03-15_final.stac-item
2023-05-01 10:09:27	ga_ls9c_ard_3-2-1_098084_2023-05-01_final.stac-item
2023-05-13 10:27:42	ga_ls9c_ard_3-2-1_102068_2023-05-13_final.stac-item
2023-05-28 11:23:34	ga_ls9c_ard_3-2-1_111069_2023-05-28_final.stac-item
2023-06-03 10:48:52	ga_ls9c_ard_3-2-1_105075_2023-06-03_final.stac-item
2023-06-04 11:30:55	ga_ls9c_ard_3-2-1_112072_2023-06-04_final.stac-item
2023-06-10 10:57:22	ga_ls9c_ard_3-2-1_106081_2023-06-10_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-06-14 10:32:36	ga_ls9c_ard_3-2-1_102081_2023-06-14_final.stac-item
2023-06-25 10:12:50	ga_ls9c_ard_3-2-1_099078_2023-06-25_final.stac-item
2023-07-03 09:28:22	ga_ls9c_ard_3-2-1_091090_2023-07-02_final.stac-item
2023-07-29 11:41:18	ga_ls9c_ard_3-2-1_113082_2023-07-29_final.stac-item
2023-07-30 10:42:06	ga_ls9c_ard_3-2-1_104073_2023-07-30_final.stac-item
2023-08-18 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-08-18_final.stac-item
2023-08-20 11:01:58	ga_ls9c_ard_3-2-1_107076_2023-08-20_final.stac-item
2023-09-07 10:49:25	ga_ls9c_ard_3-2-1_105075_2023-09-07_final.stac-item
2023-09-13 10:13:35	ga_ls9c_ard_3-2-1_099078_2023-09-13_final.stac-item
2023-09-23 09:15:46	ga_ls9c_ard_3-2-1_089088_2023-09-22_final.stac-item
2023-09-26 11:24:19	ga_ls9c_ard_3-2-1_110085_2023-09-26_final.stac-item
2023-11-05 10:33:24	ga_ls9c_ard_3-2-1_102081_2023-11-05_final.stac-item
2023-11-08 11:01:32	ga_ls9c_ard_3-2-1_107074_2023-11-08_final.stac-item
2023-11-17 10:55:46	ga_ls9c_ard_3-2-1_106075_2023-11-17_final.stac-item
2023-11-25 11:47:43	ga_ls9c_ard_3-2-1_114081_2023-11-25_final.stac-item
2023-12-05 10:42:41	ga_ls9c_ard_3-2-1_104073_2023-12-05_final.stac-item
2023-12-15 11:18:37	ga_ls9c_ard_3-2-1_110070_2023-12-15_final.stac-item
2023-12-16 10:23:00	ga_ls9c_ard_3-2-1_101070_2023-12-16_final.stac-item
2023-12-28 09:16:26	ga_ls9c_ard_3-2-1_089089_2023-12-27_final.stac-item
2024-01-04 10:55:50	ga_ls9c_ard_3-2-1_106075_2024-01-04_final.stac-item
2024-01-04 10:56:38	ga_ls9c_ard_3-2-1_106077_2024-01-04_final.stac-item
2024-01-11 11:02:26	ga_ls9c_ard_3-2-1_107076_2024-01-11_final.stac-item
2024-01-29 10:52:04	ga_ls9c_ard_3-2-1_105081_2024-01-29_final.stac-item
2024-02-05 10:53:54	ga_ls9c_ard_3-2-1_106070_2024-02-05_final.stac-item
2024-02-09 10:28:47	ga_ls9c_ard_3-2-1_102069_2024-02-09_final.stac-item
2024-03-13 09:40:35	ga_ls9c_ard_3-2-1_093088_2024-03-13_final.stac-item
2024-03-17 10:49:57	ga_ls9c_ard_3-2-1_105076_2024-03-17_final.stac-item
2024-03-24 09:22:00	ga_ls9c_ard_3-2-1_090088_2024-03-23_final.stac-item
2024-03-25 09:56:52	ga_ls9c_ard_3-2-1_097067_2024-03-25_final.stac-item
2024-03-25 09:58:27	ga_ls9c_ard_3-2-1_097071_2024-03-25_final.stac-item
2024-03-31 09:21:42	ga_ls9c_ard_3-2-1_091072_2024-03-30_final.stac-item
2024-04-26 10:01:11	ga_ls9c_ard_3-2-1_097079_2024-04-26_final.stac-item
2024-05-19 11:46:53	ga_ls9c_ard_3-2-1_114081_2024-05-19_nrt.stac-item
2024-05-20 10:51:40	ga_ls9c_ard_3-2-1_105082_2024-05-20_nrt.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