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 09:38:13	ga_ls9c_ard_3-2-1_093080_2021-11-05_final.stac-item
2021-11-05 11:18:04	ga_ls9c_ard_3-2-1_109083_2021-11-05_final.stac-item
2021-12-12 10:15:26	ga_ls9c_ard_3-2-1_099082_2021-12-12_final.stac-item
2021-12-15 10:43:31	ga_ls9c_ard_3-2-1_104075_2021-12-15_final.stac-item
2021-12-24 10:39:20	ga_ls9c_ard_3-2-1_103080_2021-12-24_final.stac-item
2021-12-25 09:44:06	ga_ls9c_ard_3-2-1_094081_2021-12-25_final.stac-item
2021-12-27 11:11:50	ga_ls9c_ard_3-2-1_108084_2021-12-27_final.stac-item
2022-01-03 09:39:55	ga_ls9c_ard_3-2-1_093086_2022-01-03_final.stac-item
2022-02-02 09:51:52	ga_ls9c_ard_3-2-1_095085_2022-02-02_final.stac-item
2022-02-08 10:52:03	ga_ls9c_ard_3-2-1_105081_2022-02-08_final.stac-item
2022-02-15 10:57:23	ga_ls9c_ard_3-2-1_106079_2022-02-15_final.stac-item
2022-02-25 11:35:33	ga_ls9c_ard_3-2-1_112082_2022-02-25_final.stac-item
2022-03-24 09:36:24	ga_ls9c_ard_3-2-1_093078_2022-03-24_final.stac-item
2022-03-25 10:21:15	ga_ls9c_ard_3-2-1_100082_2022-03-25_final.stac-item
2022-03-26 09:26:49	ga_ls9c_ard_3-2-1_091085_2022-03-25_final.stac-item
2022-03-31 09:44:10	ga_ls9c_ard_3-2-1_094082_2022-03-31_final.stac-item
2022-04-20 09:19:40	ga_ls9c_ard_3-2-1_090083_2022-04-19_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-05-03 10:24:01	ga_ls9c_ard_3-2-1_101074_2022-05-03_final.stac-item
2022-05-12 10:20:08	ga_ls9c_ard_3-2-1_100080_2022-05-12_final.stac-item
2022-05-31 10:47:20	ga_ls9c_ard_3-2-1_105071_2022-05-31_final.stac-item
2022-06-07 09:18:14	ga_ls9c_ard_3-2-1_090080_2022-06-06_final.stac-item
2022-06-07 10:58:19	ga_ls9c_ard_3-2-1_106083_2022-06-07_final.stac-item
2022-06-09 10:42:45	ga_ls9c_ard_3-2-1_104075_2022-06-09_final.stac-item
2022-06-13 11:57:47	ga_ls9c_ard_3-2-1_116077_2022-06-13_final.stac-item
2022-06-14 11:02:10	ga_ls9c_ard_3-2-1_107077_2022-06-14_final.stac-item
2022-06-23 10:57:49	ga_ls9c_ard_3-2-1_106081_2022-06-23_final.stac-item
2022-07-06 10:23:44	ga_ls9c_ard_3-2-1_101073_2022-07-06_final.stac-item
2022-07-15 10:20:18	ga_ls9c_ard_3-2-1_100080_2022-07-15_final.stac-item
2022-07-16 11:02:23	ga_ls9c_ard_3-2-1_107077_2022-07-16_final.stac-item
2022-07-17 11:44:52	ga_ls9c_ard_3-2-1_114075_2022-07-17_final.stac-item
2022-08-01 09:26:56	ga_ls9c_ard_3-2-1_091085_2022-07-31_final.stac-item
2022-08-11 09:59:20	ga_ls9c_ard_3-2-1_097073_2022-08-11_final.stac-item
2022-08-15 09:35:50	ga_ls9c_ard_3-2-1_093076_2022-08-15_final.stac-item
2022-08-19 09:13:08	ga_ls9c_ard_3-2-1_089081_2022-08-18_final.stac-item
2022-08-27 11:41:28	ga_ls9c_ard_3-2-1_113081_2022-08-27_final.stac-item
2022-09-26 10:11:53	ga_ls9c_ard_3-2-1_099073_2022-09-26_final.stac-item
2022-10-08 10:38:12	ga_ls9c_ard_3-2-1_103077_2022-10-08_final.stac-item
2022-10-21 11:45:29	ga_ls9c_ard_3-2-1_114075_2022-10-21_final.stac-item
2022-11-22 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-11-22_final.stac-item
2022-11-24 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-24_final.stac-item
2023-01-15 09:31:26	ga_ls9c_ard_3-2-1_092080_2023-01-15_final.stac-item
2023-01-31 11:10:48	ga_ls9c_ard_3-2-1_108081_2023-01-31_final.stac-item
2023-02-02 10:56:27	ga_ls9c_ard_3-2-1_106076_2023-02-02_final.stac-item
2023-02-04 10:44:31	ga_ls9c_ard_3-2-1_104077_2023-02-04_final.stac-item
2023-02-06 10:30:58	ga_ls9c_ard_3-2-1_102074_2023-02-06_final.stac-item
2023-02-07 09:38:33	ga_ls9c_ard_3-2-1_093082_2023-02-07_final.stac-item
2023-02-12 11:35:33	ga_ls9c_ard_3-2-1_112081_2023-02-12_final.stac-item
2023-02-16 11:09:59	ga_ls9c_ard_3-2-1_108079_2023-02-16_final.stac-item
2023-02-18 09:18:42	ga_ls9c_ard_3-2-1_090079_2023-02-17_final.stac-item
2023-02-19 10:01:09	ga_ls9c_ard_3-2-1_097077_2023-02-19_final.stac-item
2023-02-20 10:45:35	ga_ls9c_ard_3-2-1_104080_2023-02-20_final.stac-item
2023-03-18 09:45:33	ga_ls9c_ard_3-2-1_094085_2023-03-18_final.stac-item
2023-03-24 10:42:06	ga_ls9c_ard_3-2-1_104072_2023-03-24_final.stac-item
2023-04-13 10:17:34	ga_ls9c_ard_3-2-1_100073_2023-04-13_final.stac-item
2023-04-13 11:57:39	ga_ls9c_ard_3-2-1_116076_2023-04-13_final.stac-item
2023-04-15 10:05:59	ga_ls9c_ard_3-2-1_098075_2023-04-15_final.stac-item
2023-04-15 11:45:40	ga_ls9c_ard_3-2-1_114077_2023-04-15_final.stac-item
2023-04-15 11:46:04	ga_ls9c_ard_3-2-1_114078_2023-04-15_final.stac-item
2023-04-15 11:46:28	ga_ls9c_ard_3-2-1_114079_2023-04-15_final.stac-item
2023-04-18 10:34:30	ga_ls9c_ard_3-2-1_103069_2023-04-18_final.stac-item
2023-04-18 10:38:53	ga_ls9c_ard_3-2-1_103080_2023-04-18_final.stac-item
2023-04-19 09:43:16	ga_ls9c_ard_3-2-1_094080_2023-04-19_final.stac-item
2023-04-23 09:20:32	ga_ls9c_ard_3-2-1_090085_2023-04-22_final.stac-item
2023-04-24 10:03:47	ga_ls9c_ard_3-2-1_097085_2023-04-24_final.stac-item
2023-04-25 10:41:03	ga_ls9c_ard_3-2-1_104070_2023-04-25_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-05-01 11:47:08	ga_ls9c_ard_3-2-1_114081_2023-05-01_final.stac-item
2023-05-02 10:47:54	ga_ls9c_ard_3-2-1_105072_2023-05-02_final.stac-item
2023-05-07 09:31:06	ga_ls9c_ard_3-2-1_092081_2023-05-07_final.stac-item
2023-05-09 10:54:02	ga_ls9c_ard_3-2-1_106072_2023-05-09_final.stac-item
2023-05-12 09:51:14	ga_ls9c_ard_3-2-1_095085_2023-05-12_final.stac-item
2023-05-12 11:29:43	ga_ls9c_ard_3-2-1_111084_2023-05-12_final.stac-item
2023-05-15 10:20:55	ga_ls9c_ard_3-2-1_100082_2023-05-15_final.stac-item
2023-05-16 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-05-16_final.stac-item
2023-05-17 11:44:13	ga_ls9c_ard_3-2-1_114074_2023-05-17_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-06-03 10:46:52	ga_ls9c_ard_3-2-1_105070_2023-06-03_final.stac-item
2023-06-29 09:46:37	ga_ls9c_ard_3-2-1_095074_2023-06-29_final.stac-item
2023-07-03 11:00:04	ga_ls9c_ard_3-2-1_107072_2023-07-03_final.stac-item
2023-07-03 11:00:28	ga_ls9c_ard_3-2-1_107073_2023-07-03_final.stac-item
2023-07-04 10:09:39	ga_ls9c_ard_3-2-1_098085_2023-07-04_final.stac-item
2023-07-09 10:25:03	ga_ls9c_ard_3-2-1_101077_2023-07-09_final.stac-item
2023-09-05 11:00:33	ga_ls9c_ard_3-2-1_107072_2023-09-05_final.stac-item
2023-09-07 09:14:55	ga_ls9c_ard_3-2-1_089086_2023-09-06_final.stac-item
2023-09-07 10:51:25	ga_ls9c_ard_3-2-1_105080_2023-09-07_final.stac-item
2023-09-11 10:23:32	ga_ls9c_ard_3-2-1_101072_2023-09-11_final.stac-item
2023-09-14 09:19:34	ga_ls9c_ard_3-2-1_090082_2023-09-13_final.stac-item
2023-09-18 10:30:33	ga_ls9c_ard_3-2-1_102074_2023-09-18_final.stac-item
2023-09-19 11:13:00	ga_ls9c_ard_3-2-1_109072_2023-09-19_final.stac-item
2023-09-19 11:17:24	ga_ls9c_ard_3-2-1_109083_2023-09-19_final.stac-item
2023-09-23 09:14:58	ga_ls9c_ard_3-2-1_089086_2023-09-22_final.stac-item
2023-09-24 11:35:06	ga_ls9c_ard_3-2-1_112081_2023-09-24_final.stac-item
2023-09-25 10:34:41	ga_ls9c_ard_3-2-1_103069_2023-09-25_final.stac-item
2023-09-25 10:35:29	ga_ls9c_ard_3-2-1_103071_2023-09-25_final.stac-item
2023-09-30 10:56:49	ga_ls9c_ard_3-2-1_106078_2023-09-30_final.stac-item
2023-10-07 11:04:17	ga_ls9c_ard_3-2-1_107081_2023-10-07_final.stac-item
2023-10-08 10:06:16	ga_ls9c_ard_3-2-1_098075_2023-10-08_final.stac-item
2023-10-10 09:53:32	ga_ls9c_ard_3-2-1_096074_2023-10-10_final.stac-item
2023-10-13 10:26:05	ga_ls9c_ard_3-2-1_101078_2023-10-13_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