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
2021-11-10 09:39:53	ga_ls9c_ard_3-2-1_094078_2021-11-10_final.stac-item
2021-11-10 09:43:28	ga_ls9c_ard_3-2-1_094087_2021-11-10_final.stac-item
2021-11-15 09:42:21	ga_ls9c_ard_3-2-1_094078_2021-11-15_final.stac-item
2021-11-20 09:44:49	ga_ls9c_ard_3-2-1_094078_2021-11-20_final.stac-item
2021-11-25 09:48:03	ga_ls9c_ard_3-2-1_095080_2021-11-25_final.stac-item
2021-12-06 09:16:30	ga_ls9c_ard_3-2-1_089089_2021-12-05_final.stac-item
2021-12-07 09:54:34	ga_ls9c_ard_3-2-1_096076_2021-12-07_final.stac-item
2021-12-23 09:54:28	ga_ls9c_ard_3-2-1_096076_2021-12-23_final.stac-item
2021-12-25 09:42:54	ga_ls9c_ard_3-2-1_094078_2021-12-25_final.stac-item
2021-12-30 10:00:15	ga_ls9c_ard_3-2-1_097075_2021-12-30_final.stac-item
2022-03-22 09:49:35	ga_ls9c_ard_3-2-1_095080_2022-03-22_final.stac-item
2022-03-24 09:37:36	ga_ls9c_ard_3-2-1_093081_2022-03-24_final.stac-item
2022-03-31 09:43:46	ga_ls9c_ard_3-2-1_094081_2022-03-31_final.stac-item
2022-06-10 09:48:44	ga_ls9c_ard_3-2-1_095079_2022-06-10_final.stac-item
2022-06-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-06-23_final.stac-item
2022-06-26 09:49:05	ga_ls9c_ard_3-2-1_095079_2022-06-26_final.stac-item
2022-07-23 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-07-23_final.stac-item
2022-08-04 09:55:05	ga_ls9c_ard_3-2-1_096078_2022-08-04_final.stac-item
2022-08-06 09:42:44	ga_ls9c_ard_3-2-1_094078_2022-08-06_final.stac-item
2022-09-30 09:49:33	ga_ls9c_ard_3-2-1_095079_2022-09-30_final.stac-item
2022-10-09 11:22:17	ga_ls9c_ard_3-2-1_110079_2022-10-09_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-13 10:58:24	ga_ls9c_ard_3-2-1_106081_2022-10-13_final.stac-item
2022-10-22 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-10-22_final.stac-item
2022-10-25 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-10-25_final.stac-item
2022-10-25 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-10-25_final.stac-item
2022-10-27 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-10-27_final.stac-item
2022-11-01 09:49:13	ga_ls9c_ard_3-2-1_095078_2022-11-01_final.stac-item
2022-11-05 11:02:58	ga_ls9c_ard_3-2-1_107077_2022-11-05_final.stac-item
2022-11-17 09:49:40	ga_ls9c_ard_3-2-1_095079_2022-11-17_final.stac-item
2022-11-25 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-11-25_final.stac-item
2022-12-14 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-14_final.stac-item
2022-12-21 09:38:27	ga_ls9c_ard_3-2-1_093082_2022-12-21_final.stac-item
2022-12-23 11:03:21	ga_ls9c_ard_3-2-1_107078_2022-12-23_final.stac-item
2022-12-30 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-30_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-24 11:03:19	ga_ls9c_ard_3-2-1_107078_2023-01-24_final.stac-item
2023-01-26 10:50:59	ga_ls9c_ard_3-2-1_105078_2023-01-26_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-04 10:46:07	ga_ls9c_ard_3-2-1_104081_2023-02-04_final.stac-item
2023-02-16 09:31:30	ga_ls9c_ard_3-2-1_092080_2023-02-16_final.stac-item
2023-03-09 11:27:49	ga_ls9c_ard_3-2-1_111078_2023-03-09_final.stac-item
2023-04-22 11:50:39	ga_ls9c_ard_3-2-1_115074_2023-04-22_final.stac-item
2023-04-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2023-04-23_final.stac-item
2023-04-24 09:59:47	ga_ls9c_ard_3-2-1_097075_2023-04-24_final.stac-item
2023-04-28 11:15:30	ga_ls9c_ard_3-2-1_109079_2023-04-28_final.stac-item
2023-04-30 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-04-29_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 10:51:06	ga_ls9c_ard_3-2-1_105080_2023-05-02_final.stac-item
2023-05-03 09:54:39	ga_ls9c_ard_3-2-1_096078_2023-05-03_final.stac-item
2023-05-03 09:55:03	ga_ls9c_ard_3-2-1_096079_2023-05-03_final.stac-item
2023-05-03 09:56:15	ga_ls9c_ard_3-2-1_096082_2023-05-03_final.stac-item
2023-05-05 09:42:16	ga_ls9c_ard_3-2-1_094078_2023-05-05_final.stac-item
2023-05-05 11:17:57	ga_ls9c_ard_3-2-1_110070_2023-05-05_final.stac-item
2023-05-05 11:20:45	ga_ls9c_ard_3-2-1_110077_2023-05-05_final.stac-item
2023-05-05 11:21:33	ga_ls9c_ard_3-2-1_110079_2023-05-05_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-10 09:59:37	ga_ls9c_ard_3-2-1_097075_2023-05-10_final.stac-item
2023-05-11 10:44:04	ga_ls9c_ard_3-2-1_104078_2023-05-11_final.stac-item
2023-05-12 09:49:38	ga_ls9c_ard_3-2-1_095081_2023-05-12_final.stac-item
2023-05-14 09:36:28	ga_ls9c_ard_3-2-1_093079_2023-05-14_final.stac-item
2023-06-20 09:53:54	ga_ls9c_ard_3-2-1_096077_2023-06-20_final.stac-item
2023-06-20 09:54:18	ga_ls9c_ard_3-2-1_096078_2023-06-20_final.stac-item
2023-06-20 09:54:42	ga_ls9c_ard_3-2-1_096079_2023-06-20_final.stac-item
2023-06-22 11:20:50	ga_ls9c_ard_3-2-1_110078_2023-06-22_final.stac-item
2023-06-22 11:21:14	ga_ls9c_ard_3-2-1_110079_2023-06-22_final.stac-item
2023-07-01 11:14:47	ga_ls9c_ard_3-2-1_109078_2023-07-01_final.stac-item
2023-07-01 11:15:11	ga_ls9c_ard_3-2-1_109079_2023-07-01_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-06 09:54:07	ga_ls9c_ard_3-2-1_096077_2023-07-06_final.stac-item
2023-07-17 11:14:56	ga_ls9c_ard_3-2-1_109078_2023-07-17_final.stac-item
2023-07-17 11:15:44	ga_ls9c_ard_3-2-1_109080_2023-07-17_final.stac-item
2023-07-18 11:57:47	ga_ls9c_ard_3-2-1_116077_2023-07-18_final.stac-item
2023-07-19 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-07-19_final.stac-item
2023-07-21 10:51:00	ga_ls9c_ard_3-2-1_105080_2023-07-21_final.stac-item
2023-07-22 09:54:10	ga_ls9c_ard_3-2-1_096077_2023-07-22_final.stac-item
2023-07-22 09:54:58	ga_ls9c_ard_3-2-1_096079_2023-07-22_final.stac-item
2023-07-26 11:09:08	ga_ls9c_ard_3-2-1_108079_2023-07-26_final.stac-item
2023-07-28 10:58:25	ga_ls9c_ard_3-2-1_106083_2023-07-28_final.stac-item
2023-07-29 09:59:37	ga_ls9c_ard_3-2-1_097075_2023-07-29_final.stac-item
2023-08-02 11:15:26	ga_ls9c_ard_3-2-1_109079_2023-08-02_final.stac-item
2023-08-06 10:51:09	ga_ls9c_ard_3-2-1_105080_2023-08-06_final.stac-item
2023-10-13 10:26:53	ga_ls9c_ard_3-2-1_101080_2023-10-13_final.stac-item
2023-10-15 10:15:21	ga_ls9c_ard_3-2-1_099082_2023-10-15_final.stac-item
2023-10-19 11:28:20	ga_ls9c_ard_3-2-1_111079_2023-10-19_final.stac-item
2023-10-21 09:37:53	ga_ls9c_ard_3-2-1_093081_2023-10-21_final.stac-item
2023-10-22 10:20:45	ga_ls9c_ard_3-2-1_100080_2023-10-22_final.stac-item
2023-10-22 10:21:09	ga_ls9c_ard_3-2-1_100081_2023-10-22_final.stac-item
2023-10-26 09:55:12	ga_ls9c_ard_3-2-1_096078_2023-10-26_final.stac-item
2023-10-26 09:55:36	ga_ls9c_ard_3-2-1_096079_2023-10-26_final.stac-item
2023-10-26 09:58:00	ga_ls9c_ard_3-2-1_096085_2023-10-26_final.stac-item
2023-11-03 10:45:44	ga_ls9c_ard_3-2-1_104081_2023-11-03_final.stac-item
2023-11-04 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-11-04_final.stac-item
2023-11-15 11:09:18	ga_ls9c_ard_3-2-1_108078_2023-11-15_final.stac-item
2023-11-19 10:45:50	ga_ls9c_ard_3-2-1_104081_2023-11-19_final.stac-item
2023-11-22 09:37:54	ga_ls9c_ard_3-2-1_093081_2023-11-22_final.stac-item
2023-11-24 11:03:15	ga_ls9c_ard_3-2-1_107078_2023-11-24_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