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
2021-11-20 11:23:52	ga_ls9c_ard_3-2-1_110079_2021-11-20_final.stac-item
2021-12-07 11:34:14	ga_ls9c_ard_3-2-1_112078_2021-12-07_final.stac-item
2021-12-09 11:22:15	ga_ls9c_ard_3-2-1_110079_2021-12-09_final.stac-item
2022-01-08 09:55:14	ga_ls9c_ard_3-2-1_096078_2022-01-08_final.stac-item
2022-01-10 11:22:09	ga_ls9c_ard_3-2-1_110079_2022-01-10_final.stac-item
2022-02-28 10:26:43	ga_ls9c_ard_3-2-1_101080_2022-02-28_final.stac-item
2022-03-07 10:31:17	ga_ls9c_ard_3-2-1_102076_2022-03-07_final.stac-item
2022-03-21 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-03-21_final.stac-item
2022-04-05 11:39:11	ga_ls9c_ard_3-2-1_113076_2022-04-05_final.stac-item
2022-04-06 10:44:21	ga_ls9c_ard_3-2-1_104078_2022-04-06_final.stac-item
2022-05-25 09:48:18	ga_ls9c_ard_3-2-1_095078_2022-05-25_final.stac-item
2022-06-09 10:43:33	ga_ls9c_ard_3-2-1_104077_2022-06-09_final.stac-item
2022-06-19 09:41:07	ga_ls9c_ard_3-2-1_094075_2022-06-19_final.stac-item
2022-08-10 09:18:51	ga_ls9c_ard_3-2-1_090080_2022-08-09_final.stac-item
2022-09-16 11:16:25	ga_ls9c_ard_3-2-1_109080_2022-09-16_final.stac-item
2022-09-21 11:34:12	ga_ls9c_ard_3-2-1_112078_2022-09-21_final.stac-item
2023-01-29 11:21:56	ga_ls9c_ard_3-2-1_110078_2023-01-29_final.stac-item
2023-01-29 11:22:20	ga_ls9c_ard_3-2-1_110079_2023-01-29_final.stac-item
2023-02-13 10:37:32	ga_ls9c_ard_3-2-1_103075_2023-02-13_final.stac-item
2023-02-14 11:22:23	ga_ls9c_ard_3-2-1_110079_2023-02-14_final.stac-item
2023-02-19 11:40:49	ga_ls9c_ard_3-2-1_113079_2023-02-19_final.stac-item
2023-02-21 09:49:56	ga_ls9c_ard_3-2-1_095080_2023-02-21_final.stac-item
2023-02-21 11:28:25	ga_ls9c_ard_3-2-1_111079_2023-02-21_final.stac-item
2023-02-25 11:04:01	ga_ls9c_ard_3-2-1_107080_2023-02-25_final.stac-item
2023-03-09 11:28:37	ga_ls9c_ard_3-2-1_111080_2023-03-09_final.stac-item
2023-03-10 10:31:23	ga_ls9c_ard_3-2-1_102076_2023-03-10_final.stac-item
2023-03-10 10:32:11	ga_ls9c_ard_3-2-1_102078_2023-03-10_final.stac-item
2023-03-20 11:10:04	ga_ls9c_ard_3-2-1_108080_2023-03-20_final.stac-item
2023-03-21 11:50:55	ga_ls9c_ard_3-2-1_115074_2023-03-21_final.stac-item
2023-03-22 10:56:29	ga_ls9c_ard_3-2-1_106077_2023-03-22_final.stac-item
2023-03-23 10:00:51	ga_ls9c_ard_3-2-1_097077_2023-03-23_final.stac-item
2023-03-23 11:40:32	ga_ls9c_ard_3-2-1_113079_2023-03-23_final.stac-item
2023-03-24 10:44:30	ga_ls9c_ard_3-2-1_104078_2023-03-24_final.stac-item
2023-04-03 09:42:10	ga_ls9c_ard_3-2-1_094077_2023-04-03_final.stac-item
2023-04-08 09:59:53	ga_ls9c_ard_3-2-1_097075_2023-04-08_final.stac-item
2023-04-09 10:43:56	ga_ls9c_ard_3-2-1_104077_2023-04-09_final.stac-item
2023-04-12 09:37:07	ga_ls9c_ard_3-2-1_093080_2023-04-12_final.stac-item
2023-04-13 10:20:46	ga_ls9c_ard_3-2-1_100081_2023-04-13_final.stac-item
2023-04-16 10:50:03	ga_ls9c_ard_3-2-1_105077_2023-04-16_final.stac-item
2023-04-17 09:53:38	ga_ls9c_ard_3-2-1_096075_2023-04-17_final.stac-item
2023-04-17 09:54:50	ga_ls9c_ard_3-2-1_096078_2023-04-17_final.stac-item
2023-04-17 09:55:14	ga_ls9c_ard_3-2-1_096079_2023-04-17_final.stac-item
2023-04-17 09:55:38	ga_ls9c_ard_3-2-1_096080_2023-04-17_final.stac-item
2023-04-18 10:36:54	ga_ls9c_ard_3-2-1_103075_2023-04-18_final.stac-item
2023-04-19 09:42:52	ga_ls9c_ard_3-2-1_094079_2023-04-19_final.stac-item
2023-04-20 10:26:32	ga_ls9c_ard_3-2-1_101080_2023-04-20_final.stac-item
2023-04-21 09:30:06	ga_ls9c_ard_3-2-1_092078_2023-04-21_final.stac-item
2023-04-22 10:12:10	ga_ls9c_ard_3-2-1_099075_2023-04-22_final.stac-item
2023-04-24 09:59:47	ga_ls9c_ard_3-2-1_097075_2023-04-24_final.stac-item
2023-04-24 10:00:11	ga_ls9c_ard_3-2-1_097076_2023-04-24_final.stac-item
2023-04-24 11:40:40	ga_ls9c_ard_3-2-1_113080_2023-04-24_final.stac-item
2023-04-25 10:43:26	ga_ls9c_ard_3-2-1_104076_2023-04-25_final.stac-item
2023-04-28 09:36:37	ga_ls9c_ard_3-2-1_093079_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
2023-05-03 11:32:21	ga_ls9c_ard_3-2-1_112075_2023-05-03_final.stac-item
2023-05-05 11:21:09	ga_ls9c_ard_3-2-1_110078_2023-05-05_final.stac-item
2023-05-06 10:26:20	ga_ls9c_ard_3-2-1_101080_2023-05-06_final.stac-item
2023-05-09 10:56:26	ga_ls9c_ard_3-2-1_106078_2023-05-09_final.stac-item
2023-05-10 10:00:00	ga_ls9c_ard_3-2-1_097076_2023-05-10_final.stac-item
2023-05-10 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-05-10_final.stac-item
2023-05-11 10:43:40	ga_ls9c_ard_3-2-1_104077_2023-05-11_final.stac-item
2023-05-14 09:36:04	ga_ls9c_ard_3-2-1_093078_2023-05-14_final.stac-item
2023-05-19 09:54:57	ga_ls9c_ard_3-2-1_096079_2023-05-19_final.stac-item
2023-05-21 09:41:21	ga_ls9c_ard_3-2-1_094076_2023-05-21_final.stac-item
2023-05-21 09:41:45	ga_ls9c_ard_3-2-1_094077_2023-05-21_final.stac-item
2023-05-21 11:21:50	ga_ls9c_ard_3-2-1_110080_2023-05-21_final.stac-item
2023-05-22 10:26:12	ga_ls9c_ard_3-2-1_101080_2023-05-22_final.stac-item
2023-05-26 09:59:26	ga_ls9c_ard_3-2-1_097075_2023-05-26_final.stac-item
2023-05-26 09:59:50	ga_ls9c_ard_3-2-1_097076_2023-05-26_final.stac-item
2023-05-26 10:02:14	ga_ls9c_ard_3-2-1_097082_2023-05-26_final.stac-item
2023-05-27 10:43:06	ga_ls9c_ard_3-2-1_104076_2023-05-27_final.stac-item
2023-05-27 10:43:30	ga_ls9c_ard_3-2-1_104077_2023-05-27_final.stac-item
2023-06-05 10:36:53	ga_ls9c_ard_3-2-1_103076_2023-06-05_final.stac-item
2023-06-18 10:07:51	ga_ls9c_ard_3-2-1_098081_2023-06-18_final.stac-item
2023-06-27 09:59:19	ga_ls9c_ard_3-2-1_097075_2023-06-27_final.stac-item
2023-06-27 11:39:24	ga_ls9c_ard_3-2-1_113078_2023-06-27_final.stac-item
2023-07-03 11:02:28	ga_ls9c_ard_3-2-1_107078_2023-07-03_final.stac-item
2023-07-06 11:33:24	ga_ls9c_ard_3-2-1_112078_2023-07-06_final.stac-item
2023-07-09 10:25:51	ga_ls9c_ard_3-2-1_101079_2023-07-09_final.stac-item
2023-09-08 11:34:41	ga_ls9c_ard_3-2-1_112080_2023-09-08_final.stac-item
2023-09-12 09:30:19	ga_ls9c_ard_3-2-1_092078_2023-09-12_final.stac-item
2023-09-14 10:56:27	ga_ls9c_ard_3-2-1_106077_2023-09-14_final.stac-item
2023-09-14 10:58:51	ga_ls9c_ard_3-2-1_106083_2023-09-14_final.stac-item
2023-09-15 10:02:50	ga_ls9c_ard_3-2-1_097082_2023-09-15_final.stac-item
2023-09-15 11:39:43	ga_ls9c_ard_3-2-1_113077_2023-09-15_final.stac-item
2023-09-16 10:44:54	ga_ls9c_ard_3-2-1_104079_2023-09-16_final.stac-item
2023-09-16 10:45:42	ga_ls9c_ard_3-2-1_104081_2023-09-16_final.stac-item
2023-09-17 11:26:58	ga_ls9c_ard_3-2-1_111076_2023-09-17_final.stac-item
2023-09-19 09:36:55	ga_ls9c_ard_3-2-1_093079_2023-09-19_final.stac-item
2023-09-19 11:16:12	ga_ls9c_ard_3-2-1_109080_2023-09-19_final.stac-item
2023-09-24 09:53:49	ga_ls9c_ard_3-2-1_096075_2023-09-24_final.stac-item
2023-09-25 10:38:40	ga_ls9c_ard_3-2-1_103079_2023-09-25_final.stac-item
2023-09-26 09:42:14	ga_ls9c_ard_3-2-1_094077_2023-09-26_final.stac-item
2023-09-27 10:26:17	ga_ls9c_ard_3-2-1_101079_2023-09-27_final.stac-item
2023-09-29 10:12:20	ga_ls9c_ard_3-2-1_099075_2023-09-29_final.stac-item
2023-10-01 10:00:25	ga_ls9c_ard_3-2-1_097076_2023-10-01_final.stac-item
2023-10-01 11:39:42	ga_ls9c_ard_3-2-1_113077_2023-10-01_final.stac-item
2023-10-05 09:36:57	ga_ls9c_ard_3-2-1_093079_2023-10-05_final.stac-item
2023-10-07 11:03:05	ga_ls9c_ard_3-2-1_107078_2023-10-07_final.stac-item
2023-10-10 09:54:44	ga_ls9c_ard_3-2-1_096077_2023-10-10_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