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
2021-11-25 09:46:04	ga_ls9c_ard_3-2-1_095075_2021-11-25_final.stac-item
2021-12-16 11:26:45	ga_ls9c_ard_3-2-1_111075_2021-12-16_final.stac-item
2021-12-28 11:51:54	ga_ls9c_ard_3-2-1_115076_2021-12-28_final.stac-item
2021-12-29 10:55:28	ga_ls9c_ard_3-2-1_106074_2021-12-29_final.stac-item
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-01-02 10:31:56	ga_ls9c_ard_3-2-1_102077_2022-01-02_final.stac-item
2022-01-07 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-06_final.stac-item
2022-01-29 11:53:05	ga_ls9c_ard_3-2-1_115079_2022-01-29_final.stac-item
2022-02-02 11:23:58	ga_ls9c_ard_3-2-1_111068_2022-02-02_final.stac-item
2022-02-07 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-02-07_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-03-02 11:51:37	ga_ls9c_ard_3-2-1_115076_2022-03-02_final.stac-item
2022-03-23 10:32:50	ga_ls9c_ard_3-2-1_102080_2022-03-23_final.stac-item
2022-04-04 10:52:44	ga_ls9c_ard_3-2-1_106068_2022-04-04_final.stac-item
2022-04-16 09:40:51	ga_ls9c_ard_3-2-1_094074_2022-04-16_final.stac-item
2022-04-16 11:18:56	ga_ls9c_ard_3-2-1_110072_2022-04-16_final.stac-item
2022-05-10 10:28:08	ga_ls9c_ard_3-2-1_102069_2022-05-10_final.stac-item
2022-05-14 10:02:57	ga_ls9c_ard_3-2-1_098068_2022-05-14_final.stac-item
2022-05-14 10:06:57	ga_ls9c_ard_3-2-1_098078_2022-05-14_final.stac-item
2022-05-15 09:11:43	ga_ls9c_ard_3-2-1_089079_2022-05-14_final.stac-item
2022-05-30 10:04:04	ga_ls9c_ard_3-2-1_098071_2022-05-30_final.stac-item
2022-06-03 09:40:09	ga_ls9c_ard_3-2-1_094073_2022-06-03_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-07 09:18:38	ga_ls9c_ard_3-2-1_090081_2022-06-06_final.stac-item
2022-06-07 09:22:13	ga_ls9c_ard_3-2-1_090090_2022-06-06_final.stac-item
2022-06-10 09:45:33	ga_ls9c_ard_3-2-1_095071_2022-06-10_final.stac-item
2022-07-10 09:57:48	ga_ls9c_ard_3-2-1_097070_2022-07-10_final.stac-item
2022-08-14 10:30:15	ga_ls9c_ard_3-2-1_102073_2022-08-14_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-09-19 10:04:52	ga_ls9c_ard_3-2-1_098071_2022-09-19_final.stac-item
2022-09-24 10:23:26	ga_ls9c_ard_3-2-1_101071_2022-09-24_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-21 10:09:47	ga_ls9c_ard_3-2-1_098083_2022-10-21_final.stac-item
2022-10-29 10:56:01	ga_ls9c_ard_3-2-1_106075_2022-10-29_final.stac-item
2022-11-01 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-11-01_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-07 09:13:21	ga_ls9c_ard_3-2-1_089081_2022-11-06_final.stac-item
2022-11-08 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-08_final.stac-item
2022-11-14 10:53:16	ga_ls9c_ard_3-2-1_106068_2022-11-14_final.stac-item
2022-11-17 09:47:17	ga_ls9c_ard_3-2-1_095073_2022-11-17_final.stac-item
2022-11-20 10:22:34	ga_ls9c_ard_3-2-1_100084_2022-11-20_final.stac-item
2022-11-26 11:18:45	ga_ls9c_ard_3-2-1_110070_2022-11-26_final.stac-item
2022-11-28 11:08:46	ga_ls9c_ard_3-2-1_108076_2022-11-28_final.stac-item
2022-11-29 11:51:38	ga_ls9c_ard_3-2-1_115075_2022-11-29_final.stac-item
2022-11-30 10:55:36	ga_ls9c_ard_3-2-1_106074_2022-11-30_final.stac-item
2022-12-08 10:06:59	ga_ls9c_ard_3-2-1_098076_2022-12-08_final.stac-item
2022-12-13 10:23:08	ga_ls9c_ard_3-2-1_101070_2022-12-13_final.stac-item
2022-12-13 10:23:32	ga_ls9c_ard_3-2-1_101071_2022-12-13_final.stac-item
2022-12-14 09:34:18	ga_ls9c_ard_3-2-1_092087_2022-12-14_final.stac-item
2022-12-15 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-12-15_final.stac-item
2022-12-20 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-20_final.stac-item
2022-12-30 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-30_final.stac-item
2023-01-04 09:52:27	ga_ls9c_ard_3-2-1_095086_2023-01-04_final.stac-item
2023-01-09 10:03:48	ga_ls9c_ard_3-2-1_098068_2023-01-09_final.stac-item
2023-01-09 11:46:40	ga_ls9c_ard_3-2-1_114078_2023-01-09_final.stac-item
2023-01-11 11:32:18	ga_ls9c_ard_3-2-1_112073_2023-01-11_final.stac-item
2023-01-12 10:35:04	ga_ls9c_ard_3-2-1_103069_2023-01-12_final.stac-item
2023-01-12 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-12_final.stac-item
2023-01-17 09:20:15	ga_ls9c_ard_3-2-1_090083_2023-01-16_final.stac-item
2023-01-19 09:06:39	ga_ls9c_ard_3-2-1_088080_2023-01-18_final.stac-item
2023-01-21 10:33:33	ga_ls9c_ard_3-2-1_102081_2023-01-21_final.stac-item
2023-01-22 09:35:33	ga_ls9c_ard_3-2-1_093075_2023-01-22_final.stac-item
2023-01-24 09:26:49	ga_ls9c_ard_3-2-1_091084_2023-01-23_final.stac-item
2023-01-26 09:12:54	ga_ls9c_ard_3-2-1_089080_2023-01-25_final.stac-item
2023-01-29 11:24:20	ga_ls9c_ard_3-2-1_110084_2023-01-29_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-11 09:11:49	ga_ls9c_ard_3-2-1_089077_2023-02-10_final.stac-item
2023-03-11 11:11:52	ga_ls9c_ard_3-2-1_109069_2023-03-11_final.stac-item
2023-04-02 10:36:36	ga_ls9c_ard_3-2-1_103074_2023-04-02_final.stac-item
2023-04-06 11:51:09	ga_ls9c_ard_3-2-1_115075_2023-04-06_final.stac-item
2023-04-07 10:55:55	ga_ls9c_ard_3-2-1_106076_2023-04-07_final.stac-item
2023-04-28 11:13:54	ga_ls9c_ard_3-2-1_109075_2023-04-28_final.stac-item
2023-05-03 09:57:27	ga_ls9c_ard_3-2-1_096085_2023-05-03_final.stac-item
2023-05-14 11:12:57	ga_ls9c_ard_3-2-1_109073_2023-05-14_final.stac-item
2023-05-18 09:12:06	ga_ls9c_ard_3-2-1_089080_2023-05-17_final.stac-item
2023-05-21 09:43:45	ga_ls9c_ard_3-2-1_094082_2023-05-21_final.stac-item
2023-06-18 10:02:40	ga_ls9c_ard_3-2-1_098068_2023-06-18_final.stac-item
2023-06-19 09:12:14	ga_ls9c_ard_3-2-1_089081_2023-06-18_final.stac-item
2023-06-26 09:17:37	ga_ls9c_ard_3-2-1_090079_2023-06-25_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-07-27 10:13:56	ga_ls9c_ard_3-2-1_099080_2023-07-27_final.stac-item
2023-07-29 09:57:37	ga_ls9c_ard_3-2-1_097070_2023-07-29_final.stac-item
2023-07-31 11:29:22	ga_ls9c_ard_3-2-1_111083_2023-07-31_final.stac-item
2023-08-05 11:45:10	ga_ls9c_ard_3-2-1_114076_2023-08-05_final.stac-item
2023-08-12 10:10:06	ga_ls9c_ard_3-2-1_099070_2023-08-12_final.stac-item
2023-08-14 09:58:08	ga_ls9c_ard_3-2-1_097071_2023-08-14_final.stac-item
2023-08-15 10:40:12	ga_ls9c_ard_3-2-1_104068_2023-08-15_final.stac-item
2023-10-15 11:51:26	ga_ls9c_ard_3-2-1_115075_2023-10-15_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_final.stac-item
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final.stac-item
2023-11-14 10:23:16	ga_ls9c_ard_3-2-1_101071_2023-11-14_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-11-15 09:33:13	ga_ls9c_ard_3-2-1_092085_2023-11-15_final.stac-item
2023-11-15 11:06:31	ga_ls9c_ard_3-2-1_108071_2023-11-15_final.stac-item
2023-11-19 10:45:27	ga_ls9c_ard_3-2-1_104080_2023-11-19_final.stac-item
2023-11-23 10:17:11	ga_ls9c_ard_3-2-1_100071_2023-11-23_final.stac-item
2023-11-29 11:19:25	ga_ls9c_ard_3-2-1_110072_2023-11-29_final.stac-item
2024-02-19 09:30:49	ga_ls9c_ard_3-2-1_092079_2024-02-19_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