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
2021-12-06 09:12:54	ga_ls9c_ard_3-2-1_089080_2021-12-05_final.stac-item
2021-12-20 09:26:45	ga_ls9c_ard_3-2-1_091084_2021-12-19_final.stac-item
2021-12-20 11:05:14	ga_ls9c_ard_3-2-1_107083_2021-12-20_final.stac-item
2022-01-04 10:17:35	ga_ls9c_ard_3-2-1_100072_2022-01-04_final.stac-item
2022-01-14 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-01-13_final.stac-item
2022-01-18 10:33:30	ga_ls9c_ard_3-2-1_102081_2022-01-18_final.stac-item
2022-01-25 10:35:19	ga_ls9c_ard_3-2-1_103070_2022-01-25_final.stac-item
2022-02-09 09:52:26	ga_ls9c_ard_3-2-1_096071_2022-02-09_final.stac-item
2022-02-14 10:15:19	ga_ls9c_ard_3-2-1_099082_2022-02-14_final.stac-item
2022-02-20 09:33:48	ga_ls9c_ard_3-2-1_093071_2022-02-20_final.stac-item
2022-02-24 10:52:42	ga_ls9c_ard_3-2-1_105083_2022-02-24_final.stac-item
2022-03-01 09:29:29	ga_ls9c_ard_3-2-1_092076_2022-02-28_final.stac-item
2022-03-10 11:04:59	ga_ls9c_ard_3-2-1_107083_2022-03-10_final.stac-item
2022-03-19 10:55:35	ga_ls9c_ard_3-2-1_106075_2022-03-19_final.stac-item
2022-03-20 11:41:38	ga_ls9c_ard_3-2-1_113082_2022-03-20_final.stac-item
2022-04-23 11:24:38	ga_ls9c_ard_3-2-1_111071_2022-04-23_final.stac-item
2022-04-28 10:04:18	ga_ls9c_ard_3-2-1_098071_2022-04-28_final.stac-item
2022-04-28 10:07:29	ga_ls9c_ard_3-2-1_098079_2022-04-28_final.stac-item
2022-05-05 10:13:14	ga_ls9c_ard_3-2-1_099078_2022-05-05_final.stac-item
2022-05-08 09:06:25	ga_ls9c_ard_3-2-1_088081_2022-05-07_final.stac-item
2022-05-19 10:22:13	ga_ls9c_ard_3-2-1_101070_2022-05-19_final.stac-item
2022-05-27 11:13:14	ga_ls9c_ard_3-2-1_109074_2022-05-27_final.stac-item
2022-06-01 11:35:47	ga_ls9c_ard_3-2-1_112084_2022-06-01_final.stac-item
2022-06-02 10:39:22	ga_ls9c_ard_3-2-1_103082_2022-06-02_final.stac-item
2022-06-06 11:52:44	ga_ls9c_ard_3-2-1_115080_2022-06-06_final.stac-item
2022-07-01 10:03:13	ga_ls9c_ard_3-2-1_098068_2022-07-01_final.stac-item
2022-07-02 10:47:41	ga_ls9c_ard_3-2-1_105071_2022-07-02_final.stac-item
2022-07-03 11:36:07	ga_ls9c_ard_3-2-1_112084_2022-07-03_final.stac-item
2022-07-06 10:25:44	ga_ls9c_ard_3-2-1_101078_2022-07-06_final.stac-item
2022-08-03 09:14:36	ga_ls9c_ard_3-2-1_089085_2022-08-02_final.stac-item
2022-08-17 09:29:04	ga_ls9c_ard_3-2-1_091090_2022-08-16_final.stac-item
2022-09-18 09:24:47	ga_ls9c_ard_3-2-1_091079_2022-09-17_final.stac-item
2022-09-19 10:04:04	ga_ls9c_ard_3-2-1_098069_2022-09-19_final.stac-item
2022-09-23 11:20:39	ga_ls9c_ard_3-2-1_110075_2022-09-23_final.stac-item
2022-09-26 11:51:58	ga_ls9c_ard_3-2-1_115076_2022-09-26_final.stac-item
2022-10-04 11:00:07	ga_ls9c_ard_3-2-1_107070_2022-10-04_final.stac-item
2022-10-05 10:04:06	ga_ls9c_ard_3-2-1_098069_2022-10-05_final.stac-item
2022-11-03 09:38:26	ga_ls9c_ard_3-2-1_093082_2022-11-03_final.stac-item
2022-11-08 11:35:30	ga_ls9c_ard_3-2-1_112081_2022-11-08_final.stac-item
2022-11-12 11:06:49	ga_ls9c_ard_3-2-1_108071_2022-11-12_final.stac-item
2022-11-28 11:05:59	ga_ls9c_ard_3-2-1_108069_2022-11-28_final.stac-item
2022-11-30 09:20:42	ga_ls9c_ard_3-2-1_090084_2022-11-29_final.stac-item
2022-11-30 10:56:00	ga_ls9c_ard_3-2-1_106075_2022-11-30_final.stac-item
2022-12-11 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-12-11_final.stac-item
2022-12-24 11:45:01	ga_ls9c_ard_3-2-1_114074_2022-12-24_final.stac-item
2022-12-27 10:37:28	ga_ls9c_ard_3-2-1_103075_2022-12-27_final.stac-item
2022-12-28 09:44:38	ga_ls9c_ard_3-2-1_094082_2022-12-28_final.stac-item
2022-12-31 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-31_final.stac-item
2023-01-08 09:28:31	ga_ls9c_ard_3-2-1_091088_2023-01-07_final.stac-item
2023-01-13 11:23:31	ga_ls9c_ard_3-2-1_110082_2023-01-13_final.stac-item
2023-01-18 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-01-18_final.stac-item
2023-01-18 11:39:11	ga_ls9c_ard_3-2-1_113075_2023-01-18_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-26 09:12:06	ga_ls9c_ard_3-2-1_089078_2023-01-25_final.stac-item
2023-01-30 10:24:20	ga_ls9c_ard_3-2-1_101073_2023-01-30_final.stac-item
2023-02-08 10:17:49	ga_ls9c_ard_3-2-1_100072_2023-02-08_final.stac-item
2023-03-04 11:11:22	ga_ls9c_ard_3-2-1_108083_2023-03-04_final.stac-item
2023-03-06 10:56:11	ga_ls9c_ard_3-2-1_106076_2023-03-06_final.stac-item
2023-03-14 10:08:17	ga_ls9c_ard_3-2-1_098080_2023-03-14_final.stac-item
2023-03-18 11:24:02	ga_ls9c_ard_3-2-1_110084_2023-03-18_final.stac-item
2023-03-24 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-03-24_final.stac-item
2023-03-29 09:23:14	ga_ls9c_ard_3-2-1_091076_2023-03-28_final.stac-item
2023-03-31 09:16:04	ga_ls9c_ard_3-2-1_089089_2023-03-30_final.stac-item
2023-04-06 10:15:28	ga_ls9c_ard_3-2-1_099083_2023-04-06_final.stac-item
2023-04-16 09:11:34	ga_ls9c_ard_3-2-1_089078_2023-04-15_final.stac-item
2023-04-23 09:22:07	ga_ls9c_ard_3-2-1_090089_2023-04-22_final.stac-item
2023-04-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2023-04-23_final.stac-item
2023-04-29 10:16:40	ga_ls9c_ard_3-2-1_100071_2023-04-29_final.stac-item
2023-04-29 10:19:27	ga_ls9c_ard_3-2-1_100078_2023-04-29_final.stac-item
2023-05-01 11:44:45	ga_ls9c_ard_3-2-1_114075_2023-05-01_final.stac-item
2023-05-05 11:23:09	ga_ls9c_ard_3-2-1_110083_2023-05-05_final.stac-item
2023-05-19 11:31:26	ga_ls9c_ard_3-2-1_112073_2023-05-19_final.stac-item
2023-05-26 10:03:02	ga_ls9c_ard_3-2-1_097084_2023-05-26_final.stac-item
2023-05-26 11:41:31	ga_ls9c_ard_3-2-1_113083_2023-05-26_final.stac-item
2023-06-03 09:13:34	ga_ls9c_ard_3-2-1_089084_2023-06-02_final.stac-item
2023-06-06 09:39:16	ga_ls9c_ard_3-2-1_094071_2023-06-06_final.stac-item
2023-06-09 10:09:44	ga_ls9c_ard_3-2-1_099070_2023-06-09_final.stac-item
2023-06-17 09:21:48	ga_ls9c_ard_3-2-1_091074_2023-06-16_final.stac-item
2023-06-25 10:14:26	ga_ls9c_ard_3-2-1_099082_2023-06-25_final.stac-item
2023-06-25 10:14:50	ga_ls9c_ard_3-2-1_099083_2023-06-25_final.stac-item
2023-06-26 09:21:37	ga_ls9c_ard_3-2-1_090089_2023-06-25_final.stac-item
2023-07-03 09:25:58	ga_ls9c_ard_3-2-1_091084_2023-07-02_final.stac-item
2023-07-05 09:12:50	ga_ls9c_ard_3-2-1_089082_2023-07-04_final.stac-item
2023-07-11 10:09:55	ga_ls9c_ard_3-2-1_099070_2023-07-11_final.stac-item
2023-07-26 11:06:45	ga_ls9c_ard_3-2-1_108073_2023-07-26_final.stac-item
2023-07-31 11:24:58	ga_ls9c_ard_3-2-1_111072_2023-07-31_final.stac-item
2023-08-02 09:34:57	ga_ls9c_ard_3-2-1_093075_2023-08-02_final.stac-item
2023-08-04 09:22:13	ga_ls9c_ard_3-2-1_091074_2023-08-03_final.stac-item
2023-08-05 10:09:29	ga_ls9c_ard_3-2-1_098084_2023-08-05_final.stac-item
2023-08-13 10:52:34	ga_ls9c_ard_3-2-1_106068_2023-08-13_final.stac-item
2023-08-13 10:55:45	ga_ls9c_ard_3-2-1_106076_2023-08-13_final.stac-item
2023-08-20 09:28:40	ga_ls9c_ard_3-2-1_091090_2023-08-19_final.stac-item
2023-08-21 10:03:58	ga_ls9c_ard_3-2-1_098070_2023-08-21_final.stac-item
2023-08-23 09:57:13	ga_ls9c_ard_3-2-1_096084_2023-08-23_final.stac-item
2023-09-07 09:11:20	ga_ls9c_ard_3-2-1_089077_2023-09-06_final.stac-item
2023-09-13 10:09:36	ga_ls9c_ard_3-2-1_099068_2023-09-13_final.stac-item
2023-09-14 09:22:46	ga_ls9c_ard_3-2-1_090090_2023-09-13_final.stac-item
2023-11-01 10:52:56	ga_ls9c_ard_3-2-1_106068_2023-11-01_final.stac-item
2023-11-16 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-11-16_final.stac-item
2023-11-23 11:58:04	ga_ls9c_ard_3-2-1_116076_2023-11-23_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