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
2021-11-15 09:44:21	ga_ls9c_ard_3-2-1_094083_2021-11-15_final.stac-item
2021-11-23 10:03:38	ga_ls9c_ard_3-2-1_098072_2021-11-23_final.stac-item
2021-11-24 10:42:23	ga_ls9c_ard_3-2-1_104069_2021-11-24_final.stac-item
2021-12-22 10:48:29	ga_ls9c_ard_3-2-1_105072_2021-12-22_final.stac-item
2022-01-02 10:29:57	ga_ls9c_ard_3-2-1_102072_2022-01-02_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-01-12 09:29:42	ga_ls9c_ard_3-2-1_092076_2022-01-11_final.stac-item
2022-01-28 11:09:49	ga_ls9c_ard_3-2-1_108079_2022-01-28_final.stac-item
2022-02-02 09:51:04	ga_ls9c_ard_3-2-1_095083_2022-02-02_final.stac-item
2022-02-04 09:37:54	ga_ls9c_ard_3-2-1_093081_2022-02-04_final.stac-item
2022-02-09 09:55:37	ga_ls9c_ard_3-2-1_096079_2022-02-09_final.stac-item
2022-02-11 09:44:27	ga_ls9c_ard_3-2-1_094082_2022-02-11_final.stac-item
2022-02-16 11:41:50	ga_ls9c_ard_3-2-1_113082_2022-02-16_final.stac-item
2022-02-22 09:27:48	ga_ls9c_ard_3-2-1_091087_2022-02-21_final.stac-item
2022-02-23 10:10:15	ga_ls9c_ard_3-2-1_098085_2022-02-23_final.stac-item
2022-02-27 11:20:46	ga_ls9c_ard_3-2-1_110076_2022-02-27_final.stac-item
2022-03-10 09:24:30	ga_ls9c_ard_3-2-1_091079_2022-03-09_final.stac-item
2022-04-02 11:09:53	ga_ls9c_ard_3-2-1_108080_2022-04-02_final.stac-item
2022-04-06 10:40:22	ga_ls9c_ard_3-2-1_104068_2022-04-06_final.stac-item
2022-04-09 11:14:50	ga_ls9c_ard_3-2-1_109077_2022-04-09_final.stac-item
2022-04-14 11:34:55	ga_ls9c_ard_3-2-1_112081_2022-04-14_final.stac-item
2022-04-23 09:50:33	ga_ls9c_ard_3-2-1_095083_2022-04-23_final.stac-item
2022-05-06 10:58:05	ga_ls9c_ard_3-2-1_106082_2022-05-06_final.stac-item
2022-05-11 11:12:58	ga_ls9c_ard_3-2-1_109073_2022-05-11_final.stac-item
2022-05-15 10:46:36	ga_ls9c_ard_3-2-1_105069_2022-05-15_final.stac-item
2022-05-24 10:44:44	ga_ls9c_ard_3-2-1_104080_2022-05-24_final.stac-item
2022-05-28 10:17:37	ga_ls9c_ard_3-2-1_100074_2022-05-28_final.stac-item
2022-05-31 09:13:38	ga_ls9c_ard_3-2-1_089084_2022-05-30_final.stac-item
2022-06-12 11:14:30	ga_ls9c_ard_3-2-1_109077_2022-06-12_final.stac-item
2022-06-14 11:01:46	ga_ls9c_ard_3-2-1_107076_2022-06-14_final.stac-item
2022-06-16 10:45:51	ga_ls9c_ard_3-2-1_105067_2022-06-16_final.stac-item
2022-06-18 10:37:30	ga_ls9c_ard_3-2-1_103077_2022-06-18_final.stac-item
2022-06-28 11:12:25	ga_ls9c_ard_3-2-1_109071_2022-06-28_final.stac-item
2022-07-04 10:37:42	ga_ls9c_ard_3-2-1_103077_2022-07-04_final.stac-item
2022-07-12 09:51:24	ga_ls9c_ard_3-2-1_095085_2022-07-12_final.stac-item
2022-07-13 10:27:53	ga_ls9c_ard_3-2-1_102068_2022-07-13_final.stac-item
2022-07-13 10:29:04	ga_ls9c_ard_3-2-1_102071_2022-07-13_final.stac-item
2022-07-18 09:11:10	ga_ls9c_ard_3-2-1_089077_2022-07-17_final.stac-item
2022-07-24 11:50:46	ga_ls9c_ard_3-2-1_115074_2022-07-24_final.stac-item
2022-07-26 11:40:26	ga_ls9c_ard_3-2-1_113079_2022-07-26_final.stac-item
2022-07-28 09:47:37	ga_ls9c_ard_3-2-1_095075_2022-07-28_final.stac-item
2022-08-16 10:20:18	ga_ls9c_ard_3-2-1_100079_2022-08-16_final.stac-item
2022-08-17 09:21:53	ga_ls9c_ard_3-2-1_091072_2022-08-16_final.stac-item
2022-08-18 10:06:21	ga_ls9c_ard_3-2-1_098075_2022-08-18_final.stac-item
2022-08-26 10:54:13	ga_ls9c_ard_3-2-1_106071_2022-08-26_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-09-16 11:15:13	ga_ls9c_ard_3-2-1_109077_2022-09-16_final.stac-item
2022-09-20 09:14:50	ga_ls9c_ard_3-2-1_089085_2022-09-19_final.stac-item
2022-09-21 11:35:48	ga_ls9c_ard_3-2-1_112082_2022-09-21_final.stac-item
2022-10-02 09:34:00	ga_ls9c_ard_3-2-1_093071_2022-10-02_final.stac-item
2022-10-11 11:10:44	ga_ls9c_ard_3-2-1_108081_2022-10-11_final.stac-item
2022-10-18 09:38:05	ga_ls9c_ard_3-2-1_093081_2022-10-18_final.stac-item
2022-10-18 11:14:58	ga_ls9c_ard_3-2-1_109076_2022-10-18_final.stac-item
2022-10-22 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-10-22_final.stac-item
2022-10-22 10:48:16	ga_ls9c_ard_3-2-1_105071_2022-10-22_final.stac-item
2022-10-22 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-10-22_final.stac-item
2022-10-28 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-10-28_final.stac-item
2022-11-05 11:00:59	ga_ls9c_ard_3-2-1_107072_2022-11-05_final.stac-item
2022-11-10 09:44:40	ga_ls9c_ard_3-2-1_094082_2022-11-10_final.stac-item
2022-11-12 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-11-12_final.stac-item
2022-11-14 09:20:46	ga_ls9c_ard_3-2-1_090084_2022-11-13_final.stac-item
2022-11-17 11:27:21	ga_ls9c_ard_3-2-1_111076_2022-11-17_final.stac-item
2022-11-22 10:09:24	ga_ls9c_ard_3-2-1_098082_2022-11-22_final.stac-item
2022-11-27 10:25:55	ga_ls9c_ard_3-2-1_101077_2022-11-27_final.stac-item
2022-12-03 09:51:12	ga_ls9c_ard_3-2-1_095083_2022-12-03_final.stac-item
2022-12-19 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-12-19_final.stac-item
2022-12-23 09:22:05	ga_ls9c_ard_3-2-1_091072_2022-12-22_final.stac-item
2023-01-01 09:19:09	ga_ls9c_ard_3-2-1_090080_2022-12-31_final.stac-item
2023-01-03 10:45:16	ga_ls9c_ard_3-2-1_104079_2023-01-03_final.stac-item
2023-01-10 10:51:26	ga_ls9c_ard_3-2-1_105079_2023-01-10_final.stac-item
2023-01-22 11:13:38	ga_ls9c_ard_3-2-1_109073_2023-01-22_final.stac-item
2023-01-25 10:03:19	ga_ls9c_ard_3-2-1_098067_2023-01-25_final.stac-item
2023-01-27 09:53:23	ga_ls9c_ard_3-2-1_096073_2023-01-27_final.stac-item
2023-02-07 09:38:09	ga_ls9c_ard_3-2-1_093081_2023-02-07_final.stac-item
2023-02-07 11:13:50	ga_ls9c_ard_3-2-1_109073_2023-02-07_final.stac-item
2023-02-18 10:54:48	ga_ls9c_ard_3-2-1_106072_2023-02-18_final.stac-item
2023-03-02 09:44:04	ga_ls9c_ard_3-2-1_094081_2023-03-02_final.stac-item
2023-03-03 10:23:44	ga_ls9c_ard_3-2-1_101072_2023-03-03_final.stac-item
2023-03-11 11:13:04	ga_ls9c_ard_3-2-1_109072_2023-03-11_final.stac-item
2023-03-12 11:58:44	ga_ls9c_ard_3-2-1_116078_2023-03-12_final.stac-item
2023-04-04 10:23:50	ga_ls9c_ard_3-2-1_101073_2023-04-04_final.stac-item
2023-04-16 09:14:21	ga_ls9c_ard_3-2-1_089085_2023-04-15_final.stac-item
2023-04-23 10:54:13	ga_ls9c_ard_3-2-1_106072_2023-04-23_final.stac-item
2023-04-30 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-04-30_final.stac-item
2023-05-06 10:23:08	ga_ls9c_ard_3-2-1_101072_2023-05-06_final.stac-item
2023-05-17 11:44:13	ga_ls9c_ard_3-2-1_114074_2023-05-17_final.stac-item
2023-07-04 11:44:32	ga_ls9c_ard_3-2-1_114075_2023-07-04_final.stac-item
2023-07-13 11:40:26	ga_ls9c_ard_3-2-1_113080_2023-07-13_final.stac-item
2023-07-17 11:12:56	ga_ls9c_ard_3-2-1_109073_2023-07-17_final.stac-item
2023-07-18 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-07-18_final.stac-item
2023-07-22 11:35:03	ga_ls9c_ard_3-2-1_112082_2023-07-22_final.stac-item
2023-07-31 09:47:17	ga_ls9c_ard_3-2-1_095075_2023-07-31_final.stac-item
2023-08-09 11:20:28	ga_ls9c_ard_3-2-1_110076_2023-08-09_final.stac-item
2023-08-11 11:05:19	ga_ls9c_ard_3-2-1_108069_2023-08-11_final.stac-item
2023-08-18 11:12:41	ga_ls9c_ard_3-2-1_109072_2023-08-18_final.stac-item
2023-10-16 09:19:20	ga_ls9c_ard_3-2-1_090081_2023-10-15_final.stac-item
2023-10-23 09:28:43	ga_ls9c_ard_3-2-1_091089_2023-10-22_final.stac-item
2023-11-20 09:49:26	ga_ls9c_ard_3-2-1_095079_2023-11-20_final.stac-item
2023-11-22 11:13:36	ga_ls9c_ard_3-2-1_109073_2023-11-22_final.stac-item
2023-11-25 11:47:19	ga_ls9c_ard_3-2-1_114080_2023-11-25_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