Search ga_ls8c_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:

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First 100 results (query limit)

Time (local)	Label
2017-12-25 10:08:55	ga_ls8c_ard_3-2-1_099066_2017-12-25_final
2022-05-31 11:42:25	ga_ls8c_ard_3-2-1_113084_2022-05-31_final
2022-08-02 10:56:25	ga_ls8c_ard_3-2-1_106076_2022-08-02_final
2022-08-15 10:26:00	ga_ls8c_ard_3-2-1_101077_2022-08-15_final
2022-08-18 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-08-18_final
2022-08-19 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-08-19_final
2022-08-21 09:52:32	ga_ls8c_ard_3-2-1_095086_2022-08-21_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-08-25 09:25:49	ga_ls8c_ard_3-2-1_091081_2022-08-24_final
2022-08-26 10:03:29	ga_ls8c_ard_3-2-1_098067_2022-08-26_final
2022-09-03 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-09-02_final
2022-09-04 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-09-04_final
2022-09-11 10:03:57	ga_ls8c_ard_3-2-1_098068_2022-09-11_final
2022-09-29 09:58:25	ga_ls8c_ard_3-2-1_096085_2022-09-29_final
2022-10-03 09:33:17	ga_ls8c_ard_3-2-1_092084_2022-10-03_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-10-24 11:29:29	ga_ls8c_ard_3-2-1_111081_2022-10-24_final
2022-11-02 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-11-02_final
2022-11-10 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-11-10_final
2022-11-20 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-11-20_final
2022-11-22 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-11-21_final
2022-12-02 11:32:50	ga_ls8c_ard_3-2-1_112074_2022-12-02_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-17 09:13:46	ga_ls8c_ard_3-2-1_089082_2022-12-16_final
2022-12-23 10:15:53	ga_ls8c_ard_3-2-1_099083_2022-12-23_final
2022-12-24 09:21:28	ga_ls8c_ard_3-2-1_090086_2022-12-23_final
2022-12-25 10:02:21	ga_ls8c_ard_3-2-1_097080_2022-12-25_final
2022-12-27 11:25:41	ga_ls8c_ard_3-2-1_111072_2022-12-27_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-03 09:53:00	ga_ls8c_ard_3-2-1_096072_2023-01-03_final
2023-01-07 11:06:45	ga_ls8c_ard_3-2-1_108071_2023-01-07_final
2023-01-16 09:27:10	ga_ls8c_ard_3-2-1_091085_2023-01-15_final
2023-01-17 10:07:37	ga_ls8c_ard_3-2-1_098078_2023-01-17_final
2023-02-07 10:24:15	ga_ls8c_ard_3-2-1_101073_2023-02-07_final
2023-02-09 10:16:15	ga_ls8c_ard_3-2-1_099084_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-11 11:42:21	ga_ls8c_ard_3-2-1_113083_2023-02-11_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-11 10:27:27	ga_ls8c_ard_3-2-1_101082_2023-03-11_final
2023-03-14 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-03-14_final
2023-03-21 09:28:21	ga_ls8c_ard_3-2-1_091089_2023-03-20_final
2023-03-22 10:03:13	ga_ls8c_ard_3-2-1_098068_2023-03-22_final
2023-03-28 11:06:10	ga_ls8c_ard_3-2-1_108071_2023-03-28_final
2023-04-02 09:47:22	ga_ls8c_ard_3-2-1_095075_2023-04-02_final
2023-04-06 09:28:09	ga_ls8c_ard_3-2-1_091089_2023-04-05_final
2023-04-18 09:46:44	ga_ls8c_ard_3-2-1_095074_2023-04-18_final
2023-04-26 10:35:21	ga_ls8c_ard_3-2-1_103072_2023-04-26_final
2023-04-29 09:32:33	ga_ls8c_ard_3-2-1_092085_2023-04-29_final
2023-05-01 09:16:34	ga_ls8c_ard_3-2-1_090076_2023-04-30_final
2023-05-04 09:46:15	ga_ls8c_ard_3-2-1_095073_2023-05-04_final
2023-05-06 11:13:56	ga_ls8c_ard_3-2-1_109076_2023-05-06_final
2023-05-15 09:32:44	ga_ls8c_ard_3-2-1_092086_2023-05-15_final
2023-05-15 11:10:49	ga_ls8c_ard_3-2-1_108084_2023-05-15_final
2023-05-18 10:02:48	ga_ls8c_ard_3-2-1_097084_2023-05-18_final
2023-05-18 10:03:12	ga_ls8c_ard_3-2-1_097085_2023-05-18_final
2023-05-20 09:45:41	ga_ls8c_ard_3-2-1_095072_2023-05-20_final
2023-05-21 10:28:33	ga_ls8c_ard_3-2-1_102071_2023-05-21_final
2023-05-22 09:38:55	ga_ls8c_ard_3-2-1_093086_2023-05-22_final
2023-06-10 11:44:03	ga_ls8c_ard_3-2-1_114074_2023-06-10_final
2023-06-17 10:09:00	ga_ls8c_ard_3-2-1_099068_2023-06-17_final
2023-06-17 10:09:48	ga_ls8c_ard_3-2-1_099070_2023-06-17_final
2023-06-28 09:57:20	ga_ls8c_ard_3-2-1_096085_2023-06-28_final
2023-06-28 11:31:50	ga_ls8c_ard_3-2-1_112074_2023-06-28_final
2023-07-04 10:52:50	ga_ls8c_ard_3-2-1_106069_2023-07-04_final
2023-07-11 09:26:34	ga_ls8c_ard_3-2-1_091085_2023-07-10_final
2023-07-11 09:26:58	ga_ls8c_ard_3-2-1_091086_2023-07-10_final
2023-07-24 10:33:00	ga_ls8c_ard_3-2-1_102081_2023-07-24_final
2023-07-26 11:58:22	ga_ls8c_ard_3-2-1_116078_2023-07-26_final
2023-08-13 10:02:50	ga_ls8c_ard_3-2-1_098067_2023-08-13_final
2023-08-28 09:28:04	ga_ls8c_ard_3-2-1_091088_2023-08-27_final
2023-09-02 09:39:49	ga_ls8c_ard_3-2-1_094071_2023-09-02_final
2023-09-06 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-09-06_final
2023-09-14 10:03:48	ga_ls8c_ard_3-2-1_098069_2023-09-14_final
2023-09-15 10:49:27	ga_ls8c_ard_3-2-1_105075_2023-09-15_final
2023-09-20 11:07:13	ga_ls8c_ard_3-2-1_108073_2023-09-20_final
2023-09-29 09:27:47	ga_ls8c_ard_3-2-1_091087_2023-09-28_final
2023-10-06 11:06:27	ga_ls8c_ard_3-2-1_108071_2023-10-06_final
2023-10-07 10:10:51	ga_ls8c_ard_3-2-1_099071_2023-10-07_final
2023-10-12 10:33:25	ga_ls8c_ard_3-2-1_102081_2023-10-12_final
2023-10-15 09:23:27	ga_ls8c_ard_3-2-1_091076_2023-10-14_final
2023-11-05 11:23:18	ga_ls8c_ard_3-2-1_110082_2023-11-05_final
2023-11-17 10:04:21	ga_ls8c_ard_3-2-1_098070_2023-11-17_final
2023-11-18 10:48:49	ga_ls8c_ard_3-2-1_105073_2023-11-18_final
2023-12-04 10:52:44	ga_ls8c_ard_3-2-1_105083_2023-12-04_final
2023-12-05 11:31:59	ga_ls8c_ard_3-2-1_112073_2023-12-05_final
2023-12-06 10:39:32	ga_ls8c_ard_3-2-1_103081_2023-12-06_final
2023-12-20 09:12:44	ga_ls8c_ard_3-2-1_089080_2023-12-19_final
2023-12-23 11:20:07	ga_ls8c_ard_3-2-1_110074_2023-12-23_final
2023-12-28 10:04:08	ga_ls8c_ard_3-2-1_097085_2023-12-28_final
2024-01-03 09:28:58	ga_ls8c_ard_3-2-1_091090_2024-01-02_final
2024-01-05 10:46:17	ga_ls8c_ard_3-2-1_105067_2024-01-05_final
2024-01-07 10:34:20	ga_ls8c_ard_3-2-1_103068_2024-01-07_final
2024-01-08 11:19:12	ga_ls8c_ard_3-2-1_110072_2024-01-08_final
2024-01-19 09:24:11	ga_ls8c_ard_3-2-1_091078_2024-01-18_final
2024-02-27 09:29:04	ga_ls8c_ard_3-2-1_092075_2024-02-26_final
2024-03-02 10:43:59	ga_ls8c_ard_3-2-1_104077_2024-03-02_final
2024-03-07 11:01:37	ga_ls8c_ard_3-2-1_107075_2024-03-07_final
2024-03-16 09:21:18	ga_ls8c_ard_3-2-1_090087_2024-03-15_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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