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:

Add field

First 100 results (query limit)

Time (local)	Label
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-08-07 09:38:54	ga_ls8c_ard_3-2-1_093083_2022-08-07_final
2022-08-26 10:03:53	ga_ls8c_ard_3-2-1_098068_2022-08-26_final
2022-08-26 10:04:17	ga_ls8c_ard_3-2-1_098069_2022-08-26_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-09-03 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-09-03_final
2022-09-08 11:15:06	ga_ls8c_ard_3-2-1_109076_2022-09-08_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-17 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-09-17_final
2022-09-28 09:14:45	ga_ls8c_ard_3-2-1_089084_2022-09-27_final
2022-10-06 09:58:10	ga_ls8c_ard_3-2-1_097069_2022-10-06_final
2022-10-06 10:01:45	ga_ls8c_ard_3-2-1_097078_2022-10-06_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-11 10:21:26	ga_ls8c_ard_3-2-1_100081_2022-10-11_final
2022-10-29 10:08:22	ga_ls8c_ard_3-2-1_098079_2022-10-29_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-05 11:53:50	ga_ls8c_ard_3-2-1_115080_2022-11-05_final
2022-11-13 09:24:15	ga_ls8c_ard_3-2-1_091077_2022-11-12_final
2022-11-13 09:28:15	ga_ls8c_ard_3-2-1_091087_2022-11-12_final
2022-11-18 11:19:37	ga_ls8c_ard_3-2-1_110072_2022-11-18_final
2022-11-20 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-11-20_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-12-01 10:49:10	ga_ls8c_ard_3-2-1_105073_2022-12-01_final
2022-12-02 11:36:01	ga_ls8c_ard_3-2-1_112082_2022-12-02_final
2022-12-04 11:19:16	ga_ls8c_ard_3-2-1_110071_2022-12-04_final
2022-12-07 11:52:09	ga_ls8c_ard_3-2-1_115076_2022-12-07_final
2022-12-11 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-12-11_final
2022-12-13 11:14:14	ga_ls8c_ard_3-2-1_109074_2022-12-13_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-25 11:42:26	ga_ls8c_ard_3-2-1_113083_2022-12-25_final
2023-01-07 11:06:45	ga_ls8c_ard_3-2-1_108071_2023-01-07_final
2023-01-09 09:21:29	ga_ls8c_ard_3-2-1_090086_2023-01-08_final
2023-01-09 09:21:53	ga_ls8c_ard_3-2-1_090087_2023-01-08_final
2023-01-09 09:23:05	ga_ls8c_ard_3-2-1_090090_2023-01-08_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-18 09:16:23	ga_ls8c_ard_3-2-1_089089_2023-01-17_final
2023-01-22 10:25:49	ga_ls8c_ard_3-2-1_101077_2023-01-22_final
2023-01-23 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-01-23_final
2023-01-31 11:58:34	ga_ls8c_ard_3-2-1_116077_2023-01-31_final
2023-02-08 11:07:54	ga_ls8c_ard_3-2-1_108074_2023-02-08_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-02-18 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-02-18_final
2023-02-19 09:13:07	ga_ls8c_ard_3-2-1_089081_2023-02-18_final
2023-02-19 09:13:31	ga_ls8c_ard_3-2-1_089082_2023-02-18_final
2023-02-19 10:47:36	ga_ls8c_ard_3-2-1_105070_2023-02-19_final
2023-02-20 09:53:33	ga_ls8c_ard_3-2-1_096074_2023-02-20_final
2023-02-26 10:55:14	ga_ls8c_ard_3-2-1_106074_2023-02-26_final
2023-03-01 09:52:03	ga_ls8c_ard_3-2-1_095086_2023-03-01_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-12 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-03-12_final
2023-03-12 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-03-12_final
2023-03-13 11:52:47	ga_ls8c_ard_3-2-1_115079_2023-03-13_final
2023-03-18 10:30:00	ga_ls8c_ard_3-2-1_102073_2023-03-18_final
2023-03-21 09:28:45	ga_ls8c_ard_3-2-1_091090_2023-03-20_final
2023-03-23 09:16:21	ga_ls8c_ard_3-2-1_089090_2023-03-22_final
2023-03-23 10:49:15	ga_ls8c_ard_3-2-1_105075_2023-03-23_final
2023-03-27 10:22:55	ga_ls8c_ard_3-2-1_101071_2023-03-27_final
2023-03-28 09:32:52	ga_ls8c_ard_3-2-1_092085_2023-03-28_final
2023-03-31 09:57:21	ga_ls8c_ard_3-2-1_097069_2023-03-31_final
2023-04-04 11:14:39	ga_ls8c_ard_3-2-1_109077_2023-04-04_final
2023-04-09 09:51:48	ga_ls8c_ard_3-2-1_096071_2023-04-09_final
2023-04-16 09:57:31	ga_ls8c_ard_3-2-1_097070_2023-04-16_final
2023-04-20 09:39:32	ga_ls8c_ard_3-2-1_093087_2023-04-20_final
2023-04-30 11:50:41	ga_ls8c_ard_3-2-1_115075_2023-04-30_final
2023-05-03 09:05:47	ga_ls8c_ard_3-2-1_088080_2023-05-02_final
2023-05-10 09:15:51	ga_ls8c_ard_3-2-1_089090_2023-05-09_final
2023-05-16 11:52:28	ga_ls8c_ard_3-2-1_115080_2023-05-16_final
2023-05-24 09:26:58	ga_ls8c_ard_3-2-1_091087_2023-05-23_final
2023-06-10 10:04:22	ga_ls8c_ard_3-2-1_098072_2023-06-10_final
2023-06-10 10:06:22	ga_ls8c_ard_3-2-1_098077_2023-06-10_final
2023-06-10 11:46:26	ga_ls8c_ard_3-2-1_114080_2023-06-10_final
2023-06-14 11:23:21	ga_ls8c_ard_3-2-1_110084_2023-06-14_final
2023-06-21 09:49:52	ga_ls8c_ard_3-2-1_095082_2023-06-21_final
2023-06-27 09:11:40	ga_ls8c_ard_3-2-1_089079_2023-06-26_final
2023-07-14 11:35:10	ga_ls8c_ard_3-2-1_112082_2023-07-14_final
2023-07-18 11:11:14	ga_ls8c_ard_3-2-1_108084_2023-07-18_final
2023-07-19 10:14:01	ga_ls8c_ard_3-2-1_099080_2023-07-19_final
2023-07-23 09:46:08	ga_ls8c_ard_3-2-1_095072_2023-07-23_final
2023-08-03 09:33:18	ga_ls8c_ard_3-2-1_092086_2023-08-03_final
2023-08-05 09:17:21	ga_ls8c_ard_3-2-1_090077_2023-08-04_final
2023-08-07 10:45:53	ga_ls8c_ard_3-2-1_104082_2023-08-07_final
2023-08-12 11:01:38	ga_ls8c_ard_3-2-1_107075_2023-08-12_final
2023-08-14 10:52:06	ga_ls8c_ard_3-2-1_105082_2023-08-14_final
2023-08-17 09:44:33	ga_ls8c_ard_3-2-1_094083_2023-08-17_final
2023-08-20 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-08-20_final
2023-08-28 09:28:52	ga_ls8c_ard_3-2-1_091090_2023-08-27_final
2023-08-29 10:06:56	ga_ls8c_ard_3-2-1_098077_2023-08-29_final
2023-09-04 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-09-04_final
2023-09-06 09:21:03	ga_ls8c_ard_3-2-1_090086_2023-09-05_final
2023-09-15 09:14:58	ga_ls8c_ard_3-2-1_089086_2023-09-14_final
2023-11-16 09:27:04	ga_ls8c_ard_3-2-1_091085_2023-11-15_final
2023-11-17 10:04:21	ga_ls8c_ard_3-2-1_098070_2023-11-17_final
2023-11-27 10:42:40	ga_ls8c_ard_3-2-1_104073_2023-11-27_final
2023-12-01 10:22:18	ga_ls8c_ard_3-2-1_100084_2023-12-01_final
2023-12-05 09:52:18	ga_ls8c_ard_3-2-1_096071_2023-12-05_final
2024-02-20 09:26:56	ga_ls8c_ard_3-2-1_091085_2024-02-19_final
2024-02-25 11:20:20	ga_ls8c_ard_3-2-1_110075_2024-02-25_final
2024-03-02 10:41:59	ga_ls8c_ard_3-2-1_104072_2024-03-02_final
2024-03-16 09:22:30	ga_ls8c_ard_3-2-1_090090_2024-03-15_nrt

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