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
2022-01-14 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-01-14_final
2022-10-05 10:54:12	ga_ls8c_ard_3-2-1_106070_2022-10-05_final
2022-10-08 09:51:46	ga_ls8c_ard_3-2-1_095084_2022-10-08_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2022-10-24 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-10-24_final
2022-10-25 10:29:53	ga_ls8c_ard_3-2-1_102071_2022-10-25_final
2022-10-29 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-10-29_final
2022-10-30 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-10-29_final
2022-10-30 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-10-30_final
2022-11-06 10:56:37	ga_ls8c_ard_3-2-1_106076_2022-11-06_final
2022-11-12 10:18:17	ga_ls8c_ard_3-2-1_100073_2022-11-12_final
2022-11-13 11:04:20	ga_ls8c_ard_3-2-1_107080_2022-11-13_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-11-19 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-11-19_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-13 11:13:02	ga_ls8c_ard_3-2-1_109071_2022-12-13_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-25 11:42:26	ga_ls8c_ard_3-2-1_113083_2022-12-25_final
2022-12-26 10:41:13	ga_ls8c_ard_3-2-1_104069_2022-12-26_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2023-01-06 10:25:53	ga_ls8c_ard_3-2-1_101077_2023-01-06_final
2023-01-09 09:18:41	ga_ls8c_ard_3-2-1_090079_2023-01-08_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-12 09:52:21	ga_ls8c_ard_3-2-1_095086_2023-01-12_final
2023-01-18 10:49:41	ga_ls8c_ard_3-2-1_105075_2023-01-18_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-22 10:26:13	ga_ls8c_ard_3-2-1_101078_2023-01-22_final
2023-01-30 11:12:55	ga_ls8c_ard_3-2-1_109071_2023-01-30_final
2023-02-06 11:18:41	ga_ls8c_ard_3-2-1_110070_2023-02-06_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-17 09:25:07	ga_ls8c_ard_3-2-1_091080_2023-02-16_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-02-25 10:15:58	ga_ls8c_ard_3-2-1_099084_2023-02-25_final
2023-03-07 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-03-07_final
2023-03-10 11:19:05	ga_ls8c_ard_3-2-1_110072_2023-03-10_final
2023-03-13 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-03-13_final
2023-03-15 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-03-15_final
2023-03-15 11:38:24	ga_ls8c_ard_3-2-1_113074_2023-03-15_final
2023-03-22 11:44:53	ga_ls8c_ard_3-2-1_114075_2023-03-22_final
2023-03-27 10:25:42	ga_ls8c_ard_3-2-1_101078_2023-03-27_final
2023-04-04 11:12:15	ga_ls8c_ard_3-2-1_109071_2023-04-04_final
2023-04-06 09:28:33	ga_ls8c_ard_3-2-1_091090_2023-04-05_final
2023-05-07 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-05-07_final
2023-05-14 10:24:22	ga_ls8c_ard_3-2-1_101076_2023-05-14_final
2023-05-16 11:51:40	ga_ls8c_ard_3-2-1_115078_2023-05-16_final
2023-05-17 10:55:14	ga_ls8c_ard_3-2-1_106076_2023-05-17_final
2023-05-18 10:00:49	ga_ls8c_ard_3-2-1_097079_2023-05-18_final
2023-05-22 11:13:25	ga_ls8c_ard_3-2-1_109075_2023-05-22_final
2023-05-26 09:15:49	ga_ls8c_ard_3-2-1_089090_2023-05-25_final
2023-05-30 10:26:47	ga_ls8c_ard_3-2-1_101082_2023-05-30_final
2023-06-10 10:07:09	ga_ls8c_ard_3-2-1_098079_2023-06-10_final
2023-06-12 09:51:37	ga_ls8c_ard_3-2-1_096071_2023-06-12_final
2023-06-17 10:10:35	ga_ls8c_ard_3-2-1_099072_2023-06-17_final
2023-06-20 10:41:54	ga_ls8c_ard_3-2-1_104073_2023-06-20_final
2023-06-21 11:29:09	ga_ls8c_ard_3-2-1_111083_2023-06-21_final
2023-06-26 10:04:04	ga_ls8c_ard_3-2-1_098071_2023-06-26_final
2023-07-02 09:28:41	ga_ls8c_ard_3-2-1_092075_2023-07-01_final
2023-07-14 11:35:10	ga_ls8c_ard_3-2-1_112082_2023-07-14_final
2023-07-18 09:32:45	ga_ls8c_ard_3-2-1_092085_2023-07-18_final
2023-07-27 11:01:09	ga_ls8c_ard_3-2-1_107074_2023-07-27_final
2023-07-29 09:12:44	ga_ls8c_ard_3-2-1_089081_2023-07-28_final
2023-08-01 09:40:28	ga_ls8c_ard_3-2-1_094073_2023-08-01_final
2023-08-02 10:25:44	ga_ls8c_ard_3-2-1_101078_2023-08-02_final
2023-08-03 11:07:00	ga_ls8c_ard_3-2-1_108073_2023-08-03_final
2023-08-05 10:53:27	ga_ls8c_ard_3-2-1_106070_2023-08-05_final
2023-08-07 10:42:17	ga_ls8c_ard_3-2-1_104073_2023-08-07_final
2023-08-08 09:46:40	ga_ls8c_ard_3-2-1_095073_2023-08-08_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-30 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-08-30_final
2023-09-04 11:07:07	ga_ls8c_ard_3-2-1_108073_2023-09-04_final
2023-09-12 10:16:56	ga_ls8c_ard_3-2-1_100071_2023-09-12_final
2023-09-13 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-09-13_final
2023-09-15 09:11:22	ga_ls8c_ard_3-2-1_089077_2023-09-14_final
2023-09-22 10:53:15	ga_ls8c_ard_3-2-1_106069_2023-09-22_final
2023-10-01 10:47:08	ga_ls8c_ard_3-2-1_105069_2023-10-01_final
2023-10-08 09:21:14	ga_ls8c_ard_3-2-1_090086_2023-10-07_final
2023-10-11 11:30:14	ga_ls8c_ard_3-2-1_111084_2023-10-11_final
2023-10-17 09:13:04	ga_ls8c_ard_3-2-1_089081_2023-10-16_final
2023-10-22 11:06:31	ga_ls8c_ard_3-2-1_108071_2023-10-22_final
2023-10-24 10:54:58	ga_ls8c_ard_3-2-1_106073_2023-10-24_final
2023-10-25 10:01:45	ga_ls8c_ard_3-2-1_097079_2023-10-25_final
2023-10-26 10:42:38	ga_ls8c_ard_3-2-1_104073_2023-10-26_final
2023-10-30 10:18:19	ga_ls8c_ard_3-2-1_100074_2023-10-30_final
2023-10-31 09:23:54	ga_ls8c_ard_3-2-1_091077_2023-10-30_final
2023-10-31 09:27:05	ga_ls8c_ard_3-2-1_091085_2023-10-30_final
2023-11-01 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-01_final
2023-11-05 09:46:24	ga_ls8c_ard_3-2-1_094087_2023-11-05_final
2023-11-12 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-11-12_final
2023-11-13 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-11-13_final
2023-11-17 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-17_final
2023-11-19 09:52:25	ga_ls8c_ard_3-2-1_096071_2023-11-19_final
2023-11-22 10:25:20	ga_ls8c_ard_3-2-1_101076_2023-11-22_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