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
2022-08-23 09:34:35	ga_ls8c_ard_3-2-1_093072_2022-08-23_final
2022-09-04 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-09-04_final
2022-09-15 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-09-15_final
2022-09-19 09:17:45	ga_ls8c_ard_3-2-1_090076_2022-09-18_final
2022-09-19 09:22:32	ga_ls8c_ard_3-2-1_090088_2022-09-18_final
2022-10-08 09:52:10	ga_ls8c_ard_3-2-1_095085_2022-10-08_final
2022-11-02 09:40:52	ga_ls8c_ard_3-2-1_094072_2022-11-02_final
2022-11-05 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-11-05_final
2022-11-18 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-11-18_final
2022-11-21 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-11-21_final
2022-11-21 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-11-21_final
2022-11-22 10:57:43	ga_ls8c_ard_3-2-1_106079_2022-11-22_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-07 11:51:45	ga_ls8c_ard_3-2-1_115075_2022-12-07_final
2022-12-09 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-12-09_final
2022-12-14 11:59:05	ga_ls8c_ard_3-2-1_116078_2022-12-14_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-25 11:42:26	ga_ls8c_ard_3-2-1_113083_2022-12-25_final
2022-12-29 09:40:50	ga_ls8c_ard_3-2-1_093088_2022-12-29_final
2023-01-02 09:13:44	ga_ls8c_ard_3-2-1_089082_2023-01-01_final
2023-01-10 09:59:33	ga_ls8c_ard_3-2-1_097073_2023-01-10_final
2023-01-18 09:12:47	ga_ls8c_ard_3-2-1_089080_2023-01-17_final
2023-01-22 10:25:49	ga_ls8c_ard_3-2-1_101077_2023-01-22_final
2023-01-24 10:10:41	ga_ls8c_ard_3-2-1_099070_2023-01-24_final
2023-01-30 11:12:55	ga_ls8c_ard_3-2-1_109071_2023-01-30_final
2023-02-01 09:28:51	ga_ls8c_ard_3-2-1_091089_2023-01-31_final
2023-02-03 09:12:30	ga_ls8c_ard_3-2-1_089079_2023-02-02_final
2023-02-03 09:12:54	ga_ls8c_ard_3-2-1_089080_2023-02-02_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-03-01 11:25:21	ga_ls8c_ard_3-2-1_111072_2023-03-01_final
2023-03-08 09:52:10	ga_ls8c_ard_3-2-1_096071_2023-03-08_final
2023-03-11 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-03-11_final
2023-03-12 09:34:38	ga_ls8c_ard_3-2-1_092089_2023-03-12_final
2023-03-19 11:12:03	ga_ls8c_ard_3-2-1_109070_2023-03-19_final
2023-03-22 10:03:13	ga_ls8c_ard_3-2-1_098068_2023-03-22_final
2023-03-22 10:07:36	ga_ls8c_ard_3-2-1_098079_2023-03-22_final
2023-03-30 09:18:06	ga_ls8c_ard_3-2-1_090079_2023-03-29_final
2023-03-30 10:58:11	ga_ls8c_ard_3-2-1_106082_2023-03-30_final
2023-04-01 09:06:31	ga_ls8c_ard_3-2-1_088081_2023-03-31_final
2023-04-05 10:18:36	ga_ls8c_ard_3-2-1_100076_2023-04-05_final
2023-04-07 10:04:12	ga_ls8c_ard_3-2-1_098071_2023-04-07_final
2023-04-09 09:57:47	ga_ls8c_ard_3-2-1_096086_2023-04-09_final
2023-04-29 11:05:26	ga_ls8c_ard_3-2-1_108070_2023-04-29_final
2023-05-03 09:05:47	ga_ls8c_ard_3-2-1_088080_2023-05-02_final
2023-05-08 09:24:15	ga_ls8c_ard_3-2-1_091080_2023-05-07_final
2023-05-17 09:21:09	ga_ls8c_ard_3-2-1_090088_2023-05-16_final
2023-05-19 10:41:41	ga_ls8c_ard_3-2-1_104073_2023-05-19_final
2023-05-23 10:18:12	ga_ls8c_ard_3-2-1_100076_2023-05-23_final
2023-05-26 09:11:01	ga_ls8c_ard_3-2-1_089078_2023-05-25_final
2023-05-27 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-27_final
2023-06-02 09:21:12	ga_ls8c_ard_3-2-1_090088_2023-06-01_final
2023-06-04 10:41:46	ga_ls8c_ard_3-2-1_104073_2023-06-04_final
2023-06-08 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-06-08_final
2023-06-09 11:01:10	ga_ls8c_ard_3-2-1_107075_2023-06-09_final
2023-06-10 10:06:45	ga_ls8c_ard_3-2-1_098078_2023-06-10_final
2023-06-17 11:51:28	ga_ls8c_ard_3-2-1_115077_2023-06-17_final
2023-06-18 09:18:34	ga_ls8c_ard_3-2-1_090081_2023-06-17_final
2023-06-18 09:21:21	ga_ls8c_ard_3-2-1_090088_2023-06-17_final
2023-06-19 09:56:14	ga_ls8c_ard_3-2-1_097067_2023-06-19_final
2023-06-30 09:39:49	ga_ls8c_ard_3-2-1_094072_2023-06-30_final
2023-07-09 11:12:13	ga_ls8c_ard_3-2-1_109071_2023-07-09_final
2023-07-19 11:52:06	ga_ls8c_ard_3-2-1_115078_2023-07-19_final
2023-07-20 09:17:59	ga_ls8c_ard_3-2-1_090079_2023-07-19_final
2023-07-20 09:18:47	ga_ls8c_ard_3-2-1_090081_2023-07-19_final
2023-07-22 10:42:09	ga_ls8c_ard_3-2-1_104073_2023-07-22_final
2023-07-28 10:04:21	ga_ls8c_ard_3-2-1_098071_2023-07-28_final
2023-07-30 11:31:41	ga_ls8c_ard_3-2-1_112073_2023-07-30_final
2023-08-11 10:18:45	ga_ls8c_ard_3-2-1_100076_2023-08-11_final
2023-08-13 10:04:26	ga_ls8c_ard_3-2-1_098071_2023-08-13_final
2023-08-13 11:46:30	ga_ls8c_ard_3-2-1_114079_2023-08-13_final
2023-08-14 09:12:25	ga_ls8c_ard_3-2-1_089080_2023-08-13_final
2023-08-14 09:16:24	ga_ls8c_ard_3-2-1_089090_2023-08-13_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-08-20 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-08-20_final
2023-08-28 09:24:53	ga_ls8c_ard_3-2-1_091080_2023-08-27_final
2023-08-29 10:03:21	ga_ls8c_ard_3-2-1_098068_2023-08-29_final
2023-09-01 10:35:50	ga_ls8c_ard_3-2-1_103072_2023-09-01_final
2023-09-11 09:40:03	ga_ls8c_ard_3-2-1_093087_2023-09-11_final
2023-09-15 09:12:34	ga_ls8c_ard_3-2-1_089080_2023-09-14_final
2023-09-15 09:13:22	ga_ls8c_ard_3-2-1_089082_2023-09-14_final
2023-09-19 10:25:33	ga_ls8c_ard_3-2-1_101077_2023-09-19_final
2023-09-21 10:09:36	ga_ls8c_ard_3-2-1_099068_2023-09-21_final
2023-09-29 09:25:00	ga_ls8c_ard_3-2-1_091080_2023-09-28_final
2023-09-30 10:03:28	ga_ls8c_ard_3-2-1_098068_2023-09-30_final
2023-10-02 11:31:36	ga_ls8c_ard_3-2-1_112072_2023-10-02_final
2023-10-03 10:35:58	ga_ls8c_ard_3-2-1_103072_2023-10-03_final
2023-10-05 10:25:36	ga_ls8c_ard_3-2-1_101077_2023-10-05_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-07 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-10-07_final
2023-10-07 11:53:20	ga_ls8c_ard_3-2-1_115080_2023-10-07_final
2023-10-23 11:51:47	ga_ls8c_ard_3-2-1_115076_2023-10-23_final
2023-10-23 11:52:35	ga_ls8c_ard_3-2-1_115078_2023-10-23_final
2023-10-25 11:42:14	ga_ls8c_ard_3-2-1_113083_2023-10-25_final
2023-11-08 11:52:09	ga_ls8c_ard_3-2-1_115077_2023-11-08_final
2023-11-08 11:52:33	ga_ls8c_ard_3-2-1_115078_2023-11-08_final
2023-11-14 11:17:30	ga_ls8c_ard_3-2-1_109083_2023-11-14_final
2023-11-16 09:25:05	ga_ls8c_ard_3-2-1_091080_2023-11-15_final
2023-11-16 09:26:40	ga_ls8c_ard_3-2-1_091084_2023-11-15_final
2023-11-19 09:52:01	ga_ls8c_ard_3-2-1_096070_2023-11-19_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