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
2022-06-15 09:17:40	ga_ls8c_ard_3-2-1_090077_2022-06-14_final
2022-06-17 09:07:43	ga_ls8c_ard_3-2-1_088083_2022-06-16_final
2022-07-05 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-07-05_final
2022-07-10 09:11:33	ga_ls8c_ard_3-2-1_089077_2022-07-09_final
2022-07-18 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-18_final
2022-07-19 10:42:42	ga_ls8c_ard_3-2-1_104073_2022-07-19_final
2022-07-20 11:25:58	ga_ls8c_ard_3-2-1_111073_2022-07-20_final
2022-07-25 10:04:54	ga_ls8c_ard_3-2-1_098071_2022-07-25_final
2022-07-26 09:16:28	ga_ls8c_ard_3-2-1_089089_2022-07-25_final
2022-07-29 09:46:36	ga_ls8c_ard_3-2-1_094087_2022-07-29_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-08-07 09:40:30	ga_ls8c_ard_3-2-1_093087_2022-08-07_final
2022-08-11 09:16:37	ga_ls8c_ard_3-2-1_089089_2022-08-10_final
2022-08-18 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-08-17_final
2022-08-21 11:24:14	ga_ls8c_ard_3-2-1_111068_2022-08-21_final
2022-08-21 11:30:13	ga_ls8c_ard_3-2-1_111083_2022-08-21_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-08-25 09:29:00	ga_ls8c_ard_3-2-1_091089_2022-08-24_final
2022-08-30 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-30_final
2022-08-30 11:19:38	ga_ls8c_ard_3-2-1_110072_2022-08-30_final
2022-09-02 10:14:27	ga_ls8c_ard_3-2-1_099079_2022-09-02_final
2022-09-03 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-09-02_final
2022-09-04 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-09-04_final
2022-09-08 09:34:37	ga_ls8c_ard_3-2-1_093072_2022-09-08_final
2022-09-08 09:35:01	ga_ls8c_ard_3-2-1_093073_2022-09-08_final
2022-09-13 11:36:05	ga_ls8c_ard_3-2-1_112082_2022-09-13_final
2022-09-17 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-09-16_final
2022-09-17 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-09-17_final
2022-09-19 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-09-18_final
2022-09-24 11:12:47	ga_ls8c_ard_3-2-1_109070_2022-09-24_final
2022-09-28 09:12:46	ga_ls8c_ard_3-2-1_089079_2022-09-27_final
2022-09-29 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-09-29_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-09 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-10-09_final
2022-10-14 09:11:01	ga_ls8c_ard_3-2-1_089075_2022-10-13_final
2022-10-16 10:36:22	ga_ls8c_ard_3-2-1_103072_2022-10-16_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-17 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-10-17_final
2022-10-22 09:57:45	ga_ls8c_ard_3-2-1_097068_2022-10-22_final
2022-10-22 11:42:14	ga_ls8c_ard_3-2-1_113082_2022-10-22_final
2022-10-25 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-10-25_final
2022-10-25 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-10-25_final
2022-10-28 09:25:30	ga_ls8c_ard_3-2-1_091080_2022-10-27_final
2022-10-30 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-10-29_final
2022-10-30 09:17:09	ga_ls8c_ard_3-2-1_089090_2022-10-29_final
2022-10-30 10:48:27	ga_ls8c_ard_3-2-1_105071_2022-10-30_final
2022-10-31 09:57:13	ga_ls8c_ard_3-2-1_096082_2022-10-31_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-06 09:23:19	ga_ls8c_ard_3-2-1_090090_2022-11-05_final
2022-11-11 09:34:38	ga_ls8c_ard_3-2-1_093072_2022-11-11_final
2022-11-13 11:00:45	ga_ls8c_ard_3-2-1_107071_2022-11-13_final
2022-11-13 11:01:56	ga_ls8c_ard_3-2-1_107074_2022-11-13_final
2022-11-15 09:12:16	ga_ls8c_ard_3-2-1_089078_2022-11-14_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-11-22 10:54:08	ga_ls8c_ard_3-2-1_106070_2022-11-22_final
2022-11-29 09:27:50	ga_ls8c_ard_3-2-1_091086_2022-11-28_final
2022-11-29 09:28:14	ga_ls8c_ard_3-2-1_091087_2022-11-28_final
2022-12-01 10:52:46	ga_ls8c_ard_3-2-1_105082_2022-12-01_final
2022-12-11 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-12-11_final
2022-12-13 11:12:38	ga_ls8c_ard_3-2-1_109070_2022-12-13_final
2022-12-18 09:58:37	ga_ls8c_ard_3-2-1_096086_2022-12-18_final
2022-12-23 11:51:59	ga_ls8c_ard_3-2-1_115076_2022-12-23_final
2022-12-29 11:18:08	ga_ls8c_ard_3-2-1_109084_2022-12-29_final
2023-01-08 10:11:55	ga_ls8c_ard_3-2-1_099073_2023-01-08_final
2023-01-08 10:15:07	ga_ls8c_ard_3-2-1_099081_2023-01-08_final
2023-01-14 11:14:51	ga_ls8c_ard_3-2-1_109076_2023-01-14_final
2023-01-18 10:49:17	ga_ls8c_ard_3-2-1_105074_2023-01-18_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-24 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-01-24_final
2023-01-25 10:55:09	ga_ls8c_ard_3-2-1_106073_2023-01-25_final
2023-02-01 09:24:52	ga_ls8c_ard_3-2-1_091079_2023-01-31_final
2023-02-07 10:27:50	ga_ls8c_ard_3-2-1_101082_2023-02-07_final
2023-02-09 10:13:52	ga_ls8c_ard_3-2-1_099078_2023-02-09_final
2023-02-10 09:21:25	ga_ls8c_ard_3-2-1_090086_2023-02-09_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-24 11:11:13	ga_ls8c_ard_3-2-1_108083_2023-02-24_final
2023-02-26 09:17:57	ga_ls8c_ard_3-2-1_090078_2023-02-25_final
2023-02-26 10:54:26	ga_ls8c_ard_3-2-1_106072_2023-02-26_final
2023-02-26 10:54:50	ga_ls8c_ard_3-2-1_106073_2023-02-26_final
2023-03-07 09:11:19	ga_ls8c_ard_3-2-1_089077_2023-03-06_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_final
2023-03-12 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-03-12_final
2023-03-14 09:21:04	ga_ls8c_ard_3-2-1_090086_2023-03-13_final
2023-03-22 10:04:01	ga_ls8c_ard_3-2-1_098070_2023-03-22_final
2023-03-24 09:52:01	ga_ls8c_ard_3-2-1_096071_2023-03-24_final
2023-03-26 11:18:56	ga_ls8c_ard_3-2-1_110072_2023-03-26_final
2023-03-29 10:15:19	ga_ls8c_ard_3-2-1_099083_2023-03-29_final
2023-04-02 11:25:51	ga_ls8c_ard_3-2-1_111074_2023-04-02_final
2023-04-16 10:03:30	ga_ls8c_ard_3-2-1_097085_2023-04-16_final
2023-04-16 11:37:59	ga_ls8c_ard_3-2-1_113074_2023-04-16_final
2023-04-24 09:12:26	ga_ls8c_ard_3-2-1_089081_2023-04-23_final
2023-04-24 10:46:56	ga_ls8c_ard_3-2-1_105070_2023-04-24_final
2023-05-03 09:06:35	ga_ls8c_ard_3-2-1_088082_2023-05-02_final
2023-05-05 10:32:17	ga_ls8c_ard_3-2-1_102080_2023-05-05_final
2023-05-06 11:11:32	ga_ls8c_ard_3-2-1_109070_2023-05-06_final
2023-05-12 10:35:09	ga_ls8c_ard_3-2-1_103072_2023-05-12_final
2023-05-16 10:13:11	ga_ls8c_ard_3-2-1_099079_2023-05-16_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