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
2022-09-27 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-09-27_final
2022-10-03 09:35:16	ga_ls8c_ard_3-2-1_092089_2022-10-03_final
2022-10-04 11:53:49	ga_ls8c_ard_3-2-1_115080_2022-10-04_final
2022-10-13 10:05:03	ga_ls8c_ard_3-2-1_098071_2022-10-13_final
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-19 11:06:07	ga_ls8c_ard_3-2-1_108069_2022-10-19_final
2022-10-20 10:13:17	ga_ls8c_ard_3-2-1_099076_2022-10-20_final
2022-10-21 09:22:04	ga_ls8c_ard_3-2-1_090087_2022-10-20_final
2022-10-22 09:58:33	ga_ls8c_ard_3-2-1_097070_2022-10-22_final
2022-10-26 11:13:09	ga_ls8c_ard_3-2-1_109071_2022-10-26_final
2022-10-27 10:21:55	ga_ls8c_ard_3-2-1_100082_2022-10-27_final
2022-10-28 09:25:06	ga_ls8c_ard_3-2-1_091079_2022-10-27_final
2022-10-29 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-10-29_final
2022-10-30 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-10-29_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-05 10:13:22	ga_ls8c_ard_3-2-1_099076_2022-11-05_final
2022-11-05 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-11-05_final
2022-11-06 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-11-05_final
2022-11-09 11:27:06	ga_ls8c_ard_3-2-1_111075_2022-11-09_final
2022-11-11 09:35:50	ga_ls8c_ard_3-2-1_093075_2022-11-11_final
2022-11-13 09:25:03	ga_ls8c_ard_3-2-1_091079_2022-11-12_final
2022-11-13 11:03:56	ga_ls8c_ard_3-2-1_107079_2022-11-13_final
2022-11-14 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-14_final
2022-11-15 09:12:16	ga_ls8c_ard_3-2-1_089078_2022-11-14_final
2022-11-15 10:52:45	ga_ls8c_ard_3-2-1_105082_2022-11-15_final
2022-11-16 09:53:55	ga_ls8c_ard_3-2-1_096074_2022-11-16_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-11-18 11:24:00	ga_ls8c_ard_3-2-1_110083_2022-11-18_final
2022-11-18 11:24:24	ga_ls8c_ard_3-2-1_110084_2022-11-18_final
2022-11-23 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-11-23_final
2022-11-23 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-11-23_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2022-11-29 09:25:50	ga_ls8c_ard_3-2-1_091081_2022-11-28_final
2022-11-29 09:28:38	ga_ls8c_ard_3-2-1_091088_2022-11-28_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-08 09:18:51	ga_ls8c_ard_3-2-1_090079_2022-12-07_final
2022-12-09 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-12-09_final
2022-12-09 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-12-09_final
2022-12-11 11:30:36	ga_ls8c_ard_3-2-1_111084_2022-12-11_final
2022-12-13 09:34:33	ga_ls8c_ard_3-2-1_093072_2022-12-13_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-20 11:23:31	ga_ls8c_ard_3-2-1_110082_2022-12-20_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-25 09:59:33	ga_ls8c_ard_3-2-1_097073_2022-12-25_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-08 10:13:07	ga_ls8c_ard_3-2-1_099076_2023-01-08_final
2023-01-09 10:53:35	ga_ls8c_ard_3-2-1_106069_2023-01-09_final
2023-01-10 09:59:57	ga_ls8c_ard_3-2-1_097074_2023-01-10_final
2023-01-10 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-10_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-20 10:37:45	ga_ls8c_ard_3-2-1_103076_2023-01-20_final
2023-01-26 09:59:08	ga_ls8c_ard_3-2-1_097072_2023-01-26_final
2023-02-01 09:25:39	ga_ls8c_ard_3-2-1_091081_2023-01-31_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-19 09:13:07	ga_ls8c_ard_3-2-1_089081_2023-02-18_final
2023-02-19 10:46:48	ga_ls8c_ard_3-2-1_105068_2023-02-19_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-20 09:52:45	ga_ls8c_ard_3-2-1_096072_2023-02-20_final
2023-02-26 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-02-25_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-07 10:47:24	ga_ls8c_ard_3-2-1_105070_2023-03-07_final
2023-03-10 11:19:05	ga_ls8c_ard_3-2-1_110072_2023-03-10_final
2023-03-12 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-03-12_final
2023-03-12 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-03-12_final
2023-03-13 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-03-13_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-03-14 10:53:09	ga_ls8c_ard_3-2-1_106069_2023-03-14_final
2023-03-16 10:41:35	ga_ls8c_ard_3-2-1_104071_2023-03-16_final
2023-03-22 10:06:24	ga_ls8c_ard_3-2-1_098076_2023-03-22_final
2023-03-26 11:22:32	ga_ls8c_ard_3-2-1_110081_2023-03-26_final
2023-03-29 10:13:20	ga_ls8c_ard_3-2-1_099078_2023-03-29_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-03-31 11:41:26	ga_ls8c_ard_3-2-1_113082_2023-03-31_final
2023-04-05 10:17:00	ga_ls8c_ard_3-2-1_100072_2023-04-05_final
2023-04-07 10:06:12	ga_ls8c_ard_3-2-1_098076_2023-04-07_final
2023-04-07 10:07:00	ga_ls8c_ard_3-2-1_098078_2023-04-07_final
2023-04-07 11:46:17	ga_ls8c_ard_3-2-1_114079_2023-04-07_final
2023-04-14 10:10:41	ga_ls8c_ard_3-2-1_099072_2023-04-14_final
2023-04-14 10:12:17	ga_ls8c_ard_3-2-1_099076_2023-04-14_final
2023-04-14 11:51:34	ga_ls8c_ard_3-2-1_115077_2023-04-14_final
2023-04-15 09:18:39	ga_ls8c_ard_3-2-1_090081_2023-04-14_final
2023-04-20 11:12:02	ga_ls8c_ard_3-2-1_109071_2023-04-20_final
2023-04-24 10:51:43	ga_ls8c_ard_3-2-1_105082_2023-04-24_final
2023-04-24 10:52:07	ga_ls8c_ard_3-2-1_105083_2023-04-24_final
2023-04-27 11:17:49	ga_ls8c_ard_3-2-1_110070_2023-04-27_final
2023-05-01 09:22:10	ga_ls8c_ard_3-2-1_090090_2023-04-30_final
2023-05-03 10:45:28	ga_ls8c_ard_3-2-1_104082_2023-05-03_final
2023-05-06 09:34:15	ga_ls8c_ard_3-2-1_093074_2023-05-06_final
2023-05-06 09:38:39	ga_ls8c_ard_3-2-1_093085_2023-05-06_final
2023-05-09 11:44:47	ga_ls8c_ard_3-2-1_114076_2023-05-09_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-16 10:10:23	ga_ls8c_ard_3-2-1_099072_2023-05-16_final
2023-05-17 09:19:33	ga_ls8c_ard_3-2-1_090084_2023-05-16_final
2023-05-17 09:21:33	ga_ls8c_ard_3-2-1_090089_2023-05-16_final
2023-05-17 10:54:50	ga_ls8c_ard_3-2-1_106075_2023-05-17_final
2023-05-22 11:11:25	ga_ls8c_ard_3-2-1_109070_2023-05-22_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