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
2021-07-10 09:40:56	ga_ls8c_ard_3-2-0_094074_2021-07-10_final
2021-07-11 10:24:35	ga_ls8c_ard_3-2-0_101075_2021-07-11_final
2021-08-04 11:15:00	ga_ls8c_ard_3-2-0_109077_2021-08-04_final
2021-08-05 11:58:40	ga_ls8c_ard_3-2-0_116078_2021-08-05_final
2021-08-08 09:14:37	ga_ls8c_ard_3-2-0_089085_2021-08-07_final
2021-08-08 10:51:54	ga_ls8c_ard_3-2-0_105081_2021-08-08_final
2021-08-10 10:35:10	ga_ls8c_ard_3-2-0_103070_2021-08-10_final
2021-08-22 09:23:51	ga_ls8c_ard_3-2-0_091077_2021-08-21_final
2021-08-31 09:20:31	ga_ls8c_ard_3-2-0_090084_2021-08-30_final
2021-09-06 11:58:50	ga_ls8c_ard_3-2-0_116078_2021-09-06_final
2021-09-09 09:14:23	ga_ls8c_ard_3-2-0_089084_2021-09-08_final
2021-09-11 10:38:31	ga_ls8c_ard_3-2-0_103078_2021-09-11_final
2021-09-15 11:51:05	ga_ls8c_ard_3-2-0_115074_2021-09-15_final
2021-09-23 09:29:10	ga_ls8c_ard_3-2-0_091090_2021-09-22_final
2021-10-03 10:02:43	ga_ls8c_ard_3-2-0_097081_2021-10-03_final
2021-10-11 10:52:12	ga_ls8c_ard_3-2-0_105081_2021-10-11_final
2021-10-14 09:46:38	ga_ls8c_ard_3-2-0_094087_2021-10-14_final
2021-10-26 10:07:46	ga_ls8c_ard_3-2-0_098078_2021-10-26_final
2021-10-30 09:42:39	ga_ls8c_ard_3-2-0_094077_2021-10-30_final
2021-10-30 09:44:15	ga_ls8c_ard_3-2-0_094081_2021-10-30_final
2021-10-30 11:23:56	ga_ls8c_ard_3-2-0_110083_2021-10-30_final
2021-11-15 09:42:34	ga_ls8c_ard_3-2-0_094077_2021-11-15_final
2021-11-17 09:30:12	ga_ls8c_ard_3-2-0_092077_2021-11-17_final
2021-11-20 10:01:53	ga_ls8c_ard_3-2-0_097079_2021-11-20_final
2021-12-14 10:48:33	ga_ls8c_ard_3-2-1_105072_2021-12-14_final
2021-12-17 09:45:21	ga_ls8c_ard_3-2-1_094084_2021-12-17_final
2021-12-20 10:11:51	ga_ls8c_ard_3-2-1_099073_2021-12-20_final
2021-12-31 09:56:49	ga_ls8c_ard_3-2-1_096082_2021-12-31_final
2022-01-04 09:31:18	ga_ls8c_ard_3-2-1_092080_2022-01-04_final
2022-02-13 10:18:35	ga_ls8c_ard_3-2-1_100075_2022-02-13_final
2022-02-19 09:45:03	ga_ls8c_ard_3-2-1_094084_2022-02-19_final
2022-02-23 10:57:36	ga_ls8c_ard_3-2-1_106080_2022-02-23_final
2022-03-07 11:21:06	ga_ls8c_ard_3-2-1_110077_2022-03-07_final
2022-03-14 11:23:38	ga_ls8c_ard_3-2-1_111068_2022-03-14_final
2022-03-18 09:28:22	ga_ls8c_ard_3-2-1_091089_2022-03-17_final
2022-04-06 11:36:02	ga_ls8c_ard_3-2-1_112084_2022-04-06_final
2022-04-13 10:01:47	ga_ls8c_ard_3-2-1_097080_2022-04-13_final
2022-04-21 09:13:32	ga_ls8c_ard_3-2-1_089083_2022-04-20_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-06 10:07:59	ga_ls8c_ard_3-2-1_098080_2022-05-06_final
2022-05-15 09:58:41	ga_ls8c_ard_3-2-1_097072_2022-05-15_final
2022-06-02 09:50:48	ga_ls8c_ard_3-2-1_095083_2022-06-02_final
2022-06-17 09:06:31	ga_ls8c_ard_3-2-1_088080_2022-06-16_final
2022-06-18 11:25:05	ga_ls8c_ard_3-2-1_111071_2022-06-18_final
2022-06-21 10:20:19	ga_ls8c_ard_3-2-1_100079_2022-06-21_final
2022-06-21 10:21:31	ga_ls8c_ard_3-2-1_100082_2022-06-21_final
2022-06-25 09:55:13	ga_ls8c_ard_3-2-1_096078_2022-06-25_final
2022-07-04 09:51:50	ga_ls8c_ard_3-2-1_095085_2022-07-04_final
2022-07-10 10:52:02	ga_ls8c_ard_3-2-1_105081_2022-07-10_final
2022-07-11 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-07-11_final
2022-07-22 09:35:33	ga_ls8c_ard_3-2-1_093075_2022-07-22_final
2022-07-28 10:36:38	ga_ls8c_ard_3-2-1_103073_2022-07-28_final
2022-07-30 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-07-30_final
2022-08-10 11:45:31	ga_ls8c_ard_3-2-1_114075_2022-08-10_final
2022-08-11 09:13:49	ga_ls8c_ard_3-2-1_089082_2022-08-10_final
2022-08-31 10:24:25	ga_ls8c_ard_3-2-1_101073_2022-08-31_final
2022-09-04 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-09-04_final
2022-09-08 11:15:54	ga_ls8c_ard_3-2-1_109078_2022-09-08_final
2022-09-10 09:25:28	ga_ls8c_ard_3-2-1_091080_2022-09-09_final
2022-09-11 11:45:14	ga_ls8c_ard_3-2-1_114074_2022-09-11_final
2022-09-14 10:35:16	ga_ls8c_ard_3-2-1_103069_2022-09-14_final
2022-09-27 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-09-27_final
2022-10-10 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-10-10_final
2022-10-11 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-10-11_final
2022-10-16 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-10-16_final
2022-10-18 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-10-18_final
2022-10-23 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-23_final
2022-10-24 09:47:48	ga_ls8c_ard_3-2-1_095074_2022-10-24_final
2022-11-02 09:42:04	ga_ls8c_ard_3-2-1_094075_2022-11-02_final
2022-11-06 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-11-05_final
2022-11-09 11:29:54	ga_ls8c_ard_3-2-1_111082_2022-11-09_final
2022-11-11 09:37:26	ga_ls8c_ard_3-2-1_093079_2022-11-11_final
2022-11-12 10:20:41	ga_ls8c_ard_3-2-1_100079_2022-11-12_final
2022-11-13 09:25:03	ga_ls8c_ard_3-2-1_091079_2022-11-12_final
2022-11-20 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-11-19_final
2022-11-21 10:15:15	ga_ls8c_ard_3-2-1_099081_2022-11-21_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-12-01 10:50:46	ga_ls8c_ard_3-2-1_105077_2022-12-01_final
2022-12-06 09:31:13	ga_ls8c_ard_3-2-1_092079_2022-12-06_final
2022-12-07 10:14:04	ga_ls8c_ard_3-2-1_099078_2022-12-07_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2023-01-03 09:57:23	ga_ls8c_ard_3-2-1_096083_2023-01-03_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-23 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-01-23_final
2023-01-24 11:52:22	ga_ls8c_ard_3-2-1_115077_2023-01-24_final
2023-02-08 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-02-08_final
2023-02-08 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-02-08_final
2023-02-20 09:57:09	ga_ls8c_ard_3-2-1_096083_2023-02-20_final
2023-02-22 11:18:50	ga_ls8c_ard_3-2-1_110071_2023-02-22_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-29 10:14:08	ga_ls8c_ard_3-2-1_099080_2023-03-29_final
2023-04-11 09:44:58	ga_ls8c_ard_3-2-1_094085_2023-04-11_final
2023-04-24 10:47:43	ga_ls8c_ard_3-2-1_105072_2023-04-24_final
2023-04-29 09:34:08	ga_ls8c_ard_3-2-1_092089_2023-04-29_final
2023-04-29 11:09:02	ga_ls8c_ard_3-2-1_108079_2023-04-29_final
2023-04-29 11:10:14	ga_ls8c_ard_3-2-1_108082_2023-04-29_final
2023-05-08 09:25:03	ga_ls8c_ard_3-2-1_091082_2023-05-07_final
2023-05-18 09:58:49	ga_ls8c_ard_3-2-1_097074_2023-05-18_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