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
2022-01-01 10:39:41	ga_ls8c_ard_3-2-1_103081_2022-01-01_final
2022-01-03 10:27:19	ga_ls8c_ard_3-2-1_101081_2022-01-03_final
2022-02-05 09:34:47	ga_ls8c_ard_3-2-1_092089_2022-02-05_final
2022-02-08 09:57:17	ga_ls8c_ard_3-2-1_097068_2022-02-08_final
2022-02-17 09:51:51	ga_ls8c_ard_3-2-1_096070_2022-02-17_final
2022-02-17 11:32:19	ga_ls8c_ard_3-2-1_112074_2022-02-17_final
2022-03-02 09:23:18	ga_ls8c_ard_3-2-1_091076_2022-03-01_final
2022-03-08 10:23:05	ga_ls8c_ard_3-2-1_101071_2022-03-08_final
2022-03-16 11:14:27	ga_ls8c_ard_3-2-1_109076_2022-03-16_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-06-06 11:05:25	ga_ls8c_ard_3-2-1_107084_2022-06-06_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-16 11:40:13	ga_ls8c_ard_3-2-1_113078_2022-06-16_final
2022-06-22 09:29:05	ga_ls8c_ard_3-2-1_091090_2022-06-21_final
2022-06-27 09:46:27	ga_ls8c_ard_3-2-1_094087_2022-06-27_final
2022-06-30 10:13:22	ga_ls8c_ard_3-2-1_099077_2022-06-30_final
2022-07-23 10:17:14	ga_ls8c_ard_3-2-1_100071_2022-07-23_final
2022-07-25 10:03:18	ga_ls8c_ard_3-2-1_098067_2022-07-25_final
2022-08-07 09:34:55	ga_ls8c_ard_3-2-1_093073_2022-08-07_final
2022-08-08 10:22:35	ga_ls8c_ard_3-2-1_100084_2022-08-08_final
2022-08-28 09:57:54	ga_ls8c_ard_3-2-1_096084_2022-08-28_final
2022-08-30 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-08-30_final
2022-09-09 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-09-09_final
2022-09-27 10:10:23	ga_ls8c_ard_3-2-1_098084_2022-09-27_final
2022-10-04 10:14:56	ga_ls8c_ard_3-2-1_099080_2022-10-04_final
2022-10-11 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-10-11_final
2022-10-17 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-10-17_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-18 10:24:02	ga_ls8c_ard_3-2-1_101072_2022-10-18_final
2022-10-28 11:05:35	ga_ls8c_ard_3-2-1_107083_2022-10-28_final
2022-10-29 10:10:22	ga_ls8c_ard_3-2-1_098084_2022-10-29_final
2022-11-15 10:47:10	ga_ls8c_ard_3-2-1_105068_2022-11-15_final
2022-11-20 09:28:23	ga_ls8c_ard_3-2-1_092072_2022-11-19_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-30 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-30_final
2022-12-06 09:34:00	ga_ls8c_ard_3-2-1_092086_2022-12-06_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2023-01-02 10:52:13	ga_ls8c_ard_3-2-1_105081_2023-01-02_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-17 10:09:37	ga_ls8c_ard_3-2-1_098083_2023-01-17_final
2023-01-21 11:24:13	ga_ls8c_ard_3-2-1_110084_2023-01-21_final
2023-01-29 10:30:03	ga_ls8c_ard_3-2-1_102072_2023-01-29_final
2023-02-06 11:19:53	ga_ls8c_ard_3-2-1_110073_2023-02-06_final
2023-02-06 11:20:16	ga_ls8c_ard_3-2-1_110074_2023-02-06_final
2023-02-26 09:17:57	ga_ls8c_ard_3-2-1_090078_2023-02-25_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-17 11:26:02	ga_ls8c_ard_3-2-1_111074_2023-03-17_final
2023-04-06 09:26:33	ga_ls8c_ard_3-2-1_091085_2023-04-05_final
2023-04-10 10:34:38	ga_ls8c_ard_3-2-1_103070_2023-04-10_final
2023-04-16 09:56:43	ga_ls8c_ard_3-2-1_097068_2023-04-16_final
2023-04-18 11:25:37	ga_ls8c_ard_3-2-1_111074_2023-04-18_final
2023-04-18 11:29:36	ga_ls8c_ard_3-2-1_111084_2023-04-18_final
2023-04-26 10:35:21	ga_ls8c_ard_3-2-1_103072_2023-04-26_final
2023-04-29 09:28:33	ga_ls8c_ard_3-2-1_092075_2023-04-28_final
2023-05-07 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-05-07_final
2023-05-23 10:16:12	ga_ls8c_ard_3-2-1_100071_2023-05-23_final
2023-05-24 09:22:11	ga_ls8c_ard_3-2-1_091075_2023-05-23_final
2023-05-24 10:59:04	ga_ls8c_ard_3-2-1_107070_2023-05-24_final
2023-05-26 09:11:25	ga_ls8c_ard_3-2-1_089079_2023-05-25_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
2023-06-09 09:22:17	ga_ls8c_ard_3-2-1_091075_2023-06-08_final
2023-06-09 11:04:22	ga_ls8c_ard_3-2-1_107083_2023-06-09_final
2023-06-22 10:29:32	ga_ls8c_ard_3-2-1_102073_2023-06-22_final
2023-07-11 09:26:58	ga_ls8c_ard_3-2-1_091086_2023-07-10_final
2023-07-16 11:18:49	ga_ls8c_ard_3-2-1_110072_2023-07-16_final
2023-07-21 09:58:52	ga_ls8c_ard_3-2-1_097073_2023-07-21_final
2023-07-28 11:46:50	ga_ls8c_ard_3-2-1_114080_2023-07-28_final
2023-08-01 11:23:44	ga_ls8c_ard_3-2-1_110084_2023-08-01_final
2023-08-14 09:13:37	ga_ls8c_ard_3-2-1_089083_2023-08-13_final
2023-08-15 11:35:46	ga_ls8c_ard_3-2-1_112083_2023-08-15_final
2023-09-15 09:11:46	ga_ls8c_ard_3-2-1_089078_2023-09-14_final
2023-09-21 10:10:24	ga_ls8c_ard_3-2-1_099070_2023-09-21_final
2023-09-23 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-09-23_final
2023-09-28 10:17:01	ga_ls8c_ard_3-2-1_100071_2023-09-28_final
2023-10-03 10:39:57	ga_ls8c_ard_3-2-1_103082_2023-10-03_final
2023-10-07 10:09:15	ga_ls8c_ard_3-2-1_099067_2023-10-07_final
2023-10-10 10:42:35	ga_ls8c_ard_3-2-1_104073_2023-10-10_final
2023-10-20 09:40:45	ga_ls8c_ard_3-2-1_094073_2023-10-20_final
2023-10-23 10:11:18	ga_ls8c_ard_3-2-1_099072_2023-10-23_final
2023-10-27 11:30:17	ga_ls8c_ard_3-2-1_111084_2023-10-27_final
2023-10-30 10:22:19	ga_ls8c_ard_3-2-1_100084_2023-10-30_final
2023-10-31 09:22:42	ga_ls8c_ard_3-2-1_091074_2023-10-30_final
2023-11-02 09:16:19	ga_ls8c_ard_3-2-1_089089_2023-11-01_final
2023-11-08 10:15:40	ga_ls8c_ard_3-2-1_099083_2023-11-08_final
2023-11-09 10:55:43	ga_ls8c_ard_3-2-1_106075_2023-11-09_final
2023-11-16 09:27:28	ga_ls8c_ard_3-2-1_091086_2023-11-15_final
2023-11-18 09:13:56	ga_ls8c_ard_3-2-1_089083_2023-11-17_final
2023-12-11 10:54:08	ga_ls8c_ard_3-2-1_106071_2023-12-11_final
2023-12-26 10:12:55	ga_ls8c_ard_3-2-1_099076_2023-12-26_final
2024-01-03 09:22:59	ga_ls8c_ard_3-2-1_091075_2024-01-02_final
2024-01-08 11:18:24	ga_ls8c_ard_3-2-1_110070_2024-01-08_final
2024-01-08 11:19:12	ga_ls8c_ard_3-2-1_110072_2024-01-08_final
2024-01-08 11:20:24	ga_ls8c_ard_3-2-1_110075_2024-01-08_final
2024-01-11 10:08:51	ga_ls8c_ard_3-2-1_099066_2024-01-11_final
2024-01-11 11:51:20	ga_ls8c_ard_3-2-1_115075_2024-01-11_final
2024-01-19 09:28:10	ga_ls8c_ard_3-2-1_091088_2024-01-18_final
2024-03-03 09:46:21	ga_ls8c_ard_3-2-1_095072_2024-03-03_final
2024-03-04 10:29:11	ga_ls8c_ard_3-2-1_102071_2024-03-04_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