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
2022-02-26 11:29:18	ga_ls8c_ard_3-2-1_111082_2022-02-26_final
2022-03-06 10:35:27	ga_ls8c_ard_3-2-1_103071_2022-03-06_final
2022-03-09 11:07:32	ga_ls8c_ard_3-2-1_108074_2022-03-09_final
2022-03-12 10:01:55	ga_ls8c_ard_3-2-1_097080_2022-03-12_final
2022-03-12 11:37:37	ga_ls8c_ard_3-2-1_113072_2022-03-12_final
2022-03-14 11:26:26	ga_ls8c_ard_3-2-1_111075_2022-03-14_final
2022-03-19 10:07:38	ga_ls8c_ard_3-2-1_098079_2022-03-19_final
2022-03-28 09:59:20	ga_ls8c_ard_3-2-1_097074_2022-03-28_final
2022-03-28 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-03-28_final
2022-04-06 09:51:33	ga_ls8c_ard_3-2-1_096070_2022-04-06_final
2022-04-09 10:26:53	ga_ls8c_ard_3-2-1_101081_2022-04-09_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-22 09:52:24	ga_ls8c_ard_3-2-1_096072_2022-04-22_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-04-24 09:43:37	ga_ls8c_ard_3-2-1_094081_2022-04-24_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-28 10:54:09	ga_ls8c_ard_3-2-1_106072_2022-04-28_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-05-06 11:44:53	ga_ls8c_ard_3-2-1_114075_2022-05-06_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-17 09:45:56	ga_ls8c_ard_3-2-1_095071_2022-05-17_final
2022-05-17 11:29:37	ga_ls8c_ard_3-2-1_111083_2022-05-17_final
2022-05-28 11:10:16	ga_ls8c_ard_3-2-1_108081_2022-05-28_final
2022-05-31 10:00:20	ga_ls8c_ard_3-2-1_097076_2022-05-31_final
2022-06-06 09:25:44	ga_ls8c_ard_3-2-1_091082_2022-06-05_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-21 10:17:55	ga_ls8c_ard_3-2-1_100073_2022-06-21_final
2022-06-22 09:23:54	ga_ls8c_ard_3-2-1_091077_2022-06-21_final
2022-06-29 11:05:47	ga_ls8c_ard_3-2-1_108069_2022-06-29_final
2022-07-01 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-07-01_final
2022-07-05 10:29:31	ga_ls8c_ard_3-2-1_102071_2022-07-05_final
2022-07-09 11:45:16	ga_ls8c_ard_3-2-1_114075_2022-07-09_final
2022-07-19 10:44:41	ga_ls8c_ard_3-2-1_104078_2022-07-19_final
2022-07-25 11:47:22	ga_ls8c_ard_3-2-1_114080_2022-07-25_final
2022-07-31 11:09:57	ga_ls8c_ard_3-2-1_108079_2022-07-31_final
2022-08-17 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-08-17_final
2022-08-23 11:13:28	ga_ls8c_ard_3-2-1_109072_2022-08-23_final
2022-08-26 10:06:41	ga_ls8c_ard_3-2-1_098075_2022-08-26_final
2022-09-14 10:39:40	ga_ls8c_ard_3-2-1_103080_2022-09-14_final
2022-10-09 10:34:13	ga_ls8c_ard_3-2-1_102082_2022-10-09_final
2022-10-10 11:15:52	ga_ls8c_ard_3-2-1_109078_2022-10-10_final
2022-10-13 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-10-13_final
2022-10-17 11:23:14	ga_ls8c_ard_3-2-1_110081_2022-10-17_final
2022-10-22 10:00:57	ga_ls8c_ard_3-2-1_097076_2022-10-22_final
2022-10-30 09:13:09	ga_ls8c_ard_3-2-1_089080_2022-10-29_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-06 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-11-05_final
2022-11-18 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-11-18_final
2022-11-18 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-11-18_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-25 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-11-25_final
2022-11-30 10:09:54	ga_ls8c_ard_3-2-1_098083_2022-11-30_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-08 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-12-07_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-13 09:34:09	ga_ls8c_ard_3-2-1_093071_2022-12-13_final
2022-12-22 11:10:43	ga_ls8c_ard_3-2-1_108081_2022-12-22_final
2022-12-30 11:59:00	ga_ls8c_ard_3-2-1_116078_2022-12-30_final
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-07 11:10:20	ga_ls8c_ard_3-2-1_108080_2023-01-07_final
2023-01-10 11:39:14	ga_ls8c_ard_3-2-1_113075_2023-01-10_final
2023-01-14 11:14:51	ga_ls8c_ard_3-2-1_109076_2023-01-14_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-01-25 09:23:03	ga_ls8c_ard_3-2-1_090090_2023-01-24_final
2023-01-30 09:40:49	ga_ls8c_ard_3-2-1_093088_2023-01-30_final
2023-02-02 10:08:07	ga_ls8c_ard_3-2-1_098079_2023-02-02_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-20 10:20:24	ga_ls8c_ard_3-2-1_100080_2023-03-20_final
2023-03-22 10:08:00	ga_ls8c_ard_3-2-1_098080_2023-03-22_final
2023-04-20 11:12:02	ga_ls8c_ard_3-2-1_109071_2023-04-20_final
2023-04-25 11:34:58	ga_ls8c_ard_3-2-1_112082_2023-04-25_final
2023-04-29 09:31:45	ga_ls8c_ard_3-2-1_092083_2023-04-29_final
2023-05-02 09:57:50	ga_ls8c_ard_3-2-1_097071_2023-05-02_final
2023-05-02 11:37:55	ga_ls8c_ard_3-2-1_113074_2023-05-02_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-05-18 10:00:25	ga_ls8c_ard_3-2-1_097078_2023-05-18_final
2023-05-26 10:51:54	ga_ls8c_ard_3-2-1_105083_2023-05-26_final
2023-05-28 10:37:57	ga_ls8c_ard_3-2-1_103079_2023-05-28_final
2023-06-02 09:17:12	ga_ls8c_ard_3-2-1_090078_2023-06-01_final
2023-06-09 11:03:34	ga_ls8c_ard_3-2-1_107081_2023-06-09_final
2023-06-15 10:22:09	ga_ls8c_ard_3-2-1_101070_2023-06-15_final
2023-06-20 10:41:54	ga_ls8c_ard_3-2-1_104073_2023-06-20_final
2023-06-23 09:33:07	ga_ls8c_ard_3-2-1_093071_2023-06-23_final
2023-06-27 09:13:15	ga_ls8c_ard_3-2-1_089083_2023-06-26_final
2023-06-30 09:41:25	ga_ls8c_ard_3-2-1_094076_2023-06-30_final
2023-07-09 11:13:01	ga_ls8c_ard_3-2-1_109073_2023-07-09_final
2023-07-12 10:06:38	ga_ls8c_ard_3-2-1_098077_2023-07-12_final
2023-07-28 10:08:20	ga_ls8c_ard_3-2-1_098081_2023-07-28_final
2023-08-05 09:18:57	ga_ls8c_ard_3-2-1_090081_2023-08-04_final
2023-08-12 11:03:14	ga_ls8c_ard_3-2-1_107079_2023-08-12_final
2023-08-14 10:52:06	ga_ls8c_ard_3-2-1_105082_2023-08-14_final
2023-08-20 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-08-20_final
2023-08-31 11:31:52	ga_ls8c_ard_3-2-1_112073_2023-08-31_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