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
2017-12-13 08:10:52	ga_ls8c_ard_3-2-1_079080_2017-12-12_final
2021-12-17 11:23:26	ga_ls8c_ard_3-2-1_110082_2021-12-17_final
2021-12-28 09:25:09	ga_ls8c_ard_3-2-1_091080_2021-12-27_final
2022-01-09 11:29:31	ga_ls8c_ard_3-2-1_111082_2022-01-09_final
2022-01-14 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-01-14_final
2022-01-18 11:21:42	ga_ls8c_ard_3-2-1_110078_2022-01-18_final
2022-02-11 10:28:58	ga_ls8c_ard_3-2-1_102070_2022-02-11_final
2022-02-22 10:15:32	ga_ls8c_ard_3-2-1_099083_2022-02-22_final
2022-03-05 09:56:11	ga_ls8c_ard_3-2-1_096081_2022-03-05_final
2022-03-20 10:46:05	ga_ls8c_ard_3-2-1_105067_2022-03-20_final
2022-03-23 11:23:44	ga_ls8c_ard_3-2-1_110084_2022-03-23_final
2022-03-25 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-03-25_final
2022-04-12 10:55:01	ga_ls8c_ard_3-2-1_106074_2022-04-12_final
2022-04-14 10:42:40	ga_ls8c_ard_3-2-1_104074_2022-04-14_final
2022-04-15 09:46:39	ga_ls8c_ard_3-2-1_095073_2022-04-15_final
2022-04-17 09:40:16	ga_ls8c_ard_3-2-1_093088_2022-04-17_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-30 09:06:06	ga_ls8c_ard_3-2-1_088080_2022-04-29_final
2022-05-07 10:46:52	ga_ls8c_ard_3-2-1_105069_2022-05-07_final
2022-05-14 10:56:18	ga_ls8c_ard_3-2-1_106077_2022-05-14_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-05-30 10:53:33	ga_ls8c_ard_3-2-1_106070_2022-05-30_final
2022-06-02 09:46:49	ga_ls8c_ard_3-2-1_095073_2022-06-02_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-15 10:54:09	ga_ls8c_ard_3-2-1_106071_2022-06-15_final
2022-06-15 10:54:57	ga_ls8c_ard_3-2-1_106073_2022-06-15_final
2022-06-18 09:50:35	ga_ls8c_ard_3-2-1_095082_2022-06-18_final
2022-06-18 11:25:29	ga_ls8c_ard_3-2-1_111072_2022-06-18_final
2022-06-23 10:03:58	ga_ls8c_ard_3-2-1_098069_2022-06-23_final
2022-06-29 11:06:11	ga_ls8c_ard_3-2-1_108070_2022-06-29_final
2022-07-16 10:09:45	ga_ls8c_ard_3-2-1_099068_2022-07-16_final
2022-07-16 10:15:20	ga_ls8c_ard_3-2-1_099082_2022-07-16_final
2022-07-19 09:07:00	ga_ls8c_ard_3-2-1_088081_2022-07-18_final
2022-08-16 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-08-16_final
2022-08-25 09:23:01	ga_ls8c_ard_3-2-1_091074_2022-08-24_final
2022-09-03 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-09-02_final
2022-09-06 11:27:27	ga_ls8c_ard_3-2-1_111076_2022-09-06_final
2022-09-17 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-09-17_final
2022-09-22 11:25:56	ga_ls8c_ard_3-2-1_111072_2022-09-22_final
2022-10-11 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-10-11_final
2022-10-12 09:23:48	ga_ls8c_ard_3-2-1_091076_2022-10-11_final
2022-10-14 10:52:17	ga_ls8c_ard_3-2-1_105081_2022-10-14_final
2022-10-22 11:38:14	ga_ls8c_ard_3-2-1_113072_2022-10-22_final
2022-11-20 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-11-20_final
2022-12-01 10:51:34	ga_ls8c_ard_3-2-1_105079_2022-12-01_final
2022-12-02 09:55:08	ga_ls8c_ard_3-2-1_096077_2022-12-02_final
2022-12-25 11:40:02	ga_ls8c_ard_3-2-1_113077_2022-12-25_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-06 10:24:41	ga_ls8c_ard_3-2-1_101074_2023-01-06_final
2023-01-13 10:32:24	ga_ls8c_ard_3-2-1_102078_2023-01-13_final
2023-01-18 09:16:23	ga_ls8c_ard_3-2-1_089089_2023-01-17_final
2023-02-03 09:13:18	ga_ls8c_ard_3-2-1_089081_2023-02-02_final
2023-02-10 09:19:26	ga_ls8c_ard_3-2-1_090081_2023-02-09_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-02-27 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-02-27_final
2023-03-03 09:39:41	ga_ls8c_ard_3-2-1_093086_2023-03-03_final
2023-03-03 11:16:58	ga_ls8c_ard_3-2-1_109082_2023-03-03_final
2023-03-03 11:17:22	ga_ls8c_ard_3-2-1_109083_2023-03-03_final
2023-03-06 11:47:02	ga_ls8c_ard_3-2-1_114080_2023-03-06_final
2023-03-23 09:13:33	ga_ls8c_ard_3-2-1_089083_2023-03-22_final
2023-03-23 09:13:57	ga_ls8c_ard_3-2-1_089084_2023-03-22_final
2023-03-28 11:05:22	ga_ls8c_ard_3-2-1_108069_2023-03-28_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-04-12 10:23:27	ga_ls8c_ard_3-2-1_101073_2023-04-12_final
2023-04-15 09:20:38	ga_ls8c_ard_3-2-1_090086_2023-04-14_final
2023-05-01 10:52:40	ga_ls8c_ard_3-2-1_106069_2023-05-01_final
2023-05-02 11:37:55	ga_ls8c_ard_3-2-1_113074_2023-05-02_final
2023-05-08 09:27:51	ga_ls8c_ard_3-2-1_091089_2023-05-07_final
2023-05-09 10:05:06	ga_ls8c_ard_3-2-1_098074_2023-05-09_final
2023-05-13 11:17:12	ga_ls8c_ard_3-2-1_110069_2023-05-13_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_2023-05-15_final
2023-05-24 11:03:28	ga_ls8c_ard_3-2-1_107081_2023-05-24_final
2023-05-25 10:03:27	ga_ls8c_ard_3-2-1_098070_2023-05-25_final
2023-05-29 11:20:25	ga_ls8c_ard_3-2-1_110077_2023-05-29_final
2023-06-21 09:47:04	ga_ls8c_ard_3-2-1_095075_2023-06-21_final
2023-07-02 09:30:16	ga_ls8c_ard_3-2-1_092079_2023-07-02_final
2023-07-31 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-07-31_final
2023-08-06 09:59:25	ga_ls8c_ard_3-2-1_097074_2023-08-06_final
2023-08-22 11:40:49	ga_ls8c_ard_3-2-1_113080_2023-08-22_final
2023-09-14 11:47:28	ga_ls8c_ard_3-2-1_114081_2023-09-14_final
2023-09-20 11:05:37	ga_ls8c_ard_3-2-1_108069_2023-09-20_final
2023-09-25 09:51:17	ga_ls8c_ard_3-2-1_095084_2023-09-25_final
2023-09-28 11:58:42	ga_ls8c_ard_3-2-1_116078_2023-09-28_final
2023-09-29 09:25:24	ga_ls8c_ard_3-2-1_091081_2023-09-28_final
2023-10-10 09:06:53	ga_ls8c_ard_3-2-1_088081_2023-10-09_final
2023-10-17 10:47:10	ga_ls8c_ard_3-2-1_105069_2023-10-17_final
2023-10-17 10:51:57	ga_ls8c_ard_3-2-1_105081_2023-10-17_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-30 11:58:48	ga_ls8c_ard_3-2-1_116078_2023-10-30_final
2023-11-06 10:23:40	ga_ls8c_ard_3-2-1_101072_2023-11-06_final
2023-11-12 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-11-12_final
2023-11-16 11:02:46	ga_ls8c_ard_3-2-1_107077_2023-11-16_final
2023-11-30 11:13:08	ga_ls8c_ard_3-2-1_109072_2023-11-30_final
2023-12-11 09:22:26	ga_ls8c_ard_3-2-1_090089_2023-12-10_final
2023-12-12 10:02:31	ga_ls8c_ard_3-2-1_097081_2023-12-12_final
2024-01-04 10:08:13	ga_ls8c_ard_3-2-1_098080_2024-01-04_final
2024-01-05 10:50:16	ga_ls8c_ard_3-2-1_105077_2024-01-05_final
2024-02-16 11:23:45	ga_ls8c_ard_3-2-1_111068_2024-02-16_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years