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
2022-09-15 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-09-15_final
2022-09-19 10:56:38	ga_ls8c_ard_3-2-1_106076_2022-09-19_final
2022-09-21 10:41:53	ga_ls8c_ard_3-2-1_104070_2022-09-21_final
2022-09-22 11:30:44	ga_ls8c_ard_3-2-1_111084_2022-09-22_final
2022-10-08 11:30:39	ga_ls8c_ard_3-2-1_111084_2022-10-08_final
2022-10-11 10:21:26	ga_ls8c_ard_3-2-1_100081_2022-10-11_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-13 10:05:27	ga_ls8c_ard_3-2-1_098072_2022-10-13_final
2022-10-15 09:53:05	ga_ls8c_ard_3-2-1_096072_2022-10-15_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-11-05 10:14:09	ga_ls8c_ard_3-2-1_099078_2022-11-05_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-09 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-11-09_final
2022-11-10 10:33:52	ga_ls8c_ard_3-2-1_102081_2022-11-10_final
2022-11-11 11:17:31	ga_ls8c_ard_3-2-1_109082_2022-11-11_final
2022-11-16 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-11-16_final
2022-11-22 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-11-21_final
2022-11-25 09:47:45	ga_ls8c_ard_3-2-1_095074_2022-11-25_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-08 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-12-07_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2023-01-02 09:12:08	ga_ls8c_ard_3-2-1_089078_2023-01-01_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-07 11:07:57	ga_ls8c_ard_3-2-1_108074_2023-01-07_final
2023-01-09 09:21:05	ga_ls8c_ard_3-2-1_090085_2023-01-08_final
2023-01-10 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-10_final
2023-01-10 11:42:25	ga_ls8c_ard_3-2-1_113083_2023-01-10_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-02-21 10:34:24	ga_ls8c_ard_3-2-1_103068_2023-02-21_final
2023-02-24 11:08:01	ga_ls8c_ard_3-2-1_108075_2023-02-24_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-09 10:34:13	ga_ls8c_ard_3-2-1_103068_2023-03-09_final
2023-03-09 10:39:25	ga_ls8c_ard_3-2-1_103081_2023-03-09_final
2023-03-10 11:23:52	ga_ls8c_ard_3-2-1_110084_2023-03-10_final
2023-03-19 11:11:39	ga_ls8c_ard_3-2-1_109069_2023-03-19_final
2023-03-21 11:04:02	ga_ls8c_ard_3-2-1_107081_2023-03-21_final
2023-03-24 09:52:25	ga_ls8c_ard_3-2-1_096072_2023-03-24_final
2023-03-29 10:13:44	ga_ls8c_ard_3-2-1_099079_2023-03-29_final
2023-04-04 11:14:15	ga_ls8c_ard_3-2-1_109076_2023-04-04_final
2023-04-06 09:22:58	ga_ls8c_ard_3-2-1_091076_2023-04-05_final
2023-04-08 09:16:08	ga_ls8c_ard_3-2-1_089090_2023-04-07_final
2023-04-15 09:21:26	ga_ls8c_ard_3-2-1_090088_2023-04-14_final
2023-04-27 09:44:31	ga_ls8c_ard_3-2-1_094084_2023-04-27_final
2023-05-01 10:57:27	ga_ls8c_ard_3-2-1_106081_2023-05-01_final
2023-05-02 11:40:42	ga_ls8c_ard_3-2-1_113081_2023-05-02_final
2023-05-04 09:46:15	ga_ls8c_ard_3-2-1_095073_2023-05-04_final
2023-05-08 09:28:15	ga_ls8c_ard_3-2-1_091090_2023-05-07_final
2023-05-10 10:48:20	ga_ls8c_ard_3-2-1_105074_2023-05-10_final
2023-05-14 10:23:34	ga_ls8c_ard_3-2-1_101074_2023-05-14_final
2023-05-18 11:40:30	ga_ls8c_ard_3-2-1_113081_2023-05-18_final
2023-05-24 09:21:47	ga_ls8c_ard_3-2-1_091074_2023-05-23_final
2023-05-24 10:59:04	ga_ls8c_ard_3-2-1_107070_2023-05-24_final
2023-05-24 11:01:28	ga_ls8c_ard_3-2-1_107076_2023-05-24_final
2023-05-25 10:09:26	ga_ls8c_ard_3-2-1_098085_2023-05-25_final
2023-05-26 09:15:49	ga_ls8c_ard_3-2-1_089090_2023-05-25_final
2023-05-27 11:30:47	ga_ls8c_ard_3-2-1_112072_2023-05-27_final
2023-06-11 09:15:56	ga_ls8c_ard_3-2-1_089090_2023-06-10_final
2023-06-15 10:23:44	ga_ls8c_ard_3-2-1_101074_2023-06-15_final
2023-07-02 09:31:28	ga_ls8c_ard_3-2-1_092082_2023-07-02_final
2023-07-06 10:40:53	ga_ls8c_ard_3-2-1_104070_2023-07-06_final
2023-07-11 09:26:10	ga_ls8c_ard_3-2-1_091084_2023-07-10_final
2023-07-11 09:28:34	ga_ls8c_ard_3-2-1_091090_2023-07-10_final
2023-07-14 11:34:46	ga_ls8c_ard_3-2-1_112081_2023-07-14_final
2023-08-01 11:24:08	ga_ls8c_ard_3-2-1_110085_2023-08-01_final
2023-08-04 10:13:46	ga_ls8c_ard_3-2-1_099079_2023-08-04_final
2023-08-14 10:48:54	ga_ls8c_ard_3-2-1_105074_2023-08-14_final
2023-08-25 10:28:04	ga_ls8c_ard_3-2-1_102068_2023-08-25_final
2023-09-07 09:58:20	ga_ls8c_ard_3-2-1_097071_2023-09-07_final
2023-09-18 09:44:17	ga_ls8c_ard_3-2-1_094082_2023-09-18_final
2023-09-18 11:18:23	ga_ls8c_ard_3-2-1_110070_2023-09-18_final
2023-09-19 10:24:21	ga_ls8c_ard_3-2-1_101074_2023-09-19_final
2023-09-20 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-09-19_final
2023-09-26 10:28:58	ga_ls8c_ard_3-2-1_102070_2023-09-26_final
2023-09-27 09:38:33	ga_ls8c_ard_3-2-1_093083_2023-09-27_final
2023-09-29 09:23:24	ga_ls8c_ard_3-2-1_091076_2023-09-28_final
2023-09-29 09:26:36	ga_ls8c_ard_3-2-1_091084_2023-09-28_final
2023-09-29 11:02:17	ga_ls8c_ard_3-2-1_107076_2023-09-29_final
2023-09-29 11:04:17	ga_ls8c_ard_3-2-1_107081_2023-09-29_final
2023-10-04 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-10-04_final
2023-10-06 09:29:10	ga_ls8c_ard_3-2-1_092075_2023-10-05_final
2023-10-07 10:13:39	ga_ls8c_ard_3-2-1_099078_2023-10-07_final
2023-10-12 10:28:14	ga_ls8c_ard_3-2-1_102068_2023-10-12_final
2023-10-12 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-10-12_final
2023-10-12 10:33:25	ga_ls8c_ard_3-2-1_102081_2023-10-12_final
2023-10-22 09:29:13	ga_ls8c_ard_3-2-1_092075_2023-10-21_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-10-29 11:13:56	ga_ls8c_ard_3-2-1_109074_2023-10-29_final
2023-11-02 09:14:19	ga_ls8c_ard_3-2-1_089084_2023-11-01_final
2023-11-05 09:44:25	ga_ls8c_ard_3-2-1_094082_2023-11-05_final
2023-11-05 11:24:05	ga_ls8c_ard_3-2-1_110084_2023-11-05_final
2023-11-07 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-11-07_final
2023-11-07 11:06:31	ga_ls8c_ard_3-2-1_108071_2023-11-07_final
2023-11-09 10:56:07	ga_ls8c_ard_3-2-1_106076_2023-11-09_final
2023-11-09 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-11-09_final
2023-11-10 09:58:53	ga_ls8c_ard_3-2-1_097072_2023-11-10_final
2023-11-13 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-11-13_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