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
2020-01-20 08:10:52	ga_ls8c_ard_3-2-1_079080_2020-01-19_final
2022-03-20 10:48:53	ga_ls8c_ard_3-2-1_105074_2022-03-20_final
2022-04-24 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-24_final
2022-05-16 10:45:57	ga_ls8c_ard_3-2-1_104082_2022-05-16_final
2022-05-19 11:14:52	ga_ls8c_ard_3-2-1_109077_2022-05-19_final
2022-05-21 11:02:54	ga_ls8c_ard_3-2-1_107078_2022-05-21_final
2022-05-26 11:23:49	ga_ls8c_ard_3-2-1_110084_2022-05-26_final
2022-05-31 09:58:20	ga_ls8c_ard_3-2-1_097071_2022-05-31_final
2022-06-02 11:24:54	ga_ls8c_ard_3-2-1_111071_2022-06-02_final
2022-06-10 10:35:58	ga_ls8c_ard_3-2-1_103072_2022-06-10_final
2022-06-11 11:18:26	ga_ls8c_ard_3-2-1_110070_2022-06-11_final
2022-06-15 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-06-15_final
2022-06-23 11:47:39	ga_ls8c_ard_3-2-1_114081_2022-06-23_final
2022-07-12 10:40:04	ga_ls8c_ard_3-2-1_103082_2022-07-12_final
2022-07-18 09:59:49	ga_ls8c_ard_3-2-1_097074_2022-07-18_final
2022-07-21 10:29:34	ga_ls8c_ard_3-2-1_102071_2022-07-21_final
2022-07-22 09:34:45	ga_ls8c_ard_3-2-1_093073_2022-07-22_final
2022-07-28 10:39:49	ga_ls8c_ard_3-2-1_103081_2022-07-28_final
2022-08-02 10:58:49	ga_ls8c_ard_3-2-1_106082_2022-08-02_final
2022-09-16 10:23:19	ga_ls8c_ard_3-2-1_101070_2022-09-16_final
2022-09-25 10:20:21	ga_ls8c_ard_3-2-1_100078_2022-09-25_final
2022-10-07 10:41:49	ga_ls8c_ard_3-2-1_104070_2022-10-07_final
2022-10-14 09:14:36	ga_ls8c_ard_3-2-1_089084_2022-10-13_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-11-01 10:36:29	ga_ls8c_ard_3-2-1_103072_2022-11-01_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-12-15 09:22:58	ga_ls8c_ard_3-2-1_091074_2022-12-14_final
2022-12-15 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-12-15_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-26 10:44:25	ga_ls8c_ard_3-2-1_104077_2022-12-26_final
2022-12-29 09:40:26	ga_ls8c_ard_3-2-1_093087_2022-12-29_final
2023-01-03 09:53:48	ga_ls8c_ard_3-2-1_096074_2023-01-03_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-06 09:44:35	ga_ls8c_ard_3-2-1_094082_2023-02-06_final
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-15 09:40:42	ga_ls8c_ard_3-2-1_093088_2023-02-15_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-02-20 09:57:33	ga_ls8c_ard_3-2-1_096084_2023-02-20_final
2023-02-20 11:31:38	ga_ls8c_ard_3-2-1_112072_2023-02-20_final
2023-02-23 10:27:59	ga_ls8c_ard_3-2-1_101083_2023-02-23_final
2023-02-27 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-02-27_final
2023-03-01 11:24:57	ga_ls8c_ard_3-2-1_111071_2023-03-01_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-17 11:26:02	ga_ls8c_ard_3-2-1_111074_2023-03-17_final
2023-04-06 09:25:21	ga_ls8c_ard_3-2-1_091082_2023-04-05_final
2023-04-08 09:16:08	ga_ls8c_ard_3-2-1_089090_2023-04-07_final
2023-04-13 09:33:24	ga_ls8c_ard_3-2-1_092087_2023-04-13_final
2023-04-16 09:59:06	ga_ls8c_ard_3-2-1_097074_2023-04-16_final
2023-04-20 11:13:38	ga_ls8c_ard_3-2-1_109075_2023-04-20_final
2023-04-21 10:17:37	ga_ls8c_ard_3-2-1_100074_2023-04-21_final
2023-05-01 09:16:34	ga_ls8c_ard_3-2-1_090076_2023-04-30_final
2023-06-02 09:20:00	ga_ls8c_ard_3-2-1_090085_2023-06-01_final
2023-06-02 10:55:17	ga_ls8c_ard_3-2-1_106076_2023-06-02_final
2023-06-10 11:46:50	ga_ls8c_ard_3-2-1_114081_2023-06-10_final
2023-06-11 09:09:33	ga_ls8c_ard_3-2-1_089074_2023-06-10_final
2023-06-19 11:41:30	ga_ls8c_ard_3-2-1_113083_2023-06-19_final
2023-07-12 11:47:07	ga_ls8c_ard_3-2-1_114081_2023-07-12_final
2023-07-13 10:48:42	ga_ls8c_ard_3-2-1_105074_2023-07-13_final
2023-07-24 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-07-24_final
2023-08-05 10:55:50	ga_ls8c_ard_3-2-1_106076_2023-08-05_final
2023-08-06 09:58:13	ga_ls8c_ard_3-2-1_097071_2023-08-06_final
2023-08-11 10:17:09	ga_ls8c_ard_3-2-1_100072_2023-08-11_final
2023-08-12 11:01:14	ga_ls8c_ard_3-2-1_107074_2023-08-12_final
2023-08-26 11:11:44	ga_ls8c_ard_3-2-1_109069_2023-08-26_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-04 11:05:56	ga_ls8c_ard_3-2-1_108070_2023-09-04_final
2023-09-22 09:17:10	ga_ls8c_ard_3-2-1_090076_2023-09-21_final
2023-09-29 11:02:17	ga_ls8c_ard_3-2-1_107076_2023-09-29_final
2023-09-30 10:09:51	ga_ls8c_ard_3-2-1_098084_2023-09-30_final
2023-10-11 09:47:22	ga_ls8c_ard_3-2-1_095074_2023-10-11_final
2023-10-18 09:57:07	ga_ls8c_ard_3-2-1_096083_2023-10-18_final
2023-10-23 10:13:42	ga_ls8c_ard_3-2-1_099078_2023-10-23_final
2023-10-31 09:23:30	ga_ls8c_ard_3-2-1_091076_2023-10-30_final
2023-11-01 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-11-01_final
2023-11-16 09:27:04	ga_ls8c_ard_3-2-1_091085_2023-11-15_final
2023-11-16 11:01:34	ga_ls8c_ard_3-2-1_107074_2023-11-16_final
2023-11-21 09:44:27	ga_ls8c_ard_3-2-1_094082_2023-11-21_final
2023-11-25 09:20:56	ga_ls8c_ard_3-2-1_090085_2023-11-24_final
2023-11-25 10:55:50	ga_ls8c_ard_3-2-1_106075_2023-11-25_final
2023-11-25 10:57:50	ga_ls8c_ard_3-2-1_106080_2023-11-25_final
2023-11-28 09:51:26	ga_ls8c_ard_3-2-1_095084_2023-11-28_final
2023-11-29 10:33:05	ga_ls8c_ard_3-2-1_102080_2023-11-29_final
2023-12-05 09:52:42	ga_ls8c_ard_3-2-1_096072_2023-12-05_final
2023-12-05 11:31:59	ga_ls8c_ard_3-2-1_112073_2023-12-05_final
2023-12-08 10:27:11	ga_ls8c_ard_3-2-1_101081_2023-12-08_final
2023-12-12 11:42:12	ga_ls8c_ard_3-2-1_113083_2023-12-12_final
2023-12-15 10:33:51	ga_ls8c_ard_3-2-1_102082_2023-12-15_final
2023-12-18 09:26:41	ga_ls8c_ard_3-2-1_091084_2023-12-17_final
2023-12-19 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-12-19_final
2023-12-30 11:26:15	ga_ls8c_ard_3-2-1_111074_2023-12-30_final
2024-01-08 09:41:31	ga_ls8c_ard_3-2-1_094075_2024-01-08_final
2024-01-16 10:30:59	ga_ls8c_ard_3-2-1_102075_2024-01-16_final
2024-01-19 09:26:35	ga_ls8c_ard_3-2-1_091084_2024-01-18_final
2024-01-28 10:57:35	ga_ls8c_ard_3-2-1_106080_2024-01-28_final
2024-01-31 08:10:46	ga_ls8c_ard_3-2-1_079080_2024-01-30_final
2024-02-19 10:16:58	ga_ls8c_ard_3-2-1_100071_2024-02-19_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