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
2018-10-25 10:08:37	ga_ls8c_ard_3-2-1_099066_2018-10-25_final
2022-09-11 10:07:09	ga_ls8c_ard_3-2-1_098076_2022-09-11_final
2022-09-17 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-09-16_final
2022-09-19 10:56:38	ga_ls8c_ard_3-2-1_106076_2022-09-19_final
2022-10-13 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-10-13_final
2022-10-13 10:04:15	ga_ls8c_ard_3-2-1_098069_2022-10-13_final
2022-10-13 10:05:27	ga_ls8c_ard_3-2-1_098072_2022-10-13_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2022-11-03 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-11-03_final
2022-11-04 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-11-04_final
2022-11-18 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-11-18_final
2023-03-16 09:07:29	ga_ls8c_ard_3-2-1_088083_2023-03-15_final
2023-03-21 09:26:21	ga_ls8c_ard_3-2-1_091084_2023-03-20_final
2023-03-25 10:34:29	ga_ls8c_ard_3-2-1_103069_2023-03-25_final
2023-03-25 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-03-25_final
2023-04-06 11:05:02	ga_ls8c_ard_3-2-1_107084_2023-04-06_final
2023-04-12 10:25:02	ga_ls8c_ard_3-2-1_101077_2023-04-12_final
2023-04-24 09:16:01	ga_ls8c_ard_3-2-1_089090_2023-04-23_final
2023-04-28 10:25:23	ga_ls8c_ard_3-2-1_101078_2023-04-28_final
2023-04-29 11:05:26	ga_ls8c_ard_3-2-1_108070_2023-04-29_final
2023-05-04 11:25:31	ga_ls8c_ard_3-2-1_111074_2023-05-04_final
2023-05-06 09:39:50	ga_ls8c_ard_3-2-1_093088_2023-05-06_final
2023-05-06 11:16:44	ga_ls8c_ard_3-2-1_109083_2023-05-06_final
2023-05-17 09:16:45	ga_ls8c_ard_3-2-1_090077_2023-05-16_final
2023-05-19 09:06:00	ga_ls8c_ard_3-2-1_088081_2023-05-18_final
2023-05-24 09:25:46	ga_ls8c_ard_3-2-1_091084_2023-05-23_final
2023-06-01 10:10:02	ga_ls8c_ard_3-2-1_099071_2023-06-01_final
2023-06-05 11:25:27	ga_ls8c_ard_3-2-1_111074_2023-06-05_final
2023-06-09 09:24:17	ga_ls8c_ard_3-2-1_091080_2023-06-08_final
2023-06-09 11:04:22	ga_ls8c_ard_3-2-1_107083_2023-06-09_final
2023-06-26 11:46:33	ga_ls8c_ard_3-2-1_114080_2023-06-26_final
2023-07-02 11:10:45	ga_ls8c_ard_3-2-1_108083_2023-07-02_final
2023-07-09 11:11:49	ga_ls8c_ard_3-2-1_109070_2023-07-09_final
2023-07-17 10:22:47	ga_ls8c_ard_3-2-1_101071_2023-07-17_final
2023-08-03 09:28:55	ga_ls8c_ard_3-2-1_092075_2023-08-02_final
2023-08-03 11:05:48	ga_ls8c_ard_3-2-1_108070_2023-08-03_final
2023-08-07 09:06:36	ga_ls8c_ard_3-2-1_088081_2023-08-06_final
2023-08-07 10:42:17	ga_ls8c_ard_3-2-1_104073_2023-08-07_final
2023-08-12 11:02:02	ga_ls8c_ard_3-2-1_107076_2023-08-12_final
2023-08-13 10:08:01	ga_ls8c_ard_3-2-1_098080_2023-08-13_final
2023-08-15 09:57:17	ga_ls8c_ard_3-2-1_096084_2023-08-15_final
2023-08-15 09:58:05	ga_ls8c_ard_3-2-1_096086_2023-08-15_final
2023-08-28 10:59:46	ga_ls8c_ard_3-2-1_107070_2023-08-28_final
2023-08-29 10:03:45	ga_ls8c_ard_3-2-1_098069_2023-08-29_final
2023-08-30 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-08-30_final
2023-09-22 09:20:21	ga_ls8c_ard_3-2-1_090084_2023-09-21_final
2023-10-08 09:22:25	ga_ls8c_ard_3-2-1_090089_2023-10-07_final
2023-10-09 10:03:42	ga_ls8c_ard_3-2-1_097084_2023-10-09_final
2023-10-12 10:29:02	ga_ls8c_ard_3-2-1_102070_2023-10-12_final
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_final
2023-10-20 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-10-20_final
2023-10-21 10:27:37	ga_ls8c_ard_3-2-1_101082_2023-10-21_final
2023-10-23 10:08:54	ga_ls8c_ard_3-2-1_099066_2023-10-23_final
2023-10-24 10:54:10	ga_ls8c_ard_3-2-1_106071_2023-10-24_final
2023-10-27 09:46:37	ga_ls8c_ard_3-2-1_095072_2023-10-27_final
2023-10-27 09:47:01	ga_ls8c_ard_3-2-1_095073_2023-10-27_final
2023-10-31 09:28:17	ga_ls8c_ard_3-2-1_091088_2023-10-30_final
2023-11-02 09:16:43	ga_ls8c_ard_3-2-1_089090_2023-11-01_final
2023-11-03 11:36:04	ga_ls8c_ard_3-2-1_112083_2023-11-03_final
2023-11-09 09:18:02	ga_ls8c_ard_3-2-1_090078_2023-11-08_final
2023-11-14 11:11:55	ga_ls8c_ard_3-2-1_109069_2023-11-14_final
2023-11-16 09:26:16	ga_ls8c_ard_3-2-1_091083_2023-11-15_final
2023-11-16 09:26:40	ga_ls8c_ard_3-2-1_091084_2023-11-15_final
2023-11-18 10:47:14	ga_ls8c_ard_3-2-1_105069_2023-11-18_final
2023-11-21 11:21:21	ga_ls8c_ard_3-2-1_110077_2023-11-21_final
2023-11-23 11:06:12	ga_ls8c_ard_3-2-1_108070_2023-11-23_final
2023-11-25 10:54:38	ga_ls8c_ard_3-2-1_106072_2023-11-25_final
2023-12-01 11:57:35	ga_ls8c_ard_3-2-1_116075_2023-12-01_final
2023-12-01 11:57:59	ga_ls8c_ard_3-2-1_116076_2023-12-01_final
2023-12-03 11:45:59	ga_ls8c_ard_3-2-1_114077_2023-12-03_final
2023-12-05 09:52:42	ga_ls8c_ard_3-2-1_096072_2023-12-05_final
2023-12-05 09:57:54	ga_ls8c_ard_3-2-1_096085_2023-12-05_final
2023-12-08 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-12-08_final
2023-12-20 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-12-20_final
2024-01-12 10:56:06	ga_ls8c_ard_3-2-1_106076_2024-01-12_final
2024-01-15 11:26:37	ga_ls8c_ard_3-2-1_111075_2024-01-15_final
2024-01-18 10:19:01	ga_ls8c_ard_3-2-1_100076_2024-01-18_final
2024-01-19 09:26:59	ga_ls8c_ard_3-2-1_091085_2024-01-18_final
2024-01-21 09:14:36	ga_ls8c_ard_3-2-1_089085_2024-01-20_final
2024-01-27 11:51:36	ga_ls8c_ard_3-2-1_115076_2024-01-27_final
2024-01-28 09:20:42	ga_ls8c_ard_3-2-1_090085_2024-01-27_final
2024-02-04 09:22:10	ga_ls8c_ard_3-2-1_091073_2024-02-03_final
2024-02-04 09:26:57	ga_ls8c_ard_3-2-1_091085_2024-02-03_final
2024-02-05 11:44:43	ga_ls8c_ard_3-2-1_114074_2024-02-05_final
2024-02-05 11:45:55	ga_ls8c_ard_3-2-1_114077_2024-02-05_final
2024-02-06 10:47:30	ga_ls8c_ard_3-2-1_105070_2024-02-06_final
2024-02-12 10:12:49	ga_ls8c_ard_3-2-1_099076_2024-02-12_final
2024-02-13 09:20:47	ga_ls8c_ard_3-2-1_090085_2024-02-12_final
2024-02-16 09:52:27	ga_ls8c_ard_3-2-1_095087_2024-02-16_final
2024-02-19 11:57:27	ga_ls8c_ard_3-2-1_116075_2024-02-19_final
2024-02-19 11:57:51	ga_ls8c_ard_3-2-1_116076_2024-02-19_final
2024-02-22 10:47:52	ga_ls8c_ard_3-2-1_105071_2024-02-22_final
2024-02-23 11:36:18	ga_ls8c_ard_3-2-1_112084_2024-02-23_final
2024-03-10 09:52:50	ga_ls8c_ard_3-2-1_096073_2024-03-10_final
2024-03-16 09:20:30	ga_ls8c_ard_3-2-1_090085_2024-03-15_nrt
2024-03-22 10:17:50	ga_ls8c_ard_3-2-1_100074_2024-03-22_nrt
2024-03-25 09:13:23	ga_ls8c_ard_3-2-1_089083_2024-03-24_nrt
2024-04-09 11:44:13	ga_ls8c_ard_3-2-1_114074_2024-04-09_nrt
2024-04-09 11:46:37	ga_ls8c_ard_3-2-1_114080_2024-04-09_nrt
2024-04-16 11:51:07	ga_ls8c_ard_3-2-1_115076_2024-04-16_nrt

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