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
2022-01-14 10:06:46	ga_ls8c_ard_3-2-1_098076_2022-01-14_final
2022-01-20 11:08:32	ga_ls8c_ard_3-2-1_108076_2022-01-20_final
2022-02-09 09:06:51	ga_ls8c_ard_3-2-1_088081_2022-02-08_final
2022-02-12 11:17:01	ga_ls8c_ard_3-2-1_109082_2022-02-12_final
2022-02-28 09:38:51	ga_ls8c_ard_3-2-1_093084_2022-02-28_final
2022-03-02 09:28:05	ga_ls8c_ard_3-2-1_091088_2022-03-01_final
2022-03-09 09:30:38	ga_ls8c_ard_3-2-1_092079_2022-03-09_final
2022-03-23 09:44:51	ga_ls8c_ard_3-2-1_094084_2022-03-23_final
2022-03-31 10:28:36	ga_ls8c_ard_3-2-1_102070_2022-03-31_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-04 10:09:53	ga_ls8c_ard_3-2-1_098085_2022-04-04_final
2022-04-12 09:20:55	ga_ls8c_ard_3-2-1_090086_2022-04-11_final
2022-04-22 09:57:11	ga_ls8c_ard_3-2-1_096084_2022-04-22_final
2022-05-01 09:47:23	ga_ls8c_ard_3-2-1_095075_2022-05-01_final
2022-05-07 10:52:03	ga_ls8c_ard_3-2-1_105082_2022-05-07_final
2022-05-17 09:47:32	ga_ls8c_ard_3-2-1_095075_2022-05-17_final
2022-05-22 10:06:53	ga_ls8c_ard_3-2-1_098077_2022-05-22_final
2022-05-31 09:56:45	ga_ls8c_ard_3-2-1_097067_2022-05-31_final
2022-05-31 11:42:01	ga_ls8c_ard_3-2-1_113083_2022-05-31_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-11 11:23:38	ga_ls8c_ard_3-2-1_110083_2022-06-11_final
2022-06-12 10:27:13	ga_ls8c_ard_3-2-1_101081_2022-06-12_final
2022-06-26 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-06-26_final
2022-07-07 10:17:33	ga_ls8c_ard_3-2-1_100072_2022-07-07_final
2022-09-09 10:22:17	ga_ls8c_ard_3-2-1_100083_2022-09-09_final
2022-09-10 11:01:10	ga_ls8c_ard_3-2-1_107072_2022-09-10_final
2022-09-10 11:05:33	ga_ls8c_ard_3-2-1_107083_2022-09-10_final
2022-09-12 10:48:25	ga_ls8c_ard_3-2-1_105071_2022-09-12_final
2022-09-12 10:52:49	ga_ls8c_ard_3-2-1_105082_2022-09-12_final
2022-09-13 11:35:17	ga_ls8c_ard_3-2-1_112080_2022-09-13_final
2022-09-14 10:35:40	ga_ls8c_ard_3-2-1_103070_2022-09-14_final
2022-09-19 10:55:26	ga_ls8c_ard_3-2-1_106073_2022-09-19_final
2022-09-19 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-09-19_final
2022-09-23 10:28:43	ga_ls8c_ard_3-2-1_102068_2022-09-23_final
2022-09-26 09:23:32	ga_ls8c_ard_3-2-1_091075_2022-09-25_final
2022-09-26 11:04:24	ga_ls8c_ard_3-2-1_107080_2022-09-26_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-27 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-11-27_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-20 11:24:43	ga_ls8c_ard_3-2-1_110085_2022-12-20_final
2023-01-07 11:10:44	ga_ls8c_ard_3-2-1_108081_2023-01-07_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-11 10:42:24	ga_ls8c_ard_3-2-1_104072_2023-01-11_final
2023-01-17 10:08:25	ga_ls8c_ard_3-2-1_098080_2023-01-17_final
2023-01-23 09:29:24	ga_ls8c_ard_3-2-1_092075_2023-01-22_final
2023-02-02 11:46:36	ga_ls8c_ard_3-2-1_114078_2023-02-02_final
2023-02-06 11:24:40	ga_ls8c_ard_3-2-1_110085_2023-02-06_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-19 11:17:14	ga_ls8c_ard_3-2-1_109083_2023-03-19_final
2023-03-21 11:02:27	ga_ls8c_ard_3-2-1_107077_2023-03-21_final
2023-03-31 11:42:13	ga_ls8c_ard_3-2-1_113084_2023-03-31_final
2023-04-01 09:07:18	ga_ls8c_ard_3-2-1_088083_2023-03-31_final
2023-04-04 11:11:27	ga_ls8c_ard_3-2-1_109069_2023-04-04_final
2023-04-06 10:59:51	ga_ls8c_ard_3-2-1_107071_2023-04-06_final
2023-05-24 10:59:28	ga_ls8c_ard_3-2-1_107071_2023-05-24_final
2023-06-19 09:57:26	ga_ls8c_ard_3-2-1_097070_2023-06-19_final
2023-06-21 09:49:04	ga_ls8c_ard_3-2-1_095080_2023-06-21_final
2023-07-09 11:12:13	ga_ls8c_ard_3-2-1_109071_2023-07-09_final
2023-07-09 11:13:01	ga_ls8c_ard_3-2-1_109073_2023-07-09_final
2023-07-11 11:01:04	ga_ls8c_ard_3-2-1_107074_2023-07-11_final
2023-07-13 10:51:30	ga_ls8c_ard_3-2-1_105081_2023-07-13_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-08-18 10:25:50	ga_ls8c_ard_3-2-1_101078_2023-08-18_final
2023-08-21 09:20:16	ga_ls8c_ard_3-2-1_090084_2023-08-20_final
2023-08-25 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-08-25_final
2023-09-06 10:58:44	ga_ls8c_ard_3-2-1_106083_2023-09-06_final
2023-09-18 11:23:34	ga_ls8c_ard_3-2-1_110083_2023-09-18_final
2023-09-20 11:10:48	ga_ls8c_ard_3-2-1_108082_2023-09-20_final
2023-09-23 11:40:55	ga_ls8c_ard_3-2-1_113080_2023-09-23_final
2023-09-26 10:28:34	ga_ls8c_ard_3-2-1_102069_2023-09-26_final
2023-09-27 11:13:26	ga_ls8c_ard_3-2-1_109073_2023-09-27_final
2023-09-29 11:02:17	ga_ls8c_ard_3-2-1_107076_2023-09-29_final
2023-10-04 11:18:02	ga_ls8c_ard_3-2-1_110069_2023-10-04_final
2023-10-07 10:10:51	ga_ls8c_ard_3-2-1_099071_2023-10-07_final
2023-10-22 09:34:25	ga_ls8c_ard_3-2-1_092088_2023-10-22_final
2023-11-02 09:13:08	ga_ls8c_ard_3-2-1_089081_2023-11-01_final
2023-11-09 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-11-08_final
2023-11-12 11:25:26	ga_ls8c_ard_3-2-1_111072_2023-11-12_final
2023-11-14 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-11-14_final
2023-11-25 10:54:38	ga_ls8c_ard_3-2-1_106072_2023-11-25_final
2023-12-04 10:50:21	ga_ls8c_ard_3-2-1_105077_2023-12-04_final
2023-12-07 11:22:47	ga_ls8c_ard_3-2-1_110081_2023-12-07_final
2023-12-20 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-12-20_final
2023-12-21 09:52:48	ga_ls8c_ard_3-2-1_096072_2023-12-21_final
2024-01-15 09:48:08	ga_ls8c_ard_3-2-1_095076_2024-01-15_final
2024-01-20 11:44:43	ga_ls8c_ard_3-2-1_114074_2024-01-20_final
2024-01-26 11:10:44	ga_ls8c_ard_3-2-1_108082_2024-01-26_final
2024-02-02 11:13:24	ga_ls8c_ard_3-2-1_109073_2024-02-02_final
2024-02-13 10:58:52	ga_ls8c_ard_3-2-1_106083_2024-02-13_final
2024-02-14 11:42:31	ga_ls8c_ard_3-2-1_113084_2024-02-14_final
2024-02-20 09:21:45	ga_ls8c_ard_3-2-1_091072_2024-02-19_final
2024-02-27 11:09:33	ga_ls8c_ard_3-2-1_108079_2024-02-27_final
2024-02-27 11:10:45	ga_ls8c_ard_3-2-1_108082_2024-02-27_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