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
2022-07-27 09:53:45	ga_ls8c_ard_3-2-1_096074_2022-07-27_final
2022-07-29 09:44:36	ga_ls8c_ard_3-2-1_094082_2022-07-29_final
2022-08-21 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-08-21_final
2022-08-21 11:29:25	ga_ls8c_ard_3-2-1_111081_2022-08-21_final
2022-08-25 09:27:01	ga_ls8c_ard_3-2-1_091084_2022-08-24_final
2022-08-31 10:26:25	ga_ls8c_ard_3-2-1_101078_2022-08-31_final
2022-09-01 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-09-01_final
2022-09-01 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-09-01_final
2022-09-04 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-09-04_final
2022-09-08 11:16:18	ga_ls8c_ard_3-2-1_109079_2022-09-08_final
2022-09-12 09:15:31	ga_ls8c_ard_3-2-1_089086_2022-09-11_final
2022-09-19 09:18:09	ga_ls8c_ard_3-2-1_090077_2022-09-18_final
2022-09-27 11:47:40	ga_ls8c_ard_3-2-1_114080_2022-09-27_final
2022-09-29 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-09-29_final
2022-10-07 10:42:13	ga_ls8c_ard_3-2-1_104071_2022-10-07_final
2022-10-12 09:24:36	ga_ls8c_ard_3-2-1_091078_2022-10-11_final
2022-10-15 09:55:29	ga_ls8c_ard_3-2-1_096078_2022-10-15_final
2022-10-18 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-10-18_final
2022-10-27 11:58:25	ga_ls8c_ard_3-2-1_116076_2022-10-27_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-11 11:15:31	ga_ls8c_ard_3-2-1_109077_2022-11-11_final
2022-11-27 11:15:53	ga_ls8c_ard_3-2-1_109078_2022-11-27_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-03 10:38:24	ga_ls8c_ard_3-2-1_103077_2022-12-03_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-11 11:30:12	ga_ls8c_ard_3-2-1_111083_2022-12-11_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 11:47:30	ga_ls8c_ard_3-2-1_114080_2022-12-16_final
2022-12-25 09:58:21	ga_ls8c_ard_3-2-1_097070_2022-12-25_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-24 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-01-24_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-01-26 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-26_final
2023-02-03 10:48:11	ga_ls8c_ard_3-2-1_105071_2023-02-03_final
2023-02-05 10:37:49	ga_ls8c_ard_3-2-1_103076_2023-02-05_final
2023-02-06 09:46:11	ga_ls8c_ard_3-2-1_094086_2023-02-06_final
2023-02-26 09:19:33	ga_ls8c_ard_3-2-1_090082_2023-02-25_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-03-27 10:24:54	ga_ls8c_ard_3-2-1_101076_2023-03-27_final
2023-04-03 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-04-03_final
2023-04-07 10:05:48	ga_ls8c_ard_3-2-1_098075_2023-04-07_final
2023-04-13 11:09:30	ga_ls8c_ard_3-2-1_108080_2023-04-13_final
2023-04-25 09:52:54	ga_ls8c_ard_3-2-1_096074_2023-04-25_final
2023-04-26 10:36:57	ga_ls8c_ard_3-2-1_103076_2023-04-26_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-05-11 09:55:29	ga_ls8c_ard_3-2-1_096081_2023-05-11_final
2023-05-13 09:44:42	ga_ls8c_ard_3-2-1_094085_2023-05-13_final
2023-05-23 10:20:12	ga_ls8c_ard_3-2-1_100081_2023-05-23_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-24 09:24:11	ga_ls8c_ard_3-2-1_091080_2023-05-23_final
2023-06-07 11:11:07	ga_ls8c_ard_3-2-1_109069_2023-06-07_final
2023-06-10 11:45:15	ga_ls8c_ard_3-2-1_114077_2023-06-10_final
2023-06-10 11:46:03	ga_ls8c_ard_3-2-1_114079_2023-06-10_final
2023-06-13 10:34:06	ga_ls8c_ard_3-2-1_103069_2023-06-13_final
2023-06-21 11:25:57	ga_ls8c_ard_3-2-1_111075_2023-06-21_final
2023-06-22 10:32:19	ga_ls8c_ard_3-2-1_102080_2023-06-22_final
2023-06-23 09:33:07	ga_ls8c_ard_3-2-1_093071_2023-06-23_final
2023-06-23 11:12:00	ga_ls8c_ard_3-2-1_109071_2023-06-23_final
2023-06-24 10:17:12	ga_ls8c_ard_3-2-1_100073_2023-06-24_final
2023-06-26 10:03:17	ga_ls8c_ard_3-2-1_098069_2023-06-26_final
2023-06-28 09:51:45	ga_ls8c_ard_3-2-1_096071_2023-06-28_final
2023-07-05 09:58:49	ga_ls8c_ard_3-2-1_097073_2023-07-05_final
2023-07-09 09:34:31	ga_ls8c_ard_3-2-1_093074_2023-07-09_final
2023-07-11 11:02:39	ga_ls8c_ard_3-2-1_107078_2023-07-11_final
2023-07-14 11:31:34	ga_ls8c_ard_3-2-1_112073_2023-07-14_final
2023-07-16 11:20:48	ga_ls8c_ard_3-2-1_110077_2023-07-16_final
2023-07-19 10:12:25	ga_ls8c_ard_3-2-1_099076_2023-07-19_final
2023-07-20 09:19:35	ga_ls8c_ard_3-2-1_090083_2023-07-19_final
2023-07-23 11:29:01	ga_ls8c_ard_3-2-1_111082_2023-07-23_final
2023-07-25 11:12:42	ga_ls8c_ard_3-2-1_109072_2023-07-25_final
2023-08-01 09:45:39	ga_ls8c_ard_3-2-1_094086_2023-08-01_final
2023-08-12 11:00:26	ga_ls8c_ard_3-2-1_107072_2023-08-12_final
2023-08-13 11:46:07	ga_ls8c_ard_3-2-1_114078_2023-08-13_final
2023-08-14 09:12:25	ga_ls8c_ard_3-2-1_089080_2023-08-13_final
2023-08-19 11:09:30	ga_ls8c_ard_3-2-1_108079_2023-08-19_final
2023-08-23 09:07:31	ga_ls8c_ard_3-2-1_088083_2023-08-22_final
2023-08-26 11:17:19	ga_ls8c_ard_3-2-1_109083_2023-08-26_final
2023-08-30 10:52:36	ga_ls8c_ard_3-2-1_105083_2023-08-30_final
2023-09-02 09:45:48	ga_ls8c_ard_3-2-1_094086_2023-09-02_final
2023-09-13 09:28:07	ga_ls8c_ard_3-2-1_091088_2023-09-12_final
2023-09-21 11:53:16	ga_ls8c_ard_3-2-1_115080_2023-09-21_final
2023-09-27 09:36:57	ga_ls8c_ard_3-2-1_093079_2023-09-27_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-10-10 10:41:23	ga_ls8c_ard_3-2-1_104070_2023-10-10_final
2023-10-18 09:52:20	ga_ls8c_ard_3-2-1_096071_2023-10-18_final
2023-10-22 09:31:37	ga_ls8c_ard_3-2-1_092081_2023-10-22_final
2023-11-01 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-11-01_final
2023-11-01 11:45:15	ga_ls8c_ard_3-2-1_114075_2023-11-01_final
2023-11-03 09:53:11	ga_ls8c_ard_3-2-1_096073_2023-11-03_final
2023-11-06 10:27:16	ga_ls8c_ard_3-2-1_101081_2023-11-06_final
2023-11-07 09:34:49	ga_ls8c_ard_3-2-1_092089_2023-11-07_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-15 10:17:54	ga_ls8c_ard_3-2-1_100073_2023-11-15_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