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 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-01-14_final
2022-01-27 11:15:28	ga_ls8c_ard_3-2-1_109078_2022-01-27_final
2022-02-05 09:29:59	ga_ls8c_ard_3-2-1_092077_2022-02-04_final
2022-02-05 11:10:52	ga_ls8c_ard_3-2-1_108082_2022-02-05_final
2022-02-08 10:00:53	ga_ls8c_ard_3-2-1_097077_2022-02-08_final
2022-02-12 09:36:32	ga_ls8c_ard_3-2-1_093078_2022-02-12_final
2022-02-12 09:38:56	ga_ls8c_ard_3-2-1_093084_2022-02-12_final
2022-02-17 09:53:26	ga_ls8c_ard_3-2-1_096074_2022-02-17_final
2022-02-18 10:36:18	ga_ls8c_ard_3-2-1_103073_2022-02-18_final
2022-02-18 10:37:29	ga_ls8c_ard_3-2-1_103076_2022-02-18_final
2022-02-21 09:32:17	ga_ls8c_ard_3-2-1_092083_2022-02-21_final
2022-02-21 11:05:35	ga_ls8c_ard_3-2-1_108069_2022-02-21_final
2022-02-21 11:09:58	ga_ls8c_ard_3-2-1_108080_2022-02-21_final
2022-03-17 11:58:06	ga_ls8c_ard_3-2-1_116077_2022-03-17_final
2022-03-23 11:23:20	ga_ls8c_ard_3-2-1_110083_2022-03-23_final
2022-03-27 10:56:10	ga_ls8c_ard_3-2-1_106077_2022-03-27_final
2022-04-01 09:38:34	ga_ls8c_ard_3-2-1_093084_2022-04-01_final
2022-04-01 11:15:03	ga_ls8c_ard_3-2-1_109078_2022-04-01_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-26 09:32:02	ga_ls8c_ard_3-2-1_092083_2022-04-26_final
2022-05-08 11:32:56	ga_ls8c_ard_3-2-1_112076_2022-05-08_final
2022-05-23 10:52:32	ga_ls8c_ard_3-2-1_105083_2022-05-23_final
2022-05-24 09:54:07	ga_ls8c_ard_3-2-1_096076_2022-05-24_final
2022-05-29 10:11:52	ga_ls8c_ard_3-2-1_099074_2022-05-29_final
2022-06-15 09:20:04	ga_ls8c_ard_3-2-1_090083_2022-06-14_final
2022-06-17 10:41:49	ga_ls8c_ard_3-2-1_104071_2022-06-17_final
2022-06-27 09:44:03	ga_ls8c_ard_3-2-1_094081_2022-06-27_final
2022-07-03 10:41:04	ga_ls8c_ard_3-2-1_104069_2022-07-03_final
2022-07-07 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-07-07_final
2022-07-19 10:41:54	ga_ls8c_ard_3-2-1_104071_2022-07-19_final
2022-07-19 10:45:53	ga_ls8c_ard_3-2-1_104081_2022-07-19_final
2022-07-27 09:53:21	ga_ls8c_ard_3-2-1_096073_2022-07-27_final
2022-08-08 10:18:59	ga_ls8c_ard_3-2-1_100075_2022-08-08_final
2022-08-15 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-08-15_final
2022-08-15 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-08-15_final
2022-08-19 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-08-19_final
2022-08-25 11:03:06	ga_ls8c_ard_3-2-1_107077_2022-08-25_final
2022-09-05 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-09-05_final
2022-09-08 11:12:19	ga_ls8c_ard_3-2-1_109069_2022-09-08_final
2022-09-08 11:12:43	ga_ls8c_ard_3-2-1_109070_2022-09-08_final
2022-09-17 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-09-17_final
2022-09-17 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-09-17_final
2022-09-29 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-09-29_final
2022-10-13 10:08:38	ga_ls8c_ard_3-2-1_098080_2022-10-13_final
2022-10-18 10:26:49	ga_ls8c_ard_3-2-1_101079_2022-10-18_final
2022-10-22 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-22_final
2022-10-22 11:39:26	ga_ls8c_ard_3-2-1_113075_2022-10-22_final
2022-10-28 09:25:54	ga_ls8c_ard_3-2-1_091081_2022-10-27_final
2022-10-29 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-10-29_final
2022-11-04 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-11-04_final
2022-11-11 09:36:38	ga_ls8c_ard_3-2-1_093077_2022-11-11_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-11-24 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-11-24_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-11-27 11:15:29	ga_ls8c_ard_3-2-1_109077_2022-11-27_final
2022-11-29 11:03:55	ga_ls8c_ard_3-2-1_107079_2022-11-29_final
2022-12-05 10:26:50	ga_ls8c_ard_3-2-1_101079_2022-12-05_final
2022-12-11 11:30:12	ga_ls8c_ard_3-2-1_111083_2022-12-11_final
2022-12-13 09:37:21	ga_ls8c_ard_3-2-1_093079_2022-12-13_final
2022-12-13 11:15:26	ga_ls8c_ard_3-2-1_109077_2022-12-13_final
2022-12-14 10:18:36	ga_ls8c_ard_3-2-1_100074_2022-12-14_final
2022-12-16 10:07:01	ga_ls8c_ard_3-2-1_098076_2022-12-16_final
2022-12-18 09:53:26	ga_ls8c_ard_3-2-1_096073_2022-12-18_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-27 09:50:00	ga_ls8c_ard_3-2-1_095080_2022-12-27_final
2023-01-01 10:06:57	ga_ls8c_ard_3-2-1_098076_2023-01-01_final
2023-01-03 09:53:00	ga_ls8c_ard_3-2-1_096072_2023-01-03_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-05 09:43:26	ga_ls8c_ard_3-2-1_094079_2023-01-05_final
2023-01-07 09:32:15	ga_ls8c_ard_3-2-1_092082_2023-01-07_final
2023-01-09 10:57:10	ga_ls8c_ard_3-2-1_106078_2023-01-09_final
2023-01-12 09:49:57	ga_ls8c_ard_3-2-1_095080_2023-01-12_final
2023-01-21 11:22:13	ga_ls8c_ard_3-2-1_110079_2023-01-21_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-02-05 10:35:49	ga_ls8c_ard_3-2-1_103071_2023-02-05_final
2023-02-07 10:26:15	ga_ls8c_ard_3-2-1_101078_2023-02-07_final
2023-02-08 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-02-08_final
2023-02-13 09:49:53	ga_ls8c_ard_3-2-1_095080_2023-02-13_final
2023-02-13 09:51:29	ga_ls8c_ard_3-2-1_095084_2023-02-13_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-16 11:58:02	ga_ls8c_ard_3-2-1_116076_2023-02-16_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_final
2023-03-12 11:08:19	ga_ls8c_ard_3-2-1_108076_2023-03-12_final
2023-03-13 10:11:54	ga_ls8c_ard_3-2-1_099074_2023-03-13_final
2023-03-14 09:18:40	ga_ls8c_ard_3-2-1_090080_2023-03-13_final
2023-03-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2023-03-17_final
2023-04-12 10:24:38	ga_ls8c_ard_3-2-1_101076_2023-04-12_final
2023-04-13 11:09:54	ga_ls8c_ard_3-2-1_108081_2023-04-13_final
2023-04-17 10:44:45	ga_ls8c_ard_3-2-1_104080_2023-04-17_final
2023-04-18 11:29:12	ga_ls8c_ard_3-2-1_111083_2023-04-18_final
2023-05-04 09:49:26	ga_ls8c_ard_3-2-1_095081_2023-05-04_final
2023-05-06 11:15:08	ga_ls8c_ard_3-2-1_109079_2023-05-06_final
2023-05-09 11:45:11	ga_ls8c_ard_3-2-1_114077_2023-05-09_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