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
2017-03-18 09:37:43	ga_ls8c_ard_3-0-0_093082_2017-03-18_final
2017-03-18 09:38:07	ga_ls8c_ard_3-0-0_093083_2017-03-18_final
2017-03-18 09:38:31	ga_ls8c_ard_3-0-0_093084_2017-03-18_final
2017-03-18 09:38:55	ga_ls8c_ard_3-0-0_093085_2017-03-18_final
2017-03-18 09:39:19	ga_ls8c_ard_3-0-0_093086_2017-03-18_final
2017-03-18 09:39:43	ga_ls8c_ard_3-0-0_093087_2017-03-18_final
2017-03-20 09:28:08	ga_ls8c_ard_3-0-0_091089_2017-03-19_final
2017-03-20 09:28:32	ga_ls8c_ard_3-0-0_091090_2017-03-19_final
2017-03-20 09:28:56	ga_ls8c_ard_3-0-0_091091_2017-03-19_final
2017-05-07 09:27:48	ga_ls8c_ard_3-0-0_091089_2017-05-06_final
2017-05-07 09:28:12	ga_ls8c_ard_3-0-0_091090_2017-05-06_final
2017-05-07 09:28:36	ga_ls8c_ard_3-0-0_091091_2017-05-06_final
2017-05-12 09:42:01	ga_ls8c_ard_3-0-0_094078_2017-05-12_final
2017-05-12 09:42:24	ga_ls8c_ard_3-0-0_094079_2017-05-12_final
2017-05-12 09:42:48	ga_ls8c_ard_3-0-0_094080_2017-05-12_final
2017-05-12 09:43:12	ga_ls8c_ard_3-0-0_094081_2017-05-12_final
2017-05-12 09:43:36	ga_ls8c_ard_3-0-0_094082_2017-05-12_final
2017-05-12 09:44:00	ga_ls8c_ard_3-0-0_094083_2017-05-12_final
2017-05-14 09:32:52	ga_ls8c_ard_3-0-0_092086_2017-05-14_final
2017-05-14 09:33:16	ga_ls8c_ard_3-0-0_092087_2017-05-14_final
2017-05-14 09:33:40	ga_ls8c_ard_3-0-0_092088_2017-05-14_final
2017-05-14 09:34:04	ga_ls8c_ard_3-0-0_092089_2017-05-14_final
2017-05-14 09:34:28	ga_ls8c_ard_3-0-0_092090_2017-05-14_final
2017-06-24 09:28:13	ga_ls8c_ard_3-0-0_091089_2017-06-23_final
2017-06-24 09:28:37	ga_ls8c_ard_3-0-0_091090_2017-06-23_final
2017-06-24 09:29:01	ga_ls8c_ard_3-0-0_091091_2017-06-23_final
2017-06-29 09:42:23	ga_ls8c_ard_3-0-0_094078_2017-06-29_final
2017-06-29 09:42:47	ga_ls8c_ard_3-0-0_094079_2017-06-29_final
2017-06-29 09:43:11	ga_ls8c_ard_3-0-0_094080_2017-06-29_final
2017-06-29 09:43:35	ga_ls8c_ard_3-0-0_094081_2017-06-29_final
2017-06-29 09:43:59	ga_ls8c_ard_3-0-0_094082_2017-06-29_final
2017-06-29 09:44:23	ga_ls8c_ard_3-0-0_094083_2017-06-29_final
2017-07-01 09:33:14	ga_ls8c_ard_3-0-0_092086_2017-07-01_final
2017-07-01 09:33:38	ga_ls8c_ard_3-0-0_092087_2017-07-01_final
2017-07-01 09:34:02	ga_ls8c_ard_3-0-0_092088_2017-07-01_final
2017-07-01 09:34:26	ga_ls8c_ard_3-0-0_092089_2017-07-01_final
2017-07-01 09:34:49	ga_ls8c_ard_3-0-0_092090_2017-07-01_final
2017-07-10 09:28:16	ga_ls8c_ard_3-0-0_091089_2017-07-09_final
2017-07-10 09:28:40	ga_ls8c_ard_3-0-0_091090_2017-07-09_final
2017-07-10 09:29:04	ga_ls8c_ard_3-0-0_091091_2017-07-09_final
2017-07-13 09:51:12	ga_ls8c_ard_3-0-0_096069_2017-07-13_final
2017-07-13 09:51:36	ga_ls8c_ard_3-0-0_096070_2017-07-13_final
2017-07-13 09:51:59	ga_ls8c_ard_3-0-0_096071_2017-07-13_final
2017-07-13 09:52:23	ga_ls8c_ard_3-0-0_096072_2017-07-13_final
2017-07-13 09:52:47	ga_ls8c_ard_3-0-0_096073_2017-07-13_final
2017-07-13 09:53:11	ga_ls8c_ard_3-0-0_096074_2017-07-13_final
2017-07-13 09:53:35	ga_ls8c_ard_3-0-0_096075_2017-07-13_final
2017-07-17 09:33:17	ga_ls8c_ard_3-0-0_092086_2017-07-17_final
2017-07-17 09:33:41	ga_ls8c_ard_3-0-0_092087_2017-07-17_final
2017-07-17 09:34:05	ga_ls8c_ard_3-0-0_092088_2017-07-17_final
2017-07-17 09:34:29	ga_ls8c_ard_3-0-0_092089_2017-07-17_final
2017-07-17 09:34:53	ga_ls8c_ard_3-0-0_092090_2017-07-17_final
2017-07-29 09:51:20	ga_ls8c_ard_3-0-0_096069_2017-07-29_final
2017-07-29 09:51:44	ga_ls8c_ard_3-0-0_096070_2017-07-29_final
2017-07-29 09:52:08	ga_ls8c_ard_3-0-0_096071_2017-07-29_final
2017-07-29 09:52:31	ga_ls8c_ard_3-0-0_096072_2017-07-29_final
2017-07-29 09:52:55	ga_ls8c_ard_3-0-0_096073_2017-07-29_final
2017-07-29 09:53:19	ga_ls8c_ard_3-0-0_096074_2017-07-29_final
2017-08-25 09:38:07	ga_ls8c_ard_3-0-0_093082_2017-08-25_final
2017-08-25 09:38:31	ga_ls8c_ard_3-0-0_093083_2017-08-25_final
2017-08-25 09:38:55	ga_ls8c_ard_3-0-0_093084_2017-08-25_final
2017-08-25 09:39:19	ga_ls8c_ard_3-0-0_093085_2017-08-25_final
2017-08-25 09:39:43	ga_ls8c_ard_3-0-0_093086_2017-08-25_final
2017-08-25 09:40:07	ga_ls8c_ard_3-0-0_093087_2017-08-25_final
2017-08-27 09:28:34	ga_ls8c_ard_3-0-0_091089_2017-08-26_final
2017-08-27 09:28:58	ga_ls8c_ard_3-0-0_091090_2017-08-26_final
2017-08-27 09:29:22	ga_ls8c_ard_3-0-0_091091_2017-08-26_final
2021-09-23 09:28:46	ga_ls8c_ard_3-2-0_091089_2021-09-22_final
2021-09-23 09:29:34	ga_ls8c_ard_3-2-0_091091_2021-09-22_final
2021-09-26 09:51:42	ga_ls8c_ard_3-2-0_096069_2021-09-26_final
2021-09-26 09:52:06	ga_ls8c_ard_3-2-0_096070_2021-09-26_final
2021-09-26 09:52:30	ga_ls8c_ard_3-2-0_096071_2021-09-26_final
2021-09-26 09:52:54	ga_ls8c_ard_3-2-0_096072_2021-09-26_final
2021-09-26 09:53:18	ga_ls8c_ard_3-2-0_096073_2021-09-26_final
2021-09-26 09:53:42	ga_ls8c_ard_3-2-0_096074_2021-09-26_final
2021-09-30 09:33:48	ga_ls8c_ard_3-2-0_092086_2021-09-30_final
2021-09-30 09:34:12	ga_ls8c_ard_3-2-0_092087_2021-09-30_final
2021-09-30 09:34:36	ga_ls8c_ard_3-2-0_092088_2021-09-30_final
2021-09-30 09:35:00	ga_ls8c_ard_3-2-0_092089_2021-09-30_final
2021-09-30 09:35:24	ga_ls8c_ard_3-2-0_092090_2021-09-30_final
2021-10-05 09:47:35	ga_ls8c_ard_3-2-0_095074_2021-10-05_final
2021-10-05 09:47:59	ga_ls8c_ard_3-2-0_095075_2021-10-05_final
2021-10-05 09:48:23	ga_ls8c_ard_3-2-0_095076_2021-10-05_final
2021-10-05 09:48:47	ga_ls8c_ard_3-2-0_095077_2021-10-05_final
2021-10-05 09:49:11	ga_ls8c_ard_3-2-0_095078_2021-10-05_final
2021-10-05 09:49:35	ga_ls8c_ard_3-2-0_095079_2021-10-05_final
2021-10-07 09:38:25	ga_ls8c_ard_3-2-0_093082_2021-10-07_final
2021-10-07 09:38:49	ga_ls8c_ard_3-2-0_093083_2021-10-07_final
2021-10-07 09:39:13	ga_ls8c_ard_3-2-0_093084_2021-10-07_final
2021-10-07 09:39:37	ga_ls8c_ard_3-2-0_093085_2021-10-07_final
2021-10-07 09:40:01	ga_ls8c_ard_3-2-0_093086_2021-10-07_final
2021-10-07 09:40:25	ga_ls8c_ard_3-2-0_093087_2021-10-07_final
2021-10-09 09:28:52	ga_ls8c_ard_3-2-0_091089_2021-10-08_final
2021-10-09 09:29:16	ga_ls8c_ard_3-2-0_091090_2021-10-08_final
2021-10-09 09:29:40	ga_ls8c_ard_3-2-0_091091_2021-10-08_final
2021-10-14 09:43:02	ga_ls8c_ard_3-2-0_094078_2021-10-14_final
2021-10-14 09:43:26	ga_ls8c_ard_3-2-0_094079_2021-10-14_final
2021-10-14 09:43:50	ga_ls8c_ard_3-2-0_094080_2021-10-14_final
2021-10-14 09:44:14	ga_ls8c_ard_3-2-0_094081_2021-10-14_final
2021-10-14 09:44:38	ga_ls8c_ard_3-2-0_094082_2021-10-14_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