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
2019-03-22 09:48:22	ga_ls8c_ard_3-1-0_095078_2019-03-22_final
2019-03-22 09:48:46	ga_ls8c_ard_3-1-0_095079_2019-03-22_final
2019-03-26 09:25:38	ga_ls8c_ard_3-1-0_091083_2019-03-25_final
2019-04-07 09:46:19	ga_ls8c_ard_3-1-0_095073_2019-04-07_final
2019-04-07 09:50:42	ga_ls8c_ard_3-1-0_095084_2019-04-07_final
2019-06-26 09:47:53	ga_ls8c_ard_3-1-0_095076_2019-06-26_final
2019-06-26 09:49:05	ga_ls8c_ard_3-1-0_095079_2019-06-26_final
2019-06-26 09:50:17	ga_ls8c_ard_3-1-0_095082_2019-06-26_final
2019-07-12 09:49:08	ga_ls8c_ard_3-1-0_095079_2019-07-12_final
2019-07-16 09:23:37	ga_ls8c_ard_3-1-0_091077_2019-07-15_final
2019-07-28 09:48:01	ga_ls8c_ard_3-1-0_095076_2019-07-28_final
2019-08-13 09:49:19	ga_ls8c_ard_3-1-0_095079_2019-08-13_final
2019-08-29 09:49:23	ga_ls8c_ard_3-1-0_095079_2019-08-29_final
2019-08-29 09:51:23	ga_ls8c_ard_3-1-0_095084_2019-08-29_final
2019-09-02 09:24:41	ga_ls8c_ard_3-1-0_091079_2019-09-01_final
2019-09-14 09:48:40	ga_ls8c_ard_3-1-0_095077_2019-09-14_final
2019-09-14 09:49:04	ga_ls8c_ard_3-1-0_095078_2019-09-14_final
2019-09-30 09:46:45	ga_ls8c_ard_3-1-0_095072_2019-09-30_final
2019-11-01 09:46:48	ga_ls8c_ard_3-1-0_095072_2019-11-01_final
2019-11-01 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-11-01_final
2019-12-03 09:49:07	ga_ls8c_ard_3-1-0_095078_2019-12-03_final
2019-12-03 09:49:31	ga_ls8c_ard_3-1-0_095079_2019-12-03_final
2020-01-20 09:47:21	ga_ls8c_ard_3-1-0_095074_2020-01-20_final
2020-01-20 09:49:21	ga_ls8c_ard_3-1-0_095079_2020-01-20_final
2020-02-21 09:48:00	ga_ls8c_ard_3-1-0_095076_2020-02-21_final
2020-02-21 09:48:48	ga_ls8c_ard_3-1-0_095078_2020-02-21_final
2020-03-08 09:48:43	ga_ls8c_ard_3-1-0_095078_2020-03-08_final
2020-03-08 09:49:07	ga_ls8c_ard_3-1-0_095079_2020-03-08_final
2020-03-24 09:48:35	ga_ls8c_ard_3-1-0_095078_2020-03-24_final
2020-03-24 09:48:58	ga_ls8c_ard_3-1-0_095079_2020-03-24_final
2020-04-09 09:50:02	ga_ls8c_ard_3-1-0_095082_2020-04-09_final
2020-04-29 09:24:22	ga_ls8c_ard_3-1-0_091080_2020-04-28_final
2022-03-29 10:40:35	ga_ls8c_ard_3-2-1_104069_2022-03-29_final
2022-03-29 10:42:58	ga_ls8c_ard_3-2-1_104075_2022-03-29_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-04-01 09:35:46	ga_ls8c_ard_3-2-1_093077_2022-04-01_final
2022-04-01 09:38:34	ga_ls8c_ard_3-2-1_093084_2022-04-01_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-06 09:53:09	ga_ls8c_ard_3-2-1_096074_2022-04-06_final
2022-04-06 09:53:57	ga_ls8c_ard_3-2-1_096076_2022-04-06_final
2022-04-06 09:54:45	ga_ls8c_ard_3-2-1_096078_2022-04-06_final
2022-04-06 11:33:14	ga_ls8c_ard_3-2-1_112077_2022-04-06_final
2022-04-06 11:34:26	ga_ls8c_ard_3-2-1_112080_2022-04-06_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-15 09:46:39	ga_ls8c_ard_3-2-1_095073_2022-04-15_final
2022-04-17 09:33:29	ga_ls8c_ard_3-2-1_093071_2022-04-17_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-21 09:13:32	ga_ls8c_ard_3-2-1_089083_2022-04-20_final
2022-04-22 09:53:59	ga_ls8c_ard_3-2-1_096076_2022-04-22_final
2022-04-24 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-24_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-27 10:11:41	ga_ls8c_ard_3-2-1_099074_2022-04-27_final
2022-04-28 09:19:15	ga_ls8c_ard_3-2-1_090082_2022-04-27_final
2022-04-28 10:56:08	ga_ls8c_ard_3-2-1_106077_2022-04-28_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-04-30 10:41:24	ga_ls8c_ard_3-2-1_104071_2022-04-30_final
2022-05-01 09:46:35	ga_ls8c_ard_3-2-1_095073_2022-05-01_final
2022-05-01 09:48:35	ga_ls8c_ard_3-2-1_095078_2022-05-01_final
2022-05-02 10:32:39	ga_ls8c_ard_3-2-1_102080_2022-05-02_final
2022-05-03 09:36:15	ga_ls8c_ard_3-2-1_093078_2022-05-03_final
2022-05-03 09:37:51	ga_ls8c_ard_3-2-1_093082_2022-05-03_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-06 10:07:35	ga_ls8c_ard_3-2-1_098079_2022-05-06_final
2022-05-07 09:11:35	ga_ls8c_ard_3-2-1_089078_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-07 10:46:52	ga_ls8c_ard_3-2-1_105069_2022-05-07_final
2022-05-08 11:34:32	ga_ls8c_ard_3-2-1_112080_2022-05-08_final
2022-05-09 10:34:56	ga_ls8c_ard_3-2-1_103070_2022-05-09_final
2022-05-09 10:38:55	ga_ls8c_ard_3-2-1_103080_2022-05-09_final
2022-05-11 10:23:23	ga_ls8c_ard_3-2-1_101072_2022-05-11_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-13 10:12:38	ga_ls8c_ard_3-2-1_099076_2022-05-13_final
2022-05-13 10:14:14	ga_ls8c_ard_3-2-1_099080_2022-05-13_final
2022-05-14 09:19:25	ga_ls8c_ard_3-2-1_090082_2022-05-13_final
2022-05-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2022-05-17_final
2022-05-19 09:36:23	ga_ls8c_ard_3-2-1_093078_2022-05-19_final
2022-05-20 10:20:50	ga_ls8c_ard_3-2-1_100081_2022-05-20_final
2022-05-24 09:54:07	ga_ls8c_ard_3-2-1_096076_2022-05-24_final
2022-05-24 11:33:24	ga_ls8c_ard_3-2-1_112077_2022-05-24_final
2022-05-24 11:34:36	ga_ls8c_ard_3-2-1_112080_2022-05-24_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-26 09:42:57	ga_ls8c_ard_3-2-1_094079_2022-05-26_final
2022-05-26 11:18:38	ga_ls8c_ard_3-2-1_110071_2022-05-26_final
2022-06-02 09:48:00	ga_ls8c_ard_3-2-1_095076_2022-06-02_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-07 10:06:37	ga_ls8c_ard_3-2-1_098076_2022-06-07_final
2022-06-07 11:45:54	ga_ls8c_ard_3-2-1_114077_2022-06-07_final
2022-06-12 10:27:13	ga_ls8c_ard_3-2-1_101081_2022-06-12_final
2022-06-13 11:10:53	ga_ls8c_ard_3-2-1_108082_2022-06-13_final
2022-06-17 10:41:01	ga_ls8c_ard_3-2-1_104069_2022-06-17_final
2022-06-17 10:42:37	ga_ls8c_ard_3-2-1_104073_2022-06-17_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-18 09:50:11	ga_ls8c_ard_3-2-1_095081_2022-06-18_final
2022-06-18 09:50:35	ga_ls8c_ard_3-2-1_095082_2022-06-18_final
2022-06-20 09:39:02	ga_ls8c_ard_3-2-1_093084_2022-06-20_final
2022-06-22 09:23:30	ga_ls8c_ard_3-2-1_091076_2022-06-21_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