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
2013-09-06 09:43:03	ga_ls8c_ard_3-0-0_094074_2013-09-06_final
2014-04-02 09:45:37	ga_ls8c_ard_3-0-0_094085_2014-04-02_final
2014-10-02 09:46:34	ga_ls8c_ard_3-0-0_095072_2014-10-02_final
2015-10-30 09:44:43	ga_ls8c_ard_3-0-0_094083_2015-10-30_final
2015-11-22 09:46:57	ga_ls8c_ard_3-0-0_095073_2015-11-22_final
2016-05-25 09:44:38	ga_ls8c_ard_3-0-0_094084_2016-05-25_final
2016-08-29 09:45:35	ga_ls8c_ard_3-0-0_094085_2016-08-29_final
2017-04-26 09:43:33	ga_ls8c_ard_3-0-0_094082_2017-04-26_final
2017-04-26 09:45:09	ga_ls8c_ard_3-0-0_094086_2017-04-26_final
2017-05-02 09:06:24	ga_ls8c_ard_3-0-0_088082_2017-05-01_final
2017-06-13 09:44:42	ga_ls8c_ard_3-0-0_094084_2017-06-13_final
2018-11-07 09:40:57	ga_ls8c_ard_3-0-0_094074_2018-11-07_final
2019-01-10 09:46:04	ga_ls8c_ard_3-0-0_094087_2019-01-10_final
2019-06-03 09:45:09	ga_ls8c_ard_3-0-0_094085_2019-06-03_final
2019-08-06 09:40:42	ga_ls8c_ard_3-1-0_094073_2019-08-06_final
2019-09-14 09:46:40	ga_ls8c_ard_3-1-0_095072_2019-09-14_final
2020-07-14 09:46:16	ga_ls8c_ard_3-1-0_095072_2020-07-14_final
2020-10-11 09:46:32	ga_ls8c_ard_3-1-0_094087_2020-10-11_final
2022-01-14 10:07:58	ga_ls8c_ard_3-2-1_098079_2022-01-14_final
2023-02-02 10:03:44	ga_ls8c_ard_3-2-1_098068_2023-02-02_final
2023-02-11 11:41:57	ga_ls8c_ard_3-2-1_113082_2023-02-11_final
2023-02-17 09:25:31	ga_ls8c_ard_3-2-1_091081_2023-02-16_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-22 11:22:49	ga_ls8c_ard_3-2-1_110081_2023-02-22_final
2023-02-26 10:58:26	ga_ls8c_ard_3-2-1_106082_2023-02-26_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-01 11:28:56	ga_ls8c_ard_3-2-1_111081_2023-03-01_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-06 10:07:45	ga_ls8c_ard_3-2-1_098079_2023-03-06_final
2023-03-08 11:35:50	ga_ls8c_ard_3-2-1_112083_2023-03-08_final
2023-03-10 09:44:11	ga_ls8c_ard_3-2-1_094082_2023-03-10_final
2023-03-12 11:07:07	ga_ls8c_ard_3-2-1_108073_2023-03-12_final
2023-03-14 10:54:45	ga_ls8c_ard_3-2-1_106073_2023-03-14_final
2023-03-20 10:22:00	ga_ls8c_ard_3-2-1_100084_2023-03-20_final
2023-03-21 11:01:39	ga_ls8c_ard_3-2-1_107075_2023-03-21_final
2023-03-23 10:46:03	ga_ls8c_ard_3-2-1_105067_2023-03-23_final
2023-03-29 10:14:08	ga_ls8c_ard_3-2-1_099080_2023-03-29_final
2023-04-02 09:47:22	ga_ls8c_ard_3-2-1_095075_2023-04-02_final
2023-04-07 10:03:00	ga_ls8c_ard_3-2-1_098068_2023-04-07_final
2023-04-11 11:22:40	ga_ls8c_ard_3-2-1_110082_2023-04-11_final
2023-04-12 10:23:51	ga_ls8c_ard_3-2-1_101074_2023-04-12_final
2023-04-13 11:10:42	ga_ls8c_ard_3-2-1_108083_2023-04-13_final
2023-04-25 09:56:53	ga_ls8c_ard_3-2-1_096084_2023-04-25_final
2023-04-25 09:57:41	ga_ls8c_ard_3-2-1_096086_2023-04-25_final
2023-04-27 11:22:36	ga_ls8c_ard_3-2-1_110082_2023-04-27_final
2023-05-10 09:13:51	ga_ls8c_ard_3-2-1_089085_2023-05-09_final
2023-05-13 09:39:55	ga_ls8c_ard_3-2-1_094073_2023-05-13_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-16 11:51:40	ga_ls8c_ard_3-2-1_115078_2023-05-16_final
2023-05-17 09:20:21	ga_ls8c_ard_3-2-1_090086_2023-05-16_final
2023-05-24 09:26:10	ga_ls8c_ard_3-2-1_091085_2023-05-23_final
2023-05-24 10:59:28	ga_ls8c_ard_3-2-1_107071_2023-05-24_final
2023-05-30 10:22:00	ga_ls8c_ard_3-2-1_101070_2023-05-30_final
2023-05-31 09:28:22	ga_ls8c_ard_3-2-1_092075_2023-05-30_final
2023-06-02 09:16:48	ga_ls8c_ard_3-2-1_090077_2023-06-01_final
2023-06-08 10:20:42	ga_ls8c_ard_3-2-1_100082_2023-06-08_final
2023-06-09 09:22:41	ga_ls8c_ard_3-2-1_091076_2023-06-08_final
2023-06-10 10:08:45	ga_ls8c_ard_3-2-1_098083_2023-06-10_final
2023-06-19 10:01:02	ga_ls8c_ard_3-2-1_097079_2023-06-19_final
2023-06-25 11:01:40	ga_ls8c_ard_3-2-1_107076_2023-06-25_final
2023-06-25 11:03:16	ga_ls8c_ard_3-2-1_107080_2023-06-25_final
2023-06-27 09:12:52	ga_ls8c_ard_3-2-1_089082_2023-06-26_final
2023-06-30 09:43:48	ga_ls8c_ard_3-2-1_094082_2023-06-30_final
2023-07-06 10:42:29	ga_ls8c_ard_3-2-1_104074_2023-07-06_final
2023-07-06 10:42:53	ga_ls8c_ard_3-2-1_104075_2023-07-06_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-07-19 10:15:13	ga_ls8c_ard_3-2-1_099083_2023-07-19_final
2023-07-21 09:59:16	ga_ls8c_ard_3-2-1_097074_2023-07-21_final
2023-07-30 09:55:12	ga_ls8c_ard_3-2-1_096079_2023-07-30_final
2023-08-05 10:55:03	ga_ls8c_ard_3-2-1_106074_2023-08-05_final
2023-08-11 10:18:45	ga_ls8c_ard_3-2-1_100076_2023-08-11_final
2023-08-18 10:25:02	ga_ls8c_ard_3-2-1_101076_2023-08-18_final
2023-08-20 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-08-20_final
2023-09-04 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-09-04_final
2023-09-06 10:53:57	ga_ls8c_ard_3-2-1_106071_2023-09-06_final
2023-09-11 09:34:52	ga_ls8c_ard_3-2-1_093074_2023-09-11_final
2023-09-13 11:02:12	ga_ls8c_ard_3-2-1_107076_2023-09-13_final
2023-09-22 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-09-21_final
2023-09-26 10:28:34	ga_ls8c_ard_3-2-1_102069_2023-09-26_final
2023-09-28 10:21:49	ga_ls8c_ard_3-2-1_100083_2023-09-28_final
2023-09-28 11:57:54	ga_ls8c_ard_3-2-1_116076_2023-09-28_final
2023-09-29 11:05:29	ga_ls8c_ard_3-2-1_107084_2023-09-29_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-08 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-10-08_final
2023-10-17 10:47:58	ga_ls8c_ard_3-2-1_105071_2023-10-17_final
2023-10-17 10:48:46	ga_ls8c_ard_3-2-1_105073_2023-10-17_final
2023-10-22 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-10-22_final
2023-11-05 11:23:18	ga_ls8c_ard_3-2-1_110082_2023-11-05_final
2023-11-09 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-11-08_final
2023-11-14 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-11-14_final
2023-11-17 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-11-17_final
2023-11-18 09:14:20	ga_ls8c_ard_3-2-1_089084_2023-11-17_final
2023-11-19 09:52:25	ga_ls8c_ard_3-2-1_096071_2023-11-19_final
2023-11-20 10:35:17	ga_ls8c_ard_3-2-1_103070_2023-11-20_final
2023-11-24 10:12:58	ga_ls8c_ard_3-2-1_099076_2023-11-24_nrt
2023-11-24 11:52:15	ga_ls8c_ard_3-2-1_115077_2023-11-24_nrt

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