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
2016-02-14 09:27:13	ga_ls8c_ard_3-1-0_091086_2016-02-13_final
2019-03-22 09:50:46	ga_ls8c_ard_3-1-0_095084_2019-03-22_final
2019-03-29 09:57:20	ga_ls8c_ard_3-1-0_096085_2019-03-29_final
2019-04-11 09:23:58	ga_ls8c_ard_3-1-0_091079_2019-04-10_final
2019-04-14 09:56:03	ga_ls8c_ard_3-1-0_096082_2019-04-14_final
2019-07-16 09:23:37	ga_ls8c_ard_3-1-0_091077_2019-07-15_final
2019-08-04 09:57:51	ga_ls8c_ard_3-1-0_096085_2019-08-04_final
2019-08-13 09:47:19	ga_ls8c_ard_3-1-0_095074_2019-08-13_final
2019-08-13 09:47:43	ga_ls8c_ard_3-1-0_095075_2019-08-13_final
2019-08-17 09:24:37	ga_ls8c_ard_3-1-0_091079_2019-08-16_final
2019-08-29 09:49:47	ga_ls8c_ard_3-1-0_095080_2019-08-29_final
2019-09-14 09:51:04	ga_ls8c_ard_3-1-0_095083_2019-09-14_final
2019-10-16 09:48:23	ga_ls8c_ard_3-1-0_095076_2019-10-16_final
2019-10-16 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-10-16_final
2019-10-20 09:20:29	ga_ls8c_ard_3-1-0_091068_2019-10-19_final
2019-11-01 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-11-01_final
2019-11-08 09:53:21	ga_ls8c_ard_3-1-0_096073_2019-11-08_final
2019-11-21 09:24:24	ga_ls8c_ard_3-1-0_091078_2019-11-20_final
2019-12-07 09:24:23	ga_ls8c_ard_3-1-0_091078_2019-12-06_final
2019-12-23 09:24:21	ga_ls8c_ard_3-1-0_091078_2019-12-22_final
2020-01-08 09:28:16	ga_ls8c_ard_3-1-0_091088_2020-01-07_final
2020-01-20 09:48:09	ga_ls8c_ard_3-1-0_095076_2020-01-20_final
2020-02-21 09:49:36	ga_ls8c_ard_3-1-0_095080_2020-02-21_final
2020-03-08 09:47:55	ga_ls8c_ard_3-1-0_095076_2020-03-08_final
2020-03-08 09:51:06	ga_ls8c_ard_3-1-0_095084_2020-03-08_final
2020-03-24 09:46:59	ga_ls8c_ard_3-1-0_095074_2020-03-24_final
2020-03-24 09:48:11	ga_ls8c_ard_3-1-0_095077_2020-03-24_final
2020-03-31 09:56:17	ga_ls8c_ard_3-1-0_096082_2020-03-31_final
2020-04-25 09:47:07	ga_ls8c_ard_3-1-0_095075_2020-04-25_final
2020-04-25 09:49:07	ga_ls8c_ard_3-1-0_095080_2020-04-25_final
2020-04-29 09:23:58	ga_ls8c_ard_3-1-0_091079_2020-04-28_final
2022-03-29 10:44:10	ga_ls8c_ard_3-2-1_104078_2022-03-29_final
2022-03-30 09:49:44	ga_ls8c_ard_3-2-1_095081_2022-03-30_final
2022-03-30 11:27:01	ga_ls8c_ard_3-2-1_111077_2022-03-30_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-02 11:58:19	ga_ls8c_ard_3-2-1_116078_2022-04-02_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-10 09:29:40	ga_ls8c_ard_3-2-1_092077_2022-04-09_final
2022-04-10 09:30:04	ga_ls8c_ard_3-2-1_092078_2022-04-10_final
2022-04-10 09:30:28	ga_ls8c_ard_3-2-1_092079_2022-04-10_final
2022-04-12 09:19:19	ga_ls8c_ard_3-2-1_090082_2022-04-11_final
2022-04-13 10:00:11	ga_ls8c_ard_3-2-1_097076_2022-04-13_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-13 11:40:40	ga_ls8c_ard_3-2-1_113080_2022-04-13_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-16 10:31:30	ga_ls8c_ard_3-2-1_102077_2022-04-16_final
2022-04-16 10:32:18	ga_ls8c_ard_3-2-1_102079_2022-04-16_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-20 10:06:22	ga_ls8c_ard_3-2-1_098076_2022-04-20_final
2022-04-20 10:08:21	ga_ls8c_ard_3-2-1_098081_2022-04-20_final
2022-04-22 11:32:29	ga_ls8c_ard_3-2-1_112075_2022-04-22_final
2022-04-22 11:34:52	ga_ls8c_ard_3-2-1_112081_2022-04-22_final
2022-04-24 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-24_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-26 11:10:31	ga_ls8c_ard_3-2-1_108082_2022-04-26_final
2022-04-28 09:18:27	ga_ls8c_ard_3-2-1_090080_2022-04-27_final
2022-04-29 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-04-30 10:41:48	ga_ls8c_ard_3-2-1_104072_2022-04-30_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_final
2022-05-01 09:49:47	ga_ls8c_ard_3-2-1_095081_2022-05-01_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-05 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-05-05_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-08 09:56:03	ga_ls8c_ard_3-2-1_096081_2022-05-08_final
2022-05-08 09:56:27	ga_ls8c_ard_3-2-1_096082_2022-05-08_final
2022-05-11 10:23:23	ga_ls8c_ard_3-2-1_101072_2022-05-11_final
2022-05-13 10:11:50	ga_ls8c_ard_3-2-1_099074_2022-05-13_final
2022-05-14 09:18:37	ga_ls8c_ard_3-2-1_090080_2022-05-13_final
2022-05-14 09:19:25	ga_ls8c_ard_3-2-1_090082_2022-05-13_final
2022-05-14 10:58:42	ga_ls8c_ard_3-2-1_106083_2022-05-14_final
2022-05-15 11:39:10	ga_ls8c_ard_3-2-1_113076_2022-05-15_final
2022-05-18 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-05-18_final
2022-05-20 10:18:27	ga_ls8c_ard_3-2-1_100075_2022-05-20_final
2022-05-21 11:04:30	ga_ls8c_ard_3-2-1_107082_2022-05-21_final
2022-05-24 09:56:31	ga_ls8c_ard_3-2-1_096082_2022-05-24_final
2022-05-24 11:34:36	ga_ls8c_ard_3-2-1_112080_2022-05-24_final
2022-05-25 10:35:23	ga_ls8c_ard_3-2-1_103071_2022-05-25_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-06 09:24:08	ga_ls8c_ard_3-2-1_091078_2022-06-05_final
2022-06-08 10:47:30	ga_ls8c_ard_3-2-1_105070_2022-06-08_final
2022-06-08 10:48:42	ga_ls8c_ard_3-2-1_105073_2022-06-08_final
2022-06-11 09:42:21	ga_ls8c_ard_3-2-1_094077_2022-06-11_final
2022-06-13 11:10:05	ga_ls8c_ard_3-2-1_108080_2022-06-13_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-17 10:41:49	ga_ls8c_ard_3-2-1_104071_2022-06-17_final
2022-06-17 10:43:25	ga_ls8c_ard_3-2-1_104075_2022-06-17_final
2022-06-17 10:45:48	ga_ls8c_ard_3-2-1_104081_2022-06-17_final
2022-06-18 09:48:12	ga_ls8c_ard_3-2-1_095076_2022-06-18_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-06-20 09:37:27	ga_ls8c_ard_3-2-1_093080_2022-06-20_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