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
2019-07-28 09:51:37	ga_ls8c_ard_3-1-0_095085_2019-07-28_final
2019-08-17 09:25:01	ga_ls8c_ard_3-1-0_091080_2019-08-16_final
2019-08-29 09:47:00	ga_ls8c_ard_3-1-0_095073_2019-08-29_final
2019-09-14 09:47:04	ga_ls8c_ard_3-1-0_095073_2019-09-14_final
2019-10-16 09:47:12	ga_ls8c_ard_3-1-0_095073_2019-10-16_final
2019-11-01 09:52:47	ga_ls8c_ard_3-1-0_095087_2019-11-01_final
2019-11-17 09:47:08	ga_ls8c_ard_3-1-0_095073_2019-11-17_final
2020-02-21 09:48:00	ga_ls8c_ard_3-1-0_095076_2020-02-21_final
2020-03-24 09:48:11	ga_ls8c_ard_3-1-0_095077_2020-03-24_final
2020-04-09 09:49:14	ga_ls8c_ard_3-1-0_095080_2020-04-09_final
2022-03-29 10:43:22	ga_ls8c_ard_3-2-1_104076_2022-03-29_final
2022-04-01 09:34:11	ga_ls8c_ard_3-2-1_093073_2022-04-01_final
2022-04-01 09:34:35	ga_ls8c_ard_3-2-1_093074_2022-04-01_final
2022-04-01 11:13:04	ga_ls8c_ard_3-2-1_109073_2022-04-01_final
2022-04-03 09:25:48	ga_ls8c_ard_3-2-1_091083_2022-04-02_final
2022-04-04 10:04:42	ga_ls8c_ard_3-2-1_098072_2022-04-04_final
2022-04-04 10:08:17	ga_ls8c_ard_3-2-1_098081_2022-04-04_final
2022-04-04 11:44:46	ga_ls8c_ard_3-2-1_114075_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-05 10:47:58	ga_ls8c_ard_3-2-1_105072_2022-04-05_final
2022-04-05 10:52:21	ga_ls8c_ard_3-2-1_105083_2022-04-05_final
2022-04-06 09:56:21	ga_ls8c_ard_3-2-1_096082_2022-04-06_final
2022-04-08 11:23:17	ga_ls8c_ard_3-2-1_110083_2022-04-08_final
2022-04-09 10:23:17	ga_ls8c_ard_3-2-1_101072_2022-04-09_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-09 10:25:17	ga_ls8c_ard_3-2-1_101077_2022-04-09_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-12 10:53:25	ga_ls8c_ard_3-2-1_106070_2022-04-12_final
2022-04-13 11:39:52	ga_ls8c_ard_3-2-1_113078_2022-04-13_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-13 11:41:28	ga_ls8c_ard_3-2-1_113082_2022-04-13_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-15 09:46:39	ga_ls8c_ard_3-2-1_095073_2022-04-15_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-15 11:25:32	ga_ls8c_ard_3-2-1_111073_2022-04-15_final
2022-04-15 11:29:07	ga_ls8c_ard_3-2-1_111082_2022-04-15_final
2022-04-17 11:11:34	ga_ls8c_ard_3-2-1_109069_2022-04-17_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-20 10:06:22	ga_ls8c_ard_3-2-1_098076_2022-04-20_final
2022-04-21 09:14:44	ga_ls8c_ard_3-2-1_089086_2022-04-20_final
2022-04-21 10:48:01	ga_ls8c_ard_3-2-1_105072_2022-04-21_final
2022-04-24 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-24_final
2022-04-24 11:23:18	ga_ls8c_ard_3-2-1_110083_2022-04-24_final
2022-04-27 10:14:29	ga_ls8c_ard_3-2-1_099081_2022-04-27_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-28 10:52:57	ga_ls8c_ard_3-2-1_106069_2022-04-28_final
2022-04-28 10:54:33	ga_ls8c_ard_3-2-1_106073_2022-04-28_final
2022-04-29 11:39:00	ga_ls8c_ard_3-2-1_113076_2022-04-29_final
2022-04-30 09:06:06	ga_ls8c_ard_3-2-1_088080_2022-04-29_final
2022-04-30 10:41:00	ga_ls8c_ard_3-2-1_104070_2022-04-30_final
2022-04-30 10:41:24	ga_ls8c_ard_3-2-1_104071_2022-04-30_final
2022-05-01 09:49:23	ga_ls8c_ard_3-2-1_095080_2022-05-01_final
2022-05-01 11:25:52	ga_ls8c_ard_3-2-1_111074_2022-05-01_final
2022-05-03 09:35:51	ga_ls8c_ard_3-2-1_093077_2022-05-03_final
2022-05-03 11:16:20	ga_ls8c_ard_3-2-1_109081_2022-05-03_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-04 10:21:07	ga_ls8c_ard_3-2-1_100082_2022-05-04_final
2022-05-05 09:23:07	ga_ls8c_ard_3-2-1_091076_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-11 10:25:23	ga_ls8c_ard_3-2-1_101077_2022-05-11_final
2022-05-12 09:33:21	ga_ls8c_ard_3-2-1_092086_2022-05-12_final
2022-05-14 09:19:49	ga_ls8c_ard_3-2-1_090083_2022-05-13_final
2022-05-14 10:53:31	ga_ls8c_ard_3-2-1_106070_2022-05-14_final
2022-05-14 10:58:18	ga_ls8c_ard_3-2-1_106082_2022-05-14_final
2022-05-15 11:38:22	ga_ls8c_ard_3-2-1_113074_2022-05-15_final
2022-05-15 11:39:34	ga_ls8c_ard_3-2-1_113077_2022-05-15_final
2022-05-17 09:46:20	ga_ls8c_ard_3-2-1_095072_2022-05-17_final
2022-05-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2022-05-17_final
2022-05-18 10:28:48	ga_ls8c_ard_3-2-1_102070_2022-05-18_final
2022-05-19 09:37:59	ga_ls8c_ard_3-2-1_093082_2022-05-19_final
2022-05-20 10:21:14	ga_ls8c_ard_3-2-1_100082_2022-05-20_final
2022-05-21 11:05:18	ga_ls8c_ard_3-2-1_107084_2022-05-21_final
2022-05-24 09:56:07	ga_ls8c_ard_3-2-1_096081_2022-05-24_final
2022-05-25 10:34:11	ga_ls8c_ard_3-2-1_103068_2022-05-25_final
2022-05-25 10:35:47	ga_ls8c_ard_3-2-1_103072_2022-05-25_final
2022-05-26 09:40:09	ga_ls8c_ard_3-2-1_094072_2022-05-26_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-02 09:46:49	ga_ls8c_ard_3-2-1_095073_2022-06-02_final
2022-06-02 09:47:36	ga_ls8c_ard_3-2-1_095075_2022-06-02_final
2022-06-02 09:50:00	ga_ls8c_ard_3-2-1_095081_2022-06-02_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-07 10:06:37	ga_ls8c_ard_3-2-1_098076_2022-06-07_final
2022-06-07 10:08:13	ga_ls8c_ard_3-2-1_098080_2022-06-07_final
2022-06-08 10:46:42	ga_ls8c_ard_3-2-1_105068_2022-06-08_final
2022-06-08 10:47:54	ga_ls8c_ard_3-2-1_105071_2022-06-08_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-13 11:08:06	ga_ls8c_ard_3-2-1_108075_2022-06-13_final
2022-06-15 10:52:58	ga_ls8c_ard_3-2-1_106068_2022-06-15_final
2022-06-15 10:54:09	ga_ls8c_ard_3-2-1_106071_2022-06-15_final
2022-06-18 09:47:48	ga_ls8c_ard_3-2-1_095075_2022-06-18_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-06-19 10:28:40	ga_ls8c_ard_3-2-1_102069_2022-06-19_final
2022-06-20 09:35:27	ga_ls8c_ard_3-2-1_093075_2022-06-20_final
2022-06-20 09:36:15	ga_ls8c_ard_3-2-1_093077_2022-06-20_final
2022-06-20 11:17:08	ga_ls8c_ard_3-2-1_109082_2022-06-20_final
2022-06-20 11:17:55	ga_ls8c_ard_3-2-1_109084_2022-06-20_final
2022-06-22 10:59:59	ga_ls8c_ard_3-2-1_107070_2022-06-22_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