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
2019-03-10 09:25:18	ga_ls8c_ard_3-1-0_091082_2019-03-09_final
2019-03-13 09:56:11	ga_ls8c_ard_3-1-0_096082_2019-03-13_final
2019-04-14 09:52:27	ga_ls8c_ard_3-1-0_096073_2019-04-14_final
2019-04-14 09:52:51	ga_ls8c_ard_3-1-0_096074_2019-04-14_final
2019-06-17 09:56:01	ga_ls8c_ard_3-1-0_096081_2019-06-17_final
2019-06-17 09:56:25	ga_ls8c_ard_3-1-0_096082_2019-06-17_final
2019-06-30 09:25:58	ga_ls8c_ard_3-1-0_091083_2019-06-29_final
2019-07-03 09:54:53	ga_ls8c_ard_3-1-0_096078_2019-07-03_final
2019-07-03 09:56:29	ga_ls8c_ard_3-1-0_096082_2019-07-03_final
2019-07-28 09:50:49	ga_ls8c_ard_3-1-0_095083_2019-07-28_final
2019-08-04 09:56:15	ga_ls8c_ard_3-1-0_096081_2019-08-04_final
2019-08-04 09:56:39	ga_ls8c_ard_3-1-0_096082_2019-08-04_final
2019-08-13 09:50:07	ga_ls8c_ard_3-1-0_095081_2019-08-13_final
2019-08-17 09:24:37	ga_ls8c_ard_3-1-0_091079_2019-08-16_final
2019-08-20 09:52:44	ga_ls8c_ard_3-1-0_096072_2019-08-20_final
2019-08-20 09:56:20	ga_ls8c_ard_3-1-0_096081_2019-08-20_final
2019-08-29 09:50:11	ga_ls8c_ard_3-1-0_095081_2019-08-29_final
2019-09-02 09:25:05	ga_ls8c_ard_3-1-0_091080_2019-09-01_final
2019-09-05 09:56:47	ga_ls8c_ard_3-1-0_096082_2019-09-05_final
2019-09-14 09:47:52	ga_ls8c_ard_3-1-0_095075_2019-09-14_final
2019-09-14 09:50:16	ga_ls8c_ard_3-1-0_095081_2019-09-14_final
2019-09-18 09:26:22	ga_ls8c_ard_3-1-0_091083_2019-09-17_final
2019-09-21 09:52:53	ga_ls8c_ard_3-1-0_096072_2019-09-21_final
2019-10-07 09:53:21	ga_ls8c_ard_3-1-0_096073_2019-10-07_final
2019-10-20 09:24:28	ga_ls8c_ard_3-1-0_091078_2019-10-19_final
2019-10-20 09:26:04	ga_ls8c_ard_3-1-0_091082_2019-10-19_final
2019-10-23 09:56:34	ga_ls8c_ard_3-1-0_096081_2019-10-23_final
2019-11-21 09:26:47	ga_ls8c_ard_3-1-0_091084_2019-11-20_final
2019-11-24 09:56:30	ga_ls8c_ard_3-1-0_096081_2019-11-24_final
2019-12-10 09:55:41	ga_ls8c_ard_3-1-0_096079_2019-12-10_final
2019-12-10 09:56:29	ga_ls8c_ard_3-1-0_096081_2019-12-10_final
2019-12-23 09:26:44	ga_ls8c_ard_3-1-0_091084_2019-12-22_final
2020-01-04 09:44:37	ga_ls8c_ard_3-1-0_095067_2020-01-04_final
2020-02-21 09:51:36	ga_ls8c_ard_3-1-0_095085_2020-02-21_final
2020-02-28 09:56:33	ga_ls8c_ard_3-1-0_096082_2020-02-28_final
2020-03-15 09:57:38	ga_ls8c_ard_3-1-0_096085_2020-03-15_final
2020-03-31 09:57:29	ga_ls8c_ard_3-1-0_096085_2020-03-31_final
2020-04-16 09:56:34	ga_ls8c_ard_3-1-0_096083_2020-04-16_final
2020-05-02 09:52:02	ga_ls8c_ard_3-1-0_096072_2020-05-02_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
2022-04-01 09:38:34	ga_ls8c_ard_3-2-1_093084_2022-04-01_final
2022-04-07 10:34:26	ga_ls8c_ard_3-2-1_103069_2022-04-07_final
2022-04-08 11:23:17	ga_ls8c_ard_3-2-1_110083_2022-04-08_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-13 11:40:40	ga_ls8c_ard_3-2-1_113080_2022-04-13_final
2022-04-15 09:51:02	ga_ls8c_ard_3-2-1_095084_2022-04-15_final
2022-04-17 09:34:41	ga_ls8c_ard_3-2-1_093074_2022-04-17_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-25 10:26:28	ga_ls8c_ard_3-2-1_101080_2022-04-25_final
2022-04-28 09:18:51	ga_ls8c_ard_3-2-1_090081_2022-04-27_final
2022-04-29 10:00:31	ga_ls8c_ard_3-2-1_097077_2022-04-29_final
2022-04-29 10:01:43	ga_ls8c_ard_3-2-1_097080_2022-04-29_final
2022-04-29 11:40:12	ga_ls8c_ard_3-2-1_113079_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-05-01 09:46:59	ga_ls8c_ard_3-2-1_095074_2022-05-01_final
2022-05-02 10:29:04	ga_ls8c_ard_3-2-1_102071_2022-05-02_final
2022-05-03 11:11:56	ga_ls8c_ard_3-2-1_109070_2022-05-03_final
2022-05-04 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-05-04_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-05 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-05-05_final
2022-05-06 11:44:53	ga_ls8c_ard_3-2-1_114075_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-09 10:34:56	ga_ls8c_ard_3-2-1_103070_2022-05-09_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-14 09:19:01	ga_ls8c_ard_3-2-1_090081_2022-05-13_final
2022-05-15 11:40:22	ga_ls8c_ard_3-2-1_113079_2022-05-15_final
2022-05-16 10:43:09	ga_ls8c_ard_3-2-1_104075_2022-05-16_final
2022-05-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2022-05-17_final
2022-05-19 09:37:35	ga_ls8c_ard_3-2-1_093081_2022-05-19_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-24 09:55:19	ga_ls8c_ard_3-2-1_096079_2022-05-24_final
2022-05-24 11:34:36	ga_ls8c_ard_3-2-1_112080_2022-05-24_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-05-26 09:44:32	ga_ls8c_ard_3-2-1_094083_2022-05-26_final
2022-05-26 11:22:38	ga_ls8c_ard_3-2-1_110081_2022-05-26_final
2022-05-30 10:57:56	ga_ls8c_ard_3-2-1_106081_2022-05-30_final
2022-06-02 09:48:00	ga_ls8c_ard_3-2-1_095076_2022-06-02_final
2022-06-02 11:27:41	ga_ls8c_ard_3-2-1_111078_2022-06-02_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-04 09:38:04	ga_ls8c_ard_3-2-1_093082_2022-06-04_final
2022-06-04 11:15:21	ga_ls8c_ard_3-2-1_109078_2022-06-04_final
2022-06-04 11:16:57	ga_ls8c_ard_3-2-1_109082_2022-06-04_final
2022-06-07 10:06:13	ga_ls8c_ard_3-2-1_098075_2022-06-07_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-07 11:45:30	ga_ls8c_ard_3-2-1_114076_2022-06-07_final
2022-06-08 10:52:41	ga_ls8c_ard_3-2-1_105083_2022-06-08_final
2022-06-13 11:10:05	ga_ls8c_ard_3-2-1_108080_2022-06-13_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-17 10:45:48	ga_ls8c_ard_3-2-1_104081_2022-06-17_final
2022-06-20 09:37:27	ga_ls8c_ard_3-2-1_093080_2022-06-20_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_final
2022-06-21 10:17:55	ga_ls8c_ard_3-2-1_100073_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