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
2022-08-21 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-08-21_final
2022-08-22 10:29:24	ga_ls8c_ard_3-2-1_102070_2022-08-22_final
2022-08-26 10:06:17	ga_ls8c_ard_3-2-1_098074_2022-08-26_final
2022-09-13 11:36:05	ga_ls8c_ard_3-2-1_112082_2022-09-13_final
2022-09-14 10:40:04	ga_ls8c_ard_3-2-1_103081_2022-09-14_final
2022-09-19 10:55:02	ga_ls8c_ard_3-2-1_106072_2022-09-19_final
2022-09-23 10:33:54	ga_ls8c_ard_3-2-1_102081_2022-09-23_final
2022-09-24 09:35:06	ga_ls8c_ard_3-2-1_093073_2022-09-24_final
2022-09-24 09:38:17	ga_ls8c_ard_3-2-1_093081_2022-09-24_final
2022-09-27 10:05:59	ga_ls8c_ard_3-2-1_098073_2022-09-27_final
2022-09-28 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-09-28_final
2022-09-30 10:35:17	ga_ls8c_ard_3-2-1_103069_2022-09-30_final
2022-10-01 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-10-01_final
2022-10-01 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-10-01_final
2022-10-05 10:55:47	ga_ls8c_ard_3-2-1_106074_2022-10-05_final
2022-10-06 09:58:34	ga_ls8c_ard_3-2-1_097070_2022-10-06_final
2022-10-06 09:59:22	ga_ls8c_ard_3-2-1_097072_2022-10-06_final
2022-10-07 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-07_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-10 09:35:23	ga_ls8c_ard_3-2-1_093074_2022-10-10_final
2022-10-12 09:23:48	ga_ls8c_ard_3-2-1_091076_2022-10-11_final
2022-10-14 09:13:48	ga_ls8c_ard_3-2-1_089082_2022-10-13_final
2022-10-14 10:48:42	ga_ls8c_ard_3-2-1_105072_2022-10-14_final
2022-10-14 10:52:17	ga_ls8c_ard_3-2-1_105081_2022-10-14_final
2022-10-16 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-10-16_final
2022-10-19 11:12:06	ga_ls8c_ard_3-2-1_108084_2022-10-19_final
2022-10-21 10:55:46	ga_ls8c_ard_3-2-1_106074_2022-10-21_final
2022-10-21 10:56:58	ga_ls8c_ard_3-2-1_106077_2022-10-21_final
2022-10-23 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-23_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-10-26 11:17:32	ga_ls8c_ard_3-2-1_109082_2022-10-26_final
2022-10-28 11:01:36	ga_ls8c_ard_3-2-1_107073_2022-10-28_final
2022-10-29 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-10-29_final
2022-10-29 10:07:35	ga_ls8c_ard_3-2-1_098077_2022-10-29_final
2022-11-01 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-11-01_final
2022-11-01 10:40:29	ga_ls8c_ard_3-2-1_103082_2022-11-01_final
2022-11-03 10:24:56	ga_ls8c_ard_3-2-1_101074_2022-11-03_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-07 10:00:59	ga_ls8c_ard_3-2-1_097076_2022-11-07_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-10 10:34:16	ga_ls8c_ard_3-2-1_102082_2022-11-10_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-11 11:14:19	ga_ls8c_ard_3-2-1_109074_2022-11-11_final
2022-11-14 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-14_final
2022-11-16 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-11-16_final
2022-11-16 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-11-16_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-11-27 11:17:05	ga_ls8c_ard_3-2-1_109081_2022-11-27_final
2022-11-29 11:01:56	ga_ls8c_ard_3-2-1_107074_2022-11-29_final
2022-12-01 10:48:46	ga_ls8c_ard_3-2-1_105072_2022-12-01_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-07 10:15:40	ga_ls8c_ard_3-2-1_099082_2022-12-07_final
2022-12-08 10:56:56	ga_ls8c_ard_3-2-1_106077_2022-12-08_final
2022-12-10 10:41:22	ga_ls8c_ard_3-2-1_104069_2022-12-10_final
2022-12-10 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-12-10_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-12 10:33:22	ga_ls8c_ard_3-2-1_102080_2022-12-12_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-18 09:57:25	ga_ls8c_ard_3-2-1_096083_2022-12-18_final
2022-12-19 10:35:53	ga_ls8c_ard_3-2-1_103071_2022-12-19_final
2022-12-20 11:20:19	ga_ls8c_ard_3-2-1_110074_2022-12-20_final
2022-12-26 09:07:08	ga_ls8c_ard_3-2-1_088081_2022-12-25_final
2022-12-27 11:24:30	ga_ls8c_ard_3-2-1_111069_2022-12-27_final
2022-12-30 10:20:55	ga_ls8c_ard_3-2-1_100080_2022-12-30_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2022-12-31 11:04:58	ga_ls8c_ard_3-2-1_107082_2022-12-31_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-03 09:57:23	ga_ls8c_ard_3-2-1_096083_2023-01-03_final
2023-01-05 09:43:26	ga_ls8c_ard_3-2-1_094079_2023-01-05_final
2023-01-09 09:19:05	ga_ls8c_ard_3-2-1_090080_2023-01-08_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-19 09:55:40	ga_ls8c_ard_3-2-1_096079_2023-01-19_final
2023-01-19 11:35:21	ga_ls8c_ard_3-2-1_112081_2023-01-19_final
2023-01-20 10:39:45	ga_ls8c_ard_3-2-1_103081_2023-01-20_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-22 10:25:49	ga_ls8c_ard_3-2-1_101077_2023-01-22_final
2023-01-24 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-01-24_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-11 10:00:17	ga_ls8c_ard_3-2-1_097075_2023-02-11_final
2023-02-11 11:41:57	ga_ls8c_ard_3-2-1_113082_2023-02-11_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-18 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-02-18_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 10:49:12	ga_ls8c_ard_3-2-1_105074_2023-02-19_final
2023-02-19 10:49:36	ga_ls8c_ard_3-2-1_105075_2023-02-19_final
2023-02-25 10:13:34	ga_ls8c_ard_3-2-1_099078_2023-02-25_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-08 09:56:57	ga_ls8c_ard_3-2-1_096083_2023-03-08_final
2023-03-09 10:36:37	ga_ls8c_ard_3-2-1_103074_2023-03-09_final
2023-03-12 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-03-12_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