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
2017-09-04 10:14:49	ga_ls8c_ard_3-0-0_099081_2017-09-04_final
2017-09-04 10:15:13	ga_ls8c_ard_3-0-0_099082_2017-09-04_final
2017-09-05 09:19:12	ga_ls8c_ard_3-0-0_090081_2017-09-04_final
2017-09-05 09:19:36	ga_ls8c_ard_3-0-0_090082_2017-09-04_final
2017-09-05 10:58:05	ga_ls8c_ard_3-0-0_106081_2017-09-05_final
2017-09-05 10:58:29	ga_ls8c_ard_3-0-0_106082_2017-09-05_final
2017-09-06 10:02:28	ga_ls8c_ard_3-0-0_097081_2017-09-06_final
2017-09-06 10:02:52	ga_ls8c_ard_3-0-0_097082_2017-09-06_final
2017-09-06 11:41:21	ga_ls8c_ard_3-0-0_113081_2017-09-06_final
2017-09-06 11:41:45	ga_ls8c_ard_3-0-0_113082_2017-09-06_final
2017-09-07 09:06:51	ga_ls8c_ard_3-1-0_088081_2017-09-06_final
2017-09-07 09:07:15	ga_ls8c_ard_3-0-0_088082_2017-09-06_final
2017-09-07 10:45:44	ga_ls8c_ard_3-0-0_104081_2017-09-07_final
2017-09-07 10:46:08	ga_ls8c_ard_3-0-0_104082_2017-09-07_final
2017-09-08 09:50:06	ga_ls8c_ard_3-0-0_095081_2017-09-08_final
2017-09-08 09:50:30	ga_ls8c_ard_3-0-0_095082_2017-09-08_final
2017-09-08 11:28:59	ga_ls8c_ard_3-0-0_111081_2017-09-08_final
2017-09-08 11:29:23	ga_ls8c_ard_3-0-0_111082_2017-09-08_final
2017-10-25 09:07:02	ga_ls8c_ard_3-1-0_088081_2017-10-24_final
2017-10-25 09:07:26	ga_ls8c_ard_3-0-0_088082_2017-10-24_final
2017-10-25 10:45:55	ga_ls8c_ard_3-0-0_104081_2017-10-25_final
2017-10-25 10:46:19	ga_ls8c_ard_3-0-0_104082_2017-10-25_final
2017-10-26 09:50:18	ga_ls8c_ard_3-0-0_095081_2017-10-26_final
2017-10-26 09:50:42	ga_ls8c_ard_3-0-0_095082_2017-10-26_final
2017-10-26 11:29:11	ga_ls8c_ard_3-0-0_111081_2017-10-26_final
2017-10-26 11:29:35	ga_ls8c_ard_3-0-0_111082_2017-10-26_final
2017-10-27 10:33:34	ga_ls8c_ard_3-0-0_102081_2017-10-27_final
2017-10-27 10:33:57	ga_ls8c_ard_3-0-0_102082_2017-10-27_final
2017-11-26 09:06:54	ga_ls8c_ard_3-1-0_088081_2017-11-25_final
2017-11-26 09:07:18	ga_ls8c_ard_3-0-0_088082_2017-11-25_final
2017-11-26 10:45:47	ga_ls8c_ard_3-0-0_104081_2017-11-26_final
2017-11-26 10:46:11	ga_ls8c_ard_3-0-0_104082_2017-11-26_final
2017-11-27 09:50:10	ga_ls8c_ard_3-0-0_095081_2017-11-27_final
2017-11-27 09:50:34	ga_ls8c_ard_3-0-0_095082_2017-11-27_final
2017-11-27 11:29:03	ga_ls8c_ard_3-0-0_111081_2017-11-27_final
2017-11-27 11:29:27	ga_ls8c_ard_3-0-0_111082_2017-11-27_final
2017-11-28 10:33:25	ga_ls8c_ard_3-0-0_102081_2017-11-28_final
2017-11-28 10:33:49	ga_ls8c_ard_3-0-0_102082_2017-11-28_final
2022-01-22 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-01-22_final
2022-01-22 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-01-22_final
2022-01-23 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-01-23_final
2022-01-23 10:02:56	ga_ls8c_ard_3-2-1_097082_2022-01-23_final
2022-01-23 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-01-23_final
2022-01-24 09:06:54	ga_ls8c_ard_3-2-1_088081_2022-01-23_final
2022-01-24 09:07:18	ga_ls8c_ard_3-2-1_088082_2022-01-23_final
2022-01-24 10:45:47	ga_ls8c_ard_3-2-1_104081_2022-01-24_final
2022-01-24 10:46:11	ga_ls8c_ard_3-2-1_104082_2022-01-24_final
2022-01-25 09:50:09	ga_ls8c_ard_3-2-1_095081_2022-01-25_final
2022-01-25 09:50:33	ga_ls8c_ard_3-2-1_095082_2022-01-25_final
2022-04-03 11:03:54	ga_ls8c_ard_3-2-1_107081_2022-04-03_final
2022-04-03 11:04:17	ga_ls8c_ard_3-2-1_107082_2022-04-03_final
2022-04-05 09:12:40	ga_ls8c_ard_3-2-1_089081_2022-04-04_final
2022-04-05 09:13:04	ga_ls8c_ard_3-2-1_089082_2022-04-04_final
2022-04-05 10:51:33	ga_ls8c_ard_3-2-1_105081_2022-04-05_final
2022-04-05 10:51:57	ga_ls8c_ard_3-2-1_105082_2022-04-05_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-06 09:56:21	ga_ls8c_ard_3-2-1_096082_2022-04-06_final
2022-04-06 11:34:50	ga_ls8c_ard_3-2-1_112081_2022-04-06_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2023-02-12 09:07:02	ga_ls8c_ard_3-2-1_088081_2023-02-11_final
2023-02-12 09:07:26	ga_ls8c_ard_3-2-1_088082_2023-02-11_final
2023-02-12 10:45:55	ga_ls8c_ard_3-2-1_104081_2023-02-12_final
2023-02-12 10:46:19	ga_ls8c_ard_3-2-1_104082_2023-02-12_final
2023-02-13 09:50:17	ga_ls8c_ard_3-2-1_095081_2023-02-13_final
2023-02-13 09:50:41	ga_ls8c_ard_3-2-1_095082_2023-02-13_final
2023-02-13 11:29:10	ga_ls8c_ard_3-2-1_111081_2023-02-13_final
2023-02-13 11:29:34	ga_ls8c_ard_3-2-1_111082_2023-02-13_final
2023-02-14 10:33:32	ga_ls8c_ard_3-2-1_102081_2023-02-14_final
2023-02-14 10:33:56	ga_ls8c_ard_3-2-1_102082_2023-02-14_final
2023-02-15 09:37:54	ga_ls8c_ard_3-2-1_093081_2023-02-15_final
2023-02-15 09:38:18	ga_ls8c_ard_3-2-1_093082_2023-02-15_final
2023-02-15 11:16:47	ga_ls8c_ard_3-2-1_109081_2023-02-15_final
2023-02-15 11:17:11	ga_ls8c_ard_3-2-1_109082_2023-02-15_final
2023-02-16 08:42:40	ga_ls8c_ard_3-2-1_084082_2023-02-15_final
2023-02-16 10:21:33	ga_ls8c_ard_3-2-1_100082_2023-02-16_final
2023-02-17 09:25:31	ga_ls8c_ard_3-2-1_091081_2023-02-16_final
2023-02-17 09:25:55	ga_ls8c_ard_3-2-1_091082_2023-02-16_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-18 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-02-18_final
2023-02-18 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-02-18_final
2023-02-19 09:13:07	ga_ls8c_ard_3-2-1_089081_2023-02-18_final
2023-02-19 09:13:31	ga_ls8c_ard_3-2-1_089082_2023-02-18_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-19 10:52:23	ga_ls8c_ard_3-2-1_105082_2023-02-19_final
2023-02-24 11:10:25	ga_ls8c_ard_3-2-1_108081_2023-02-24_final
2023-02-24 11:10:49	ga_ls8c_ard_3-2-1_108082_2023-02-24_final
2023-02-25 10:14:46	ga_ls8c_ard_3-2-1_099081_2023-02-25_final
2023-02-25 10:15:10	ga_ls8c_ard_3-2-1_099082_2023-02-25_final
2023-02-26 09:19:33	ga_ls8c_ard_3-2-1_090082_2023-02-25_final
2023-02-26 10:58:02	ga_ls8c_ard_3-2-1_106081_2023-02-26_final
2023-02-26 10:58:26	ga_ls8c_ard_3-2-1_106082_2023-02-26_final
2023-02-27 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-02-27_final
2023-02-27 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-02-27_final
2023-02-27 11:41:18	ga_ls8c_ard_3-2-1_113081_2023-02-27_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_final
2023-02-28 09:07:11	ga_ls8c_ard_3-2-1_088082_2023-02-27_final
2023-02-28 10:45:40	ga_ls8c_ard_3-2-1_104081_2023-02-28_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years