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
2016-05-15 09:06:17	ga_ls8c_ard_3-1-0_088081_2016-05-14_final
2019-03-13 11:30:17	ga_ls8c_ard_3-1-0_112070_2019-03-13_final
2019-03-19 09:19:53	ga_ls8c_ard_3-1-0_090084_2019-03-18_final
2019-03-25 11:58:09	ga_ls8c_ard_3-1-0_116078_2019-03-25_final
2019-03-27 10:07:18	ga_ls8c_ard_3-1-0_098079_2019-03-27_final
2019-04-11 09:26:46	ga_ls8c_ard_3-1-0_091086_2019-04-10_final
2019-06-15 10:06:46	ga_ls8c_ard_3-1-0_098077_2019-06-15_final
2019-06-27 10:28:45	ga_ls8c_ard_3-1-0_102070_2019-06-27_final
2019-06-30 09:25:10	ga_ls8c_ard_3-1-0_091081_2019-06-29_final
2019-07-07 09:27:47	ga_ls8c_ard_3-1-0_092072_2019-07-06_final
2019-07-07 11:11:28	ga_ls8c_ard_3-1-0_108084_2019-07-07_final
2019-07-09 10:57:06	ga_ls8c_ard_3-1-0_106079_2019-07-09_final
2019-07-12 09:51:08	ga_ls8c_ard_3-1-0_095084_2019-07-12_final
2019-07-13 10:33:36	ga_ls8c_ard_3-1-0_102082_2019-07-13_final
2019-07-18 09:11:40	ga_ls8c_ard_3-1-0_089078_2019-07-17_final
2019-07-18 09:16:03	ga_ls8c_ard_3-1-0_089089_2019-07-17_final
2019-07-23 09:27:51	ga_ls8c_ard_3-1-0_092072_2019-07-22_final
2019-07-27 09:06:21	ga_ls8c_ard_3-1-0_088080_2019-07-26_final
2019-07-28 09:46:50	ga_ls8c_ard_3-1-0_095073_2019-07-28_final
2019-08-02 10:09:24	ga_ls8c_ard_3-1-0_098083_2019-08-02_final
2019-08-08 11:07:14	ga_ls8c_ard_3-1-0_108073_2019-08-08_final
2019-08-10 09:20:48	ga_ls8c_ard_3-1-0_090085_2019-08-09_final
2019-08-10 09:22:00	ga_ls8c_ard_3-1-0_090088_2019-08-09_final
2019-08-26 10:54:34	ga_ls8c_ard_3-1-0_106072_2019-08-26_final
2019-08-30 10:30:39	ga_ls8c_ard_3-1-0_102074_2019-08-30_final
2019-09-04 09:15:07	ga_ls8c_ard_3-1-0_089086_2019-09-03_final
2019-09-04 10:46:49	ga_ls8c_ard_3-1-0_105068_2019-09-04_final
2019-09-09 09:33:41	ga_ls8c_ard_3-1-0_092086_2019-09-09_final
2019-09-09 09:35:17	ga_ls8c_ard_3-1-0_092090_2019-09-09_final
2019-09-11 10:53:26	ga_ls8c_ard_3-1-0_106069_2019-09-11_final
2019-09-14 09:47:04	ga_ls8c_ard_3-1-0_095073_2019-09-14_final
2019-09-18 09:28:46	ga_ls8c_ard_3-1-0_091089_2019-09-17_final
2019-09-24 10:24:36	ga_ls8c_ard_3-1-0_101074_2019-09-24_final
2019-09-25 09:29:23	ga_ls8c_ard_3-1-0_092075_2019-09-24_final
2019-10-06 09:13:17	ga_ls8c_ard_3-1-0_089081_2019-10-05_final
2019-10-07 11:36:38	ga_ls8c_ard_3-1-0_112084_2019-10-07_final
2019-10-11 11:07:32	ga_ls8c_ard_3-1-0_108073_2019-10-11_final
2019-10-13 09:19:53	ga_ls8c_ard_3-1-0_090082_2019-10-12_final
2019-10-13 10:55:34	ga_ls8c_ard_3-1-0_106074_2019-10-13_final
2019-10-16 09:44:48	ga_ls8c_ard_3-1-0_095067_2019-10-16_final
2019-10-26 10:23:29	ga_ls8c_ard_3-1-0_101071_2019-10-26_final
2019-10-29 09:21:05	ga_ls8c_ard_3-1-0_090085_2019-10-28_final
2019-11-02 10:29:15	ga_ls8c_ard_3-1-0_102070_2019-11-02_final
2019-11-04 11:58:58	ga_ls8c_ard_3-1-0_116078_2019-11-04_final
2019-11-07 09:13:41	ga_ls8c_ard_3-1-0_089082_2019-11-06_final
2019-11-07 09:14:29	ga_ls8c_ard_3-1-0_089084_2019-11-06_final
2019-11-12 11:11:30	ga_ls8c_ard_3-1-0_108083_2019-11-12_final
2019-11-17 09:46:21	ga_ls8c_ard_3-1-0_095071_2019-11-17_final
2019-11-22 10:04:28	ga_ls8c_ard_3-1-0_098070_2019-11-22_final
2019-11-23 10:50:31	ga_ls8c_ard_3-1-0_105077_2019-11-23_final
2019-11-24 11:30:11	ga_ls8c_ard_3-1-0_112068_2019-11-24_final
2019-11-28 09:34:58	ga_ls8c_ard_3-1-0_092089_2019-11-28_final
2019-12-03 09:50:43	ga_ls8c_ard_3-1-0_095082_2019-12-03_final
2019-12-08 10:10:27	ga_ls8c_ard_3-1-0_098085_2019-12-08_final
2019-12-09 10:46:31	ga_ls8c_ard_3-1-0_105067_2019-12-09_final
2019-12-23 09:25:56	ga_ls8c_ard_3-1-0_091082_2019-12-22_final
2019-12-25 10:47:16	ga_ls8c_ard_3-1-0_105069_2019-12-25_final
2019-12-26 09:50:50	ga_ls8c_ard_3-1-0_096067_2019-12-26_final
2019-12-29 10:27:19	ga_ls8c_ard_3-1-0_101081_2019-12-29_final
2019-12-29 10:27:43	ga_ls8c_ard_3-1-0_101082_2019-12-29_final
2020-01-01 09:21:43	ga_ls8c_ard_3-1-0_090087_2019-12-31_final
2020-01-01 10:56:36	ga_ls8c_ard_3-1-0_106077_2020-01-01_final
2020-02-02 09:18:22	ga_ls8c_ard_3-1-0_090079_2020-02-01_final
2020-02-05 09:52:03	ga_ls8c_ard_3-1-0_095086_2020-02-05_final
2020-02-10 10:08:11	ga_ls8c_ard_3-1-0_098080_2020-02-10_final
2020-02-16 11:05:59	ga_ls8c_ard_3-1-0_108070_2020-02-16_final
2020-02-16 11:09:34	ga_ls8c_ard_3-1-0_108079_2020-02-16_final
2020-02-18 10:56:00	ga_ls8c_ard_3-1-0_106076_2020-02-18_final
2020-02-21 11:28:29	ga_ls8c_ard_3-1-0_111080_2020-02-21_final
2020-03-21 09:22:06	ga_ls8c_ard_3-1-0_090089_2020-03-20_final
2020-03-31 11:35:34	ga_ls8c_ard_3-1-0_112083_2020-03-31_final
2020-04-04 11:10:48	ga_ls8c_ard_3-1-0_108083_2020-04-04_final
2020-04-06 09:21:33	ga_ls8c_ard_3-1-0_090088_2020-04-05_final
2020-04-09 11:23:20	ga_ls8c_ard_3-1-0_111068_2020-04-09_final
2020-04-13 09:23:17	ga_ls8c_ard_3-1-0_091077_2020-04-12_final
2020-04-15 10:45:49	ga_ls8c_ard_3-1-0_105067_2020-04-15_final
2020-04-22 09:21:02	ga_ls8c_ard_3-1-0_090087_2020-04-21_final
2020-04-25 11:29:36	ga_ls8c_ard_3-1-0_111084_2020-04-25_final
2020-05-06 09:32:28	ga_ls8c_ard_3-1-0_092085_2020-05-06_final
2020-05-06 11:10:09	ga_ls8c_ard_3-1-0_108082_2020-05-06_final
2022-04-01 11:17:27	ga_ls8c_ard_3-2-1_109084_2022-04-01_final
2022-04-04 10:04:42	ga_ls8c_ard_3-2-1_098072_2022-04-04_final
2022-04-10 11:10:57	ga_ls8c_ard_3-2-1_108083_2022-04-10_final
2022-04-20 11:44:27	ga_ls8c_ard_3-2-1_114074_2022-04-20_final
2022-04-21 09:14:20	ga_ls8c_ard_3-2-1_089085_2022-04-20_final
2022-04-27 11:50:34	ga_ls8c_ard_3-2-1_115074_2022-04-27_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-28 09:21:15	ga_ls8c_ard_3-2-1_090087_2022-04-27_final
2022-04-30 10:45:47	ga_ls8c_ard_3-2-1_104082_2022-04-30_final
2022-05-01 11:23:29	ga_ls8c_ard_3-2-1_111068_2022-05-01_final
2022-05-04 10:20:43	ga_ls8c_ard_3-2-1_100081_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-14 10:53:31	ga_ls8c_ard_3-2-1_106070_2022-05-14_final
2022-05-17 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-05-17_final
2022-06-01 09:06:43	ga_ls8c_ard_3-2-1_088081_2022-05-31_final
2022-06-02 11:23:42	ga_ls8c_ard_3-2-1_111068_2022-06-02_final
2022-06-18 09:51:23	ga_ls8c_ard_3-2-1_095084_2022-06-18_final
2022-06-21 10:22:18	ga_ls8c_ard_3-2-1_100084_2022-06-21_final
2022-06-22 09:25:06	ga_ls8c_ard_3-2-1_091080_2022-06-21_final
2022-06-22 09:25:30	ga_ls8c_ard_3-2-1_091081_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