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
2015-12-26 11:14:15	ga_ls8c_ard_3-1-0_109075_2015-12-26_final
2017-10-08 09:58:14	ga_ls8c_ard_3-1-0_097070_2017-10-08_final
2019-03-10 11:03:23	ga_ls8c_ard_3-1-0_107080_2019-03-10_final
2019-03-12 10:45:49	ga_ls8c_ard_3-1-0_105067_2019-03-12_final
2019-03-14 10:35:51	ga_ls8c_ard_3-1-0_103073_2019-03-14_final
2019-03-26 11:01:44	ga_ls8c_ard_3-1-0_107076_2019-03-26_final
2019-04-02 09:30:59	ga_ls8c_ard_3-1-0_092081_2019-04-02_final
2019-06-14 09:24:18	ga_ls8c_ard_3-1-0_091079_2019-06-13_final
2019-06-17 09:57:36	ga_ls8c_ard_3-1-0_096085_2019-06-17_final
2019-06-25 09:07:25	ga_ls8c_ard_3-1-0_088083_2019-06-24_final
2019-06-26 11:26:46	ga_ls8c_ard_3-1-0_111076_2019-06-26_final
2019-06-28 09:37:31	ga_ls8c_ard_3-1-0_093081_2019-06-28_final
2019-07-01 10:07:38	ga_ls8c_ard_3-1-0_098079_2019-07-01_final
2019-07-02 10:46:55	ga_ls8c_ard_3-1-0_105069_2019-07-02_final
2019-07-05 11:18:14	ga_ls8c_ard_3-1-0_110070_2019-07-05_final
2019-07-07 11:07:28	ga_ls8c_ard_3-1-0_108074_2019-07-07_final
2019-07-14 09:37:35	ga_ls8c_ard_3-1-0_093081_2019-07-14_final
2019-07-18 09:14:28	ga_ls8c_ard_3-1-0_089085_2019-07-17_final
2019-07-20 10:37:24	ga_ls8c_ard_3-1-0_103076_2019-07-20_final
2019-07-30 11:11:46	ga_ls8c_ard_3-1-0_109069_2019-07-30_final
2019-08-03 09:14:58	ga_ls8c_ard_3-1-0_089086_2019-08-02_final
2019-08-03 10:48:16	ga_ls8c_ard_3-1-0_105072_2019-08-03_final
2019-08-04 09:57:03	ga_ls8c_ard_3-1-0_096083_2019-08-04_final
2019-08-11 11:42:09	ga_ls8c_ard_3-1-0_113083_2019-08-11_final
2019-09-19 10:08:50	ga_ls8c_ard_3-1-0_098081_2019-09-19_final
2019-09-19 11:44:55	ga_ls8c_ard_3-1-0_114074_2019-09-19_final
2019-09-21 09:55:41	ga_ls8c_ard_3-1-0_096079_2019-09-21_final
2019-10-04 09:26:50	ga_ls8c_ard_3-1-0_091084_2019-10-03_final
2019-10-09 09:38:36	ga_ls8c_ard_3-1-0_094067_2019-10-09_final
2019-10-09 11:23:29	ga_ls8c_ard_3-1-0_110082_2019-10-09_final
2019-10-12 10:09:55	ga_ls8c_ard_3-1-0_099068_2019-10-12_final
2019-10-13 09:21:53	ga_ls8c_ard_3-1-0_090087_2019-10-12_final
2019-10-22 10:47:24	ga_ls8c_ard_3-1-0_105069_2019-10-22_final
2019-10-24 10:36:38	ga_ls8c_ard_3-1-0_103073_2019-10-24_final
2019-10-27 11:10:44	ga_ls8c_ard_3-1-0_108081_2019-10-27_final
2019-10-29 10:57:10	ga_ls8c_ard_3-1-0_106078_2019-10-29_final
2019-11-06 10:03:20	ga_ls8c_ard_3-1-0_098067_2019-11-06_final
2019-11-06 10:07:19	ga_ls8c_ard_3-1-0_098077_2019-11-06_final
2019-11-14 10:59:08	ga_ls8c_ard_3-1-0_106083_2019-11-14_final
2019-11-15 09:59:07	ga_ls8c_ard_3-1-0_097072_2019-11-15_final
2019-11-17 11:23:38	ga_ls8c_ard_3-1-0_111067_2019-11-17_final
2019-11-17 11:27:13	ga_ls8c_ard_3-1-0_111076_2019-11-17_final
2019-11-19 11:12:27	ga_ls8c_ard_3-1-0_109070_2019-11-19_final
2019-11-21 09:24:48	ga_ls8c_ard_3-1-0_091079_2019-11-20_final
2019-11-25 10:38:33	ga_ls8c_ard_3-1-0_103078_2019-11-25_final
2019-11-27 10:27:48	ga_ls8c_ard_3-1-0_101082_2019-11-27_final
2019-12-06 10:22:01	ga_ls8c_ard_3-1-0_100083_2019-12-06_final
2019-12-23 11:03:37	ga_ls8c_ard_3-1-0_107079_2019-12-23_final
2019-12-24 11:45:17	ga_ls8c_ard_3-1-0_114075_2019-12-24_final
2020-01-08 11:01:10	ga_ls8c_ard_3-1-0_107073_2020-01-08_final
2020-01-13 11:20:53	ga_ls8c_ard_3-1-0_110076_2020-01-13_final
2020-01-15 09:30:26	ga_ls8c_ard_3-1-0_092078_2020-01-15_final
2020-01-21 10:31:49	ga_ls8c_ard_3-1-0_102077_2020-01-21_final
2020-01-22 09:38:35	ga_ls8c_ard_3-1-0_093083_2020-01-22_final
2020-02-01 10:16:24	ga_ls8c_ard_3-1-0_099085_2020-02-01_final
2020-02-03 10:03:14	ga_ls8c_ard_3-1-0_097083_2020-02-03_final
2020-02-12 09:53:25	ga_ls8c_ard_3-1-0_096074_2020-02-12_final
2020-02-14 11:18:45	ga_ls8c_ard_3-1-0_110071_2020-02-14_final
2020-03-03 11:10:17	ga_ls8c_ard_3-1-0_108081_2020-03-03_final
2020-03-13 10:04:49	ga_ls8c_ard_3-1-0_098072_2020-03-13_final
2020-03-18 10:23:19	ga_ls8c_ard_3-1-0_101072_2020-03-18_final
2020-03-19 11:09:22	ga_ls8c_ard_3-1-0_108079_2020-03-19_final
2020-03-24 11:23:52	ga_ls8c_ard_3-1-0_111069_2020-03-24_final
2020-03-29 10:06:16	ga_ls8c_ard_3-1-0_098076_2020-03-29_final
2020-03-30 09:14:38	ga_ls8c_ard_3-1-0_089086_2020-03-29_final
2020-04-09 11:28:31	ga_ls8c_ard_3-1-0_111081_2020-04-09_final
2020-04-11 11:16:33	ga_ls8c_ard_3-1-0_109082_2020-04-11_final
2020-04-17 10:36:14	ga_ls8c_ard_3-1-0_103074_2020-04-17_final
2020-04-20 11:05:55	ga_ls8c_ard_3-1-0_108071_2020-04-20_final
2020-04-25 09:45:08	ga_ls8c_ard_3-1-0_095070_2020-04-25_final
2020-07-14 09:45:52	ga_ls8c_ard_3-1-0_095071_2020-07-14_final
2021-04-02 09:13:53	ga_ls8c_ard_3-2-0_089084_2021-04-01_final
2021-04-16 09:25:45	ga_ls8c_ard_3-2-0_091083_2021-04-15_final
2021-05-14 11:28:03	ga_ls8c_ard_3-2-0_111080_2021-05-14_final
2021-05-25 11:06:50	ga_ls8c_ard_3-2-0_108073_2021-05-25_final
2021-06-09 10:24:05	ga_ls8c_ard_3-2-0_101074_2021-06-09_final
2021-06-19 10:59:37	ga_ls8c_ard_3-2-0_107070_2021-06-19_final
2021-06-22 11:35:43	ga_ls8c_ard_3-2-0_112083_2021-06-22_final
2021-07-20 10:20:51	ga_ls8c_ard_3-2-0_100081_2021-07-20_final
2021-08-05 10:17:23	ga_ls8c_ard_3-2-0_100072_2021-08-05_final
2021-08-06 09:24:34	ga_ls8c_ard_3-2-0_091079_2021-08-05_final
2021-08-15 09:18:50	ga_ls8c_ard_3-2-0_090080_2021-08-14_final
2021-08-24 10:50:23	ga_ls8c_ard_3-2-0_105077_2021-08-24_final
2021-08-27 11:22:54	ga_ls8c_ard_3-2-0_110081_2021-08-27_final
2021-08-29 11:09:45	ga_ls8c_ard_3-2-0_108079_2021-08-29_final
2021-08-31 09:21:43	ga_ls8c_ard_3-2-0_090087_2021-08-30_final
2021-09-10 11:34:56	ga_ls8c_ard_3-2-0_112080_2021-09-10_final
2021-09-27 10:39:22	ga_ls8c_ard_3-2-0_103080_2021-09-27_final
2021-11-08 11:14:07	ga_ls8c_ard_3-2-0_109074_2021-11-08_final
2021-11-24 11:15:16	ga_ls8c_ard_3-2-0_109077_2021-11-24_final
2022-03-30 09:50:08	ga_ls8c_ard_3-2-1_095082_2022-03-30_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-02 10:18:38	ga_ls8c_ard_3-2-1_100076_2022-04-02_final
2022-04-03 11:01:54	ga_ls8c_ard_3-2-1_107076_2022-04-03_final
2022-04-05 09:16:16	ga_ls8c_ard_3-2-1_089090_2022-04-04_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-26 11:07:19	ga_ls8c_ard_3-2-1_108074_2022-04-26_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
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_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