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
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2018-09-21 10:22:20	ga_ls8c_ard_3-0-0_101070_2018-09-21_final
2018-09-27 09:45:18	ga_ls8c_ard_3-0-0_095070_2018-09-27_final
2018-09-27 11:24:11	ga_ls8c_ard_3-0-0_111070_2018-09-27_final
2018-09-28 10:28:35	ga_ls8c_ard_3-0-0_102070_2018-09-28_final
2018-09-29 11:11:51	ga_ls8c_ard_3-0-0_109070_2018-09-29_final
2018-09-30 10:16:14	ga_ls8c_ard_3-0-0_100070_2018-09-30_final
2018-10-29 09:45:31	ga_ls8c_ard_3-0-0_095070_2018-10-29_final
2018-10-29 11:24:24	ga_ls8c_ard_3-0-0_111070_2018-10-29_final
2018-10-30 10:28:46	ga_ls8c_ard_3-0-0_102070_2018-10-30_final
2018-10-31 09:33:33	ga_ls8c_ard_3-0-0_093071_2018-10-31_final
2018-10-31 11:12:02	ga_ls8c_ard_3-0-0_109070_2018-10-31_final
2018-11-01 10:16:25	ga_ls8c_ard_3-1-0_100070_2018-11-01_final
2018-11-23 11:18:14	ga_ls8c_ard_3-0-0_110070_2018-11-23_final
2018-11-24 10:22:37	ga_ls8c_ard_3-0-0_101070_2018-11-24_final
2018-12-09 11:18:12	ga_ls8c_ard_3-0-0_110070_2018-12-09_final
2018-12-10 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-10_final
2018-12-16 09:45:28	ga_ls8c_ard_3-0-0_095070_2018-12-16_final
2018-12-16 11:24:22	ga_ls8c_ard_3-0-0_111070_2018-12-16_final
2018-12-17 10:28:44	ga_ls8c_ard_3-0-0_102070_2018-12-17_final
2018-12-18 11:12:00	ga_ls8c_ard_3-0-0_109070_2018-12-18_final
2018-12-19 10:16:23	ga_ls8c_ard_3-1-0_100070_2018-12-19_final
2018-12-23 09:51:40	ga_ls8c_ard_3-0-0_096070_2018-12-23_final
2018-12-23 11:30:33	ga_ls8c_ard_3-0-0_112070_2018-12-23_final
2018-12-24 10:34:55	ga_ls8c_ard_3-0-0_103070_2018-12-24_final
2018-12-25 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-12-25_final
2018-12-26 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-26_final
2019-01-01 09:45:29	ga_ls8c_ard_3-0-0_095070_2019-01-01_final
2019-01-01 11:24:22	ga_ls8c_ard_3-0-0_111070_2019-01-01_final
2019-01-02 10:28:44	ga_ls8c_ard_3-0-0_102070_2019-01-02_final
2019-01-03 11:12:00	ga_ls8c_ard_3-0-0_109070_2019-01-03_final
2019-01-04 10:16:22	ga_ls8c_ard_3-0-0_100070_2019-01-04_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_final
2019-01-08 09:51:39	ga_ls8c_ard_3-0-0_096070_2019-01-08_final
2019-01-08 11:30:32	ga_ls8c_ard_3-0-0_112070_2019-01-08_final
2019-01-09 10:34:54	ga_ls8c_ard_3-0-0_103070_2019-01-09_final
2019-01-10 11:18:10	ga_ls8c_ard_3-0-0_110070_2019-01-10_final
2019-01-11 10:22:32	ga_ls8c_ard_3-0-0_101070_2019-01-11_final
2019-01-17 09:45:26	ga_ls8c_ard_3-0-0_095070_2019-01-17_final
2019-01-17 11:24:19	ga_ls8c_ard_3-0-0_111070_2019-01-17_final
2019-01-18 10:28:41	ga_ls8c_ard_3-0-0_102070_2019-01-18_final
2019-01-19 11:11:57	ga_ls8c_ard_3-0-0_109070_2019-01-19_final
2019-01-20 10:16:19	ga_ls8c_ard_3-0-0_100070_2019-01-20_final
2023-08-24 11:24:29	ga_ls8c_ard_3-2-1_111070_2023-08-24_final
2023-08-24 11:24:53	ga_ls8c_ard_3-2-1_111071_2023-08-24_final
2023-08-25 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-08-25_final
2023-08-28 10:59:46	ga_ls8c_ard_3-2-1_107070_2023-08-28_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-09-01 10:35:02	ga_ls8c_ard_3-2-1_103070_2023-09-01_final
2023-09-01 10:35:26	ga_ls8c_ard_3-2-1_103071_2023-09-01_final
2023-10-17 10:47:34	ga_ls8c_ard_3-2-1_105070_2023-10-17_final
2023-10-18 09:51:56	ga_ls8c_ard_3-2-1_096070_2023-10-18_final
2023-10-19 10:35:11	ga_ls8c_ard_3-2-1_103070_2023-10-19_final
2023-10-23 10:10:30	ga_ls8c_ard_3-2-1_099070_2023-10-23_final
2023-10-29 11:12:21	ga_ls8c_ard_3-2-1_109070_2023-10-29_final
2023-11-02 10:47:37	ga_ls8c_ard_3-2-1_105070_2023-11-02_final
2023-11-03 09:52:00	ga_ls8c_ard_3-2-1_096070_2023-11-03_final
2023-11-04 10:35:15	ga_ls8c_ard_3-2-1_103070_2023-11-04_final
2023-11-05 11:18:30	ga_ls8c_ard_3-2-1_110070_2023-11-05_final
2023-11-06 10:22:52	ga_ls8c_ard_3-2-1_101070_2023-11-06_final
2023-11-09 10:53:43	ga_ls8c_ard_3-2-1_106070_2023-11-09_final
2023-11-10 09:58:05	ga_ls8c_ard_3-2-1_097070_2023-11-10_final
2023-11-13 10:29:02	ga_ls8c_ard_3-2-1_102070_2023-11-13_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-18 10:47:38	ga_ls8c_ard_3-2-1_105070_2023-11-18_final
2023-11-19 09:52:01	ga_ls8c_ard_3-2-1_096070_2023-11-19_final
2023-11-20 10:35:17	ga_ls8c_ard_3-2-1_103070_2023-11-20_final
2023-11-21 11:18:33	ga_ls8c_ard_3-2-1_110070_2023-11-21_final
2023-11-22 10:22:56	ga_ls8c_ard_3-2-1_101070_2023-11-22_final
2023-11-23 11:06:12	ga_ls8c_ard_3-2-1_108070_2023-11-23_final
2023-11-24 10:10:35	ga_ls8c_ard_3-2-1_099070_2023-11-24_final
2023-11-25 10:53:50	ga_ls8c_ard_3-2-1_106070_2023-11-25_final
2023-11-26 09:58:13	ga_ls8c_ard_3-2-1_097070_2023-11-26_final
2023-11-27 10:41:28	ga_ls8c_ard_3-2-1_104070_2023-11-27_final
2023-11-30 11:12:21	ga_ls8c_ard_3-2-1_109070_2023-11-30_final
2024-01-14 10:41:21	ga_ls8c_ard_3-2-1_104070_2024-01-14_final
2024-01-15 11:24:37	ga_ls8c_ard_3-2-1_111070_2024-01-15_final
2024-01-17 11:12:15	ga_ls8c_ard_3-2-1_109070_2024-01-17_final
2024-04-10 10:47:00	ga_ls8c_ard_3-2-1_105070_2024-04-10_final
2024-04-11 09:51:22	ga_ls8c_ard_3-2-1_096070_2024-04-11_final
2024-04-13 11:17:52	ga_ls8c_ard_3-2-1_110070_2024-04-13_final
2024-04-14 10:22:14	ga_ls8c_ard_3-2-1_101070_2024-04-14_final
2024-04-15 11:05:29	ga_ls8c_ard_3-2-1_108070_2024-04-15_final
2024-04-16 10:09:51	ga_ls8c_ard_3-2-1_099070_2024-04-16_final
2024-04-17 10:53:05	ga_ls8c_ard_3-2-1_106070_2024-04-17_final
2024-04-18 09:57:27	ga_ls8c_ard_3-2-1_097070_2024-04-18_final
2024-04-19 10:40:41	ga_ls8c_ard_3-2-1_104070_2024-04-19_final
2024-04-20 11:23:57	ga_ls8c_ard_3-2-1_111070_2024-04-20_final
2024-04-21 10:28:20	ga_ls8c_ard_3-2-1_102070_2024-04-21_final
2024-04-22 11:11:36	ga_ls8c_ard_3-2-1_109070_2024-04-22_final
2024-04-24 10:59:13	ga_ls8c_ard_3-2-1_107070_2024-04-24_final
2024-05-10 10:59:02	ga_ls8c_ard_3-2-1_107070_2024-05-10_final
2024-05-11 10:03:24	ga_ls8c_ard_3-2-1_098070_2024-05-11_nrt
2024-05-12 10:46:38	ga_ls8c_ard_3-2-1_105070_2024-05-12_final
2024-05-13 09:50:59	ga_ls8c_ard_3-2-1_096070_2024-05-13_final
2024-05-14 10:34:13	ga_ls8c_ard_3-2-1_103070_2024-05-14_nrt
2024-05-15 11:17:27	ga_ls8c_ard_3-2-1_110070_2024-05-15_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