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
2022-10-17 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-10-17_final
2022-10-19 09:33:37	ga_ls8c_ard_3-2-1_092085_2022-10-19_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-20 10:16:29	ga_ls8c_ard_3-2-1_099084_2022-10-20_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-10-22 10:00:09	ga_ls8c_ard_3-2-1_097074_2022-10-22_final
2022-10-22 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-22_final
2022-10-22 10:04:32	ga_ls8c_ard_3-2-1_097085_2022-10-22_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2022-10-29 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-10-29_final
2022-10-31 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-10-31_final
2022-10-31 09:53:38	ga_ls8c_ard_3-2-1_096073_2022-10-31_final
2022-10-31 09:56:49	ga_ls8c_ard_3-2-1_096081_2022-10-31_final
2022-10-31 11:36:06	ga_ls8c_ard_3-2-1_112082_2022-10-31_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-03 10:24:32	ga_ls8c_ard_3-2-1_101073_2022-11-03_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-08 10:41:27	ga_ls8c_ard_3-2-1_104069_2022-11-08_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-14 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-14_final
2022-11-18 09:45:07	ga_ls8c_ard_3-2-1_094083_2022-11-18_final
2022-11-20 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-11-20_final
2022-11-20 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-11-20_final
2022-11-22 09:18:50	ga_ls8c_ard_3-2-1_090079_2022-11-21_final
2022-11-22 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-11-21_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-11-26 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-11-26_final
2022-11-27 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-11-27_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-11-30 10:09:54	ga_ls8c_ard_3-2-1_098083_2022-11-30_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-06 09:31:13	ga_ls8c_ard_3-2-1_092079_2022-12-06_final
2022-12-06 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-12-06_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-09 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-12-09_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-10 10:41:46	ga_ls8c_ard_3-2-1_104070_2022-12-10_final
2022-12-12 10:30:35	ga_ls8c_ard_3-2-1_102073_2022-12-12_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-15 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-12-14_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-22 11:11:31	ga_ls8c_ard_3-2-1_108083_2022-12-22_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-25 10:03:57	ga_ls8c_ard_3-2-1_097084_2022-12-25_final
2022-12-26 10:42:01	ga_ls8c_ard_3-2-1_104071_2022-12-26_final
2022-12-27 11:30:05	ga_ls8c_ard_3-2-1_111083_2022-12-27_final
2022-12-29 09:36:51	ga_ls8c_ard_3-2-1_093078_2022-12-29_final
2022-12-29 09:39:15	ga_ls8c_ard_3-2-1_093084_2022-12-29_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2022-12-29 11:17:20	ga_ls8c_ard_3-2-1_109082_2022-12-29_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-04 10:39:27	ga_ls8c_ard_3-2-1_103080_2023-01-04_final
2023-01-06 10:26:41	ga_ls8c_ard_3-2-1_101079_2023-01-06_final
2023-01-09 09:18:41	ga_ls8c_ard_3-2-1_090079_2023-01-08_final
2023-01-09 10:57:34	ga_ls8c_ard_3-2-1_106079_2023-01-09_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-14 11:17:15	ga_ls8c_ard_3-2-1_109082_2023-01-14_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-16 09:27:34	ga_ls8c_ard_3-2-1_091086_2023-01-15_final
2023-01-17 10:08:01	ga_ls8c_ard_3-2-1_098079_2023-01-17_final
2023-01-17 10:08:25	ga_ls8c_ard_3-2-1_098080_2023-01-17_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-19 09:57:40	ga_ls8c_ard_3-2-1_096084_2023-01-19_final
2023-01-21 09:44:08	ga_ls8c_ard_3-2-1_094081_2023-01-21_final
2023-01-21 09:45:20	ga_ls8c_ard_3-2-1_094084_2023-01-21_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-23 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-01-23_final
2023-01-25 10:58:20	ga_ls8c_ard_3-2-1_106081_2023-01-25_final
2023-01-30 09:35:13	ga_ls8c_ard_3-2-1_093074_2023-01-30_final
2023-02-05 10:35:25	ga_ls8c_ard_3-2-1_103070_2023-02-05_final
2023-02-05 10:39:25	ga_ls8c_ard_3-2-1_103080_2023-02-05_final
2023-02-07 10:24:39	ga_ls8c_ard_3-2-1_101074_2023-02-07_final
2023-02-07 10:25:51	ga_ls8c_ard_3-2-1_101077_2023-02-07_final
2023-02-10 09:20:37	ga_ls8c_ard_3-2-1_090084_2023-02-09_final
2023-02-11 11:41:57	ga_ls8c_ard_3-2-1_113082_2023-02-11_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-17 11:00:24	ga_ls8c_ard_3-2-1_107071_2023-02-17_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-18 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-02-18_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-20 09:58:21	ga_ls8c_ard_3-2-1_096086_2023-02-20_final
2023-02-22 11:22:25	ga_ls8c_ard_3-2-1_110080_2023-02-22_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-24 09:33:55	ga_ls8c_ard_3-2-1_092087_2023-02-24_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-03-01 09:50:27	ga_ls8c_ard_3-2-1_095082_2023-03-01_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_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