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
2022-07-09 10:03:59	ga_ls8c_ard_3-2-1_098069_2022-07-09_final
2022-07-13 09:45:14	ga_ls8c_ard_3-2-1_094084_2022-07-13_final
2022-07-14 10:26:06	ga_ls8c_ard_3-2-1_101078_2022-07-14_final
2022-07-16 10:11:21	ga_ls8c_ard_3-2-1_099072_2022-07-16_final
2022-07-16 10:16:08	ga_ls8c_ard_3-2-1_099084_2022-07-16_final
2022-07-17 09:20:32	ga_ls8c_ard_3-2-1_090084_2022-07-16_final
2022-07-17 10:53:25	ga_ls8c_ard_3-2-1_106069_2022-07-17_final
2022-07-20 09:51:52	ga_ls8c_ard_3-2-1_095085_2022-07-20_final
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-24 09:26:48	ga_ls8c_ard_3-2-1_091084_2022-07-23_final
2022-07-29 09:46:12	ga_ls8c_ard_3-2-1_094086_2022-07-29_final
2022-07-29 11:19:06	ga_ls8c_ard_3-2-1_110071_2022-07-29_final
2022-07-31 11:07:34	ga_ls8c_ard_3-2-1_108073_2022-07-31_final
2022-08-01 10:15:56	ga_ls8c_ard_3-2-1_099083_2022-08-01_final
2022-08-02 10:59:12	ga_ls8c_ard_3-2-1_106083_2022-08-02_final
2022-08-05 11:30:08	ga_ls8c_ard_3-2-1_111083_2022-08-05_final
2022-08-09 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-08-09_final
2022-08-13 10:40:21	ga_ls8c_ard_3-2-1_103082_2022-08-13_final
2022-08-19 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-08-19_final
2022-08-23 09:38:10	ga_ls8c_ard_3-2-1_093081_2022-08-23_final
2022-08-25 09:27:48	ga_ls8c_ard_3-2-1_091086_2022-08-24_final
2022-08-28 09:57:54	ga_ls8c_ard_3-2-1_096084_2022-08-28_final
2022-09-03 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-09-02_final
2022-09-03 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-09-02_final
2022-09-03 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-09-03_final
2022-09-04 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-09-04_final
2022-09-05 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-09-04_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-11 10:05:09	ga_ls8c_ard_3-2-1_098071_2022-09-11_final
2022-09-16 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-09-16_final
2022-09-18 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-09-18_final
2022-09-20 11:42:17	ga_ls8c_ard_3-2-1_113082_2022-09-20_final
2022-09-24 09:34:18	ga_ls8c_ard_3-2-1_093071_2022-09-24_final
2022-09-24 11:12:47	ga_ls8c_ard_3-2-1_109070_2022-09-24_final
2022-09-24 11:14:46	ga_ls8c_ard_3-2-1_109075_2022-09-24_final
2022-09-26 09:23:56	ga_ls8c_ard_3-2-1_091076_2022-09-25_final
2022-10-01 09:40:28	ga_ls8c_ard_3-2-1_094071_2022-10-01_final
2022-10-03 11:08:58	ga_ls8c_ard_3-2-1_108076_2022-10-03_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-05 09:23:18	ga_ls8c_ard_3-2-1_090090_2022-10-04_final
2022-10-12 09:26:59	ga_ls8c_ard_3-2-1_091084_2022-10-11_final
2022-10-12 11:00:41	ga_ls8c_ard_3-2-1_107071_2022-10-12_final
2022-10-15 09:58:41	ga_ls8c_ard_3-2-1_096086_2022-10-15_final
2022-10-17 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-10-17_final
2022-10-18 10:23:38	ga_ls8c_ard_3-2-1_101071_2022-10-18_final
2022-10-20 11:53:22	ga_ls8c_ard_3-2-1_115079_2022-10-20_final
2022-10-21 10:54:10	ga_ls8c_ard_3-2-1_106070_2022-10-21_final
2022-10-23 10:46:37	ga_ls8c_ard_3-2-1_104082_2022-10-23_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-10-30 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-10-29_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-07 10:00:12	ga_ls8c_ard_3-2-1_097074_2022-11-07_final
2022-11-11 09:35:50	ga_ls8c_ard_3-2-1_093075_2022-11-11_final
2022-11-11 11:14:19	ga_ls8c_ard_3-2-1_109074_2022-11-11_final
2022-11-13 09:27:03	ga_ls8c_ard_3-2-1_091084_2022-11-12_final
2022-11-13 11:04:20	ga_ls8c_ard_3-2-1_107080_2022-11-13_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-11-14 10:10:18	ga_ls8c_ard_3-2-1_098084_2022-11-14_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-11-20 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-11-19_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-29 09:26:38	ga_ls8c_ard_3-2-1_091083_2022-11-28_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-03 10:40:00	ga_ls8c_ard_3-2-1_103081_2022-12-03_final
2022-12-04 09:46:46	ga_ls8c_ard_3-2-1_094087_2022-12-04_final
2022-12-06 11:06:30	ga_ls8c_ard_3-2-1_108070_2022-12-06_final
2022-12-08 09:17:15	ga_ls8c_ard_3-2-1_090075_2022-12-07_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-13 09:36:09	ga_ls8c_ard_3-2-1_093076_2022-12-13_final
2022-12-15 09:22:58	ga_ls8c_ard_3-2-1_091074_2022-12-14_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-31 09:22:06	ga_ls8c_ard_3-2-1_091072_2022-12-30_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-09 09:18:17	ga_ls8c_ard_3-2-1_090078_2023-01-08_final
2023-01-10 09:59:33	ga_ls8c_ard_3-2-1_097073_2023-01-10_final
2023-01-11 10:44:00	ga_ls8c_ard_3-2-1_104076_2023-01-11_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-19 11:34:09	ga_ls8c_ard_3-2-1_112078_2023-01-19_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-01-31 10:20:05	ga_ls8c_ard_3-2-1_100078_2023-01-31_final
2023-02-09 11:52:21	ga_ls8c_ard_3-2-1_115077_2023-02-09_final
2023-02-10 10:55:07	ga_ls8c_ard_3-2-1_106073_2023-02-10_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-02-17 09:21:55	ga_ls8c_ard_3-2-1_091072_2023-02-16_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-24 11:11:36	ga_ls8c_ard_3-2-1_108084_2023-02-24_final
2023-02-25 10:15:58	ga_ls8c_ard_3-2-1_099084_2023-02-25_final
2023-03-03 09:40:28	ga_ls8c_ard_3-2-1_093088_2023-03-03_final
2023-03-05 09:23:18	ga_ls8c_ard_3-2-1_091076_2023-03-04_final
2023-03-06 10:02:58	ga_ls8c_ard_3-2-1_098067_2023-03-06_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_final
2023-03-07 09:11:19	ga_ls8c_ard_3-2-1_089077_2023-03-06_final
2023-03-07 10:49:48	ga_ls8c_ard_3-2-1_105076_2023-03-07_final
2023-03-08 09:52:58	ga_ls8c_ard_3-2-1_096073_2023-03-08_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