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
2021-12-04 10:13:29	ga_ls8c_ard_3-2-0_099077_2021-12-04_final
2021-12-04 10:15:29	ga_ls8c_ard_3-2-0_099082_2021-12-04_final
2021-12-05 09:18:16	ga_ls8c_ard_3-2-0_090078_2021-12-04_final
2021-12-19 09:31:23	ga_ls8c_ard_3-2-1_092080_2021-12-19_final
2021-12-30 09:13:34	ga_ls8c_ard_3-2-1_089082_2021-12-29_final
2022-01-02 11:20:33	ga_ls8c_ard_3-2-1_110075_2022-01-02_final
2022-01-04 09:31:18	ga_ls8c_ard_3-2-1_092080_2022-01-04_final
2022-01-04 09:32:30	ga_ls8c_ard_3-2-1_092083_2022-01-04_final
2022-01-11 11:14:45	ga_ls8c_ard_3-2-1_109076_2022-01-11_final
2022-01-12 10:17:08	ga_ls8c_ard_3-2-1_100071_2022-01-12_final
2022-01-12 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-01-12_final
2022-01-18 11:18:31	ga_ls8c_ard_3-2-1_110070_2022-01-18_final
2022-01-19 10:22:53	ga_ls8c_ard_3-2-1_101070_2022-01-19_final
2022-01-28 10:20:38	ga_ls8c_ard_3-2-1_100080_2022-01-28_final
2022-02-07 10:56:06	ga_ls8c_ard_3-2-1_106076_2022-02-07_final
2022-02-12 11:14:13	ga_ls8c_ard_3-2-1_109075_2022-02-12_final
2022-02-16 10:49:52	ga_ls8c_ard_3-2-1_105076_2022-02-16_final
2022-02-18 10:39:05	ga_ls8c_ard_3-2-1_103080_2022-02-18_final
2022-02-21 09:32:17	ga_ls8c_ard_3-2-1_092083_2022-02-21_final
2022-02-23 09:18:19	ga_ls8c_ard_3-2-1_090079_2022-02-22_final
2022-02-23 10:56:01	ga_ls8c_ard_3-2-1_106076_2022-02-23_final
2022-03-02 09:26:05	ga_ls8c_ard_3-2-1_091083_2022-03-01_final
2022-03-03 11:47:26	ga_ls8c_ard_3-2-1_114081_2022-03-03_final
2022-03-07 11:19:54	ga_ls8c_ard_3-2-1_110074_2022-03-07_final
2022-03-10 10:10:42	ga_ls8c_ard_3-2-1_099071_2022-03-10_final
2022-03-18 11:02:28	ga_ls8c_ard_3-2-1_107077_2022-03-18_final
2022-03-18 11:04:51	ga_ls8c_ard_3-2-1_107083_2022-03-18_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-04-02 11:57:31	ga_ls8c_ard_3-2-1_116076_2022-04-02_final
2022-04-13 10:03:23	ga_ls8c_ard_3-2-1_097084_2022-04-13_final
2022-04-19 10:59:36	ga_ls8c_ard_3-2-1_107070_2022-04-19_final
2022-04-19 11:02:47	ga_ls8c_ard_3-2-1_107078_2022-04-19_final
2022-05-02 10:27:52	ga_ls8c_ard_3-2-1_102068_2022-05-02_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-10 11:19:48	ga_ls8c_ard_3-2-1_110074_2022-05-10_final
2022-05-12 11:09:51	ga_ls8c_ard_3-2-1_108080_2022-05-12_final
2022-05-14 10:56:42	ga_ls8c_ard_3-2-1_106078_2022-05-14_final
2022-05-21 11:04:54	ga_ls8c_ard_3-2-1_107083_2022-05-21_final
2022-05-24 09:57:19	ga_ls8c_ard_3-2-1_096084_2022-05-24_final
2022-05-28 09:32:35	ga_ls8c_ard_3-2-1_092084_2022-05-28_final
2022-05-30 10:57:32	ga_ls8c_ard_3-2-1_106080_2022-05-30_final
2022-06-04 11:14:10	ga_ls8c_ard_3-2-1_109075_2022-06-04_final
2022-06-04 11:17:21	ga_ls8c_ard_3-2-1_109083_2022-06-04_final
2022-06-11 11:20:02	ga_ls8c_ard_3-2-1_110074_2022-06-11_final
2022-06-13 09:32:48	ga_ls8c_ard_3-2-1_092084_2022-06-13_final
2022-06-13 11:08:30	ga_ls8c_ard_3-2-1_108076_2022-06-13_final
2022-06-18 09:52:35	ga_ls8c_ard_3-2-1_095087_2022-06-18_final
2022-06-21 10:22:18	ga_ls8c_ard_3-2-1_100084_2022-06-21_final
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-06-24 09:16:44	ga_ls8c_ard_3-2-1_089090_2022-06-23_final
2022-06-25 11:31:42	ga_ls8c_ard_3-2-1_112072_2022-06-25_final
2022-07-16 10:16:08	ga_ls8c_ard_3-2-1_099084_2022-07-16_final
2022-08-04 10:46:04	ga_ls8c_ard_3-2-1_104081_2022-08-04_final
2022-08-14 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-08-14_final
2022-08-14 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-08-14_final
2022-08-21 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-08-21_final
2022-08-23 11:14:16	ga_ls8c_ard_3-2-1_109074_2022-08-23_final
2022-08-25 11:03:06	ga_ls8c_ard_3-2-1_107077_2022-08-25_final
2022-08-28 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-08-28_final
2022-09-03 10:58:06	ga_ls8c_ard_3-2-1_106080_2022-09-03_final
2022-09-08 11:15:06	ga_ls8c_ard_3-2-1_109076_2022-09-08_final
2022-09-14 10:40:04	ga_ls8c_ard_3-2-1_103081_2022-09-14_final
2022-09-24 11:14:23	ga_ls8c_ard_3-2-1_109074_2022-09-24_final
2022-09-26 09:22:44	ga_ls8c_ard_3-2-1_091073_2022-09-25_final
2022-09-26 11:06:00	ga_ls8c_ard_3-2-1_107084_2022-09-26_final
2022-09-28 10:52:03	ga_ls8c_ard_3-2-1_105080_2022-09-28_final
2022-10-03 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-10-03_final
2022-10-05 09:18:30	ga_ls8c_ard_3-2-1_090078_2022-10-04_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2022-10-13 11:47:55	ga_ls8c_ard_3-2-1_114081_2022-10-13_final
2022-10-14 10:51:53	ga_ls8c_ard_3-2-1_105080_2022-10-14_final
2022-10-29 10:09:34	ga_ls8c_ard_3-2-1_098082_2022-10-29_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-11-02 11:20:57	ga_ls8c_ard_3-2-1_110075_2022-11-02_final
2022-11-11 11:14:43	ga_ls8c_ard_3-2-1_109075_2022-11-11_final
2022-11-13 11:02:44	ga_ls8c_ard_3-2-1_107076_2022-11-13_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-20 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-11-20_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-14 10:17:24	ga_ls8c_ard_3-2-1_100071_2022-12-14_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-24 10:56:22	ga_ls8c_ard_3-2-1_106076_2022-12-24_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-26 09:07:08	ga_ls8c_ard_3-2-1_088081_2022-12-25_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2022-12-30 10:20:31	ga_ls8c_ard_3-2-1_100079_2022-12-30_final
2023-01-02 10:52:13	ga_ls8c_ard_3-2-1_105081_2023-01-02_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-11 10:46:23	ga_ls8c_ard_3-2-1_104082_2023-01-11_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-16 11:04:51	ga_ls8c_ard_3-2-1_107082_2023-01-16_final
2023-01-18 09:16:23	ga_ls8c_ard_3-2-1_089089_2023-01-17_final
2023-01-19 11:31:46	ga_ls8c_ard_3-2-1_112072_2023-01-19_final
2023-01-25 10:56:45	ga_ls8c_ard_3-2-1_106077_2023-01-25_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-02-15 11:13:59	ga_ls8c_ard_3-2-1_109074_2023-02-15_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_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