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
2022-05-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2022-05-17_final
2022-05-22 11:45:22	ga_ls8c_ard_3-2-1_114076_2022-05-22_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-18 09:48:12	ga_ls8c_ard_3-2-1_095076_2022-06-18_final
2022-06-20 11:16:20	ga_ls8c_ard_3-2-1_109080_2022-06-20_final
2022-06-23 11:46:27	ga_ls8c_ard_3-2-1_114078_2022-06-23_final
2022-07-05 10:33:06	ga_ls8c_ard_3-2-1_102080_2022-07-05_final
2022-07-07 10:17:57	ga_ls8c_ard_3-2-1_100073_2022-07-07_final
2022-07-08 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-07-08_final
2022-07-11 09:52:25	ga_ls8c_ard_3-2-1_096071_2022-07-11_final
2022-07-18 10:02:36	ga_ls8c_ard_3-2-1_097081_2022-07-18_final
2022-07-25 11:45:22	ga_ls8c_ard_3-2-1_114075_2022-07-25_final
2022-08-02 09:20:19	ga_ls8c_ard_3-2-1_090083_2022-08-01_final
2022-08-06 10:32:08	ga_ls8c_ard_3-2-1_102077_2022-08-06_final
2022-08-09 09:27:22	ga_ls8c_ard_3-2-1_091085_2022-08-08_final
2022-08-09 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-08-09_final
2022-08-11 10:52:18	ga_ls8c_ard_3-2-1_105081_2022-08-11_final
2022-08-12 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-08-12_final
2022-08-14 11:24:01	ga_ls8c_ard_3-2-1_110083_2022-08-14_final
2022-08-15 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-08-15_final
2022-08-21 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-08-21_final
2022-08-27 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-08-27_final
2022-08-27 10:52:20	ga_ls8c_ard_3-2-1_105081_2022-08-27_final
2022-08-29 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-08-29_final
2022-08-31 10:24:49	ga_ls8c_ard_3-2-1_101074_2022-08-31_final
2022-09-04 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-09-04_final
2022-09-08 11:12:19	ga_ls8c_ard_3-2-1_109069_2022-09-08_final
2022-09-16 10:25:19	ga_ls8c_ard_3-2-1_101075_2022-09-16_final
2022-09-17 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-09-17_final
2022-09-20 10:01:00	ga_ls8c_ard_3-2-1_097076_2022-09-20_final
2022-09-24 09:37:05	ga_ls8c_ard_3-2-1_093078_2022-09-24_final
2022-09-29 09:56:49	ga_ls8c_ard_3-2-1_096081_2022-09-29_final
2022-10-04 10:13:20	ga_ls8c_ard_3-2-1_099076_2022-10-04_final
2022-10-06 11:39:27	ga_ls8c_ard_3-2-1_113075_2022-10-06_final
2022-10-12 09:26:11	ga_ls8c_ard_3-2-1_091082_2022-10-11_final
2022-10-13 11:45:55	ga_ls8c_ard_3-2-1_114076_2022-10-13_final
2022-10-17 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-10-17_final
2022-10-19 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-10-19_final
2022-10-19 11:11:18	ga_ls8c_ard_3-2-1_108082_2022-10-19_final
2022-10-27 10:21:07	ga_ls8c_ard_3-2-1_100080_2022-10-27_final
2022-10-28 09:25:54	ga_ls8c_ard_3-2-1_091081_2022-10-27_final
2022-10-31 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-10-31_final
2022-11-01 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-11-01_final
2022-11-02 09:42:28	ga_ls8c_ard_3-2-1_094076_2022-11-02_final
2022-11-06 10:57:49	ga_ls8c_ard_3-2-1_106079_2022-11-06_final
2022-11-08 10:43:03	ga_ls8c_ard_3-2-1_104073_2022-11-08_final
2022-11-13 09:27:03	ga_ls8c_ard_3-2-1_091084_2022-11-12_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-20 09:35:34	ga_ls8c_ard_3-2-1_092090_2022-11-20_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-23 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-11-23_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-11-25 11:29:02	ga_ls8c_ard_3-2-1_111080_2022-11-25_final
2022-11-27 11:15:53	ga_ls8c_ard_3-2-1_109078_2022-11-27_final
2022-11-29 11:05:55	ga_ls8c_ard_3-2-1_107084_2022-11-29_final
2022-12-01 10:48:22	ga_ls8c_ard_3-2-1_105071_2022-12-01_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-08 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-12-07_final
2022-12-22 11:11:55	ga_ls8c_ard_3-2-1_108084_2022-12-22_final
2023-01-06 10:24:41	ga_ls8c_ard_3-2-1_101074_2023-01-06_final
2023-01-12 11:27:15	ga_ls8c_ard_3-2-1_111076_2023-01-12_final
2023-01-14 09:40:22	ga_ls8c_ard_3-2-1_093087_2023-01-14_final
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-01-26 11:39:37	ga_ls8c_ard_3-2-1_113076_2023-01-26_final
2023-01-30 09:36:49	ga_ls8c_ard_3-2-1_093078_2023-01-30_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-10 10:57:07	ga_ls8c_ard_3-2-1_106078_2023-02-10_final
2023-02-10 10:57:31	ga_ls8c_ard_3-2-1_106079_2023-02-10_final
2023-02-12 10:44:19	ga_ls8c_ard_3-2-1_104077_2023-02-12_final
2023-02-13 09:49:53	ga_ls8c_ard_3-2-1_095080_2023-02-13_final
2023-02-14 10:31:08	ga_ls8c_ard_3-2-1_102075_2023-02-14_final
2023-02-15 09:37:30	ga_ls8c_ard_3-2-1_093080_2023-02-15_final
2023-02-16 11:58:02	ga_ls8c_ard_3-2-1_116076_2023-02-16_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-17 11:03:36	ga_ls8c_ard_3-2-1_107079_2023-02-17_final
2023-02-24 09:32:44	ga_ls8c_ard_3-2-1_092084_2023-02-24_final
2023-03-04 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-03-04_final
2023-03-04 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-03-04_final
2023-03-15 11:39:36	ga_ls8c_ard_3-2-1_113077_2023-03-15_final
2023-03-23 10:50:03	ga_ls8c_ard_3-2-1_105077_2023-03-23_final
2023-03-28 11:07:22	ga_ls8c_ard_3-2-1_108074_2023-03-28_final
2023-03-30 09:18:06	ga_ls8c_ard_3-2-1_090079_2023-03-29_final
2023-04-15 10:57:32	ga_ls8c_ard_3-2-1_106081_2023-04-15_final
2023-04-24 10:47:19	ga_ls8c_ard_3-2-1_105071_2023-04-24_final
2023-04-26 10:36:57	ga_ls8c_ard_3-2-1_103076_2023-04-26_final
2023-04-29 09:29:21	ga_ls8c_ard_3-2-1_092077_2023-04-28_final
2023-04-29 09:30:09	ga_ls8c_ard_3-2-1_092079_2023-04-29_final
2023-05-06 09:35:51	ga_ls8c_ard_3-2-1_093078_2023-05-06_final
2023-05-13 11:20:24	ga_ls8c_ard_3-2-1_110077_2023-05-13_final
2023-05-16 10:10:47	ga_ls8c_ard_3-2-1_099073_2023-05-16_final
2023-05-17 10:57:38	ga_ls8c_ard_3-2-1_106082_2023-05-17_final
2023-05-18 10:01:37	ga_ls8c_ard_3-2-1_097081_2023-05-18_final
2023-05-18 11:39:42	ga_ls8c_ard_3-2-1_113079_2023-05-18_final
2023-05-19 10:41:41	ga_ls8c_ard_3-2-1_104073_2023-05-19_final
2023-05-22 11:14:37	ga_ls8c_ard_3-2-1_109078_2023-05-22_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-24 09:24:58	ga_ls8c_ard_3-2-1_091082_2023-05-23_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