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:

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First 100 results (query limit)

Time (local)	Label
2021-10-01 10:13:05	ga_ls8c_ard_3-2-0_099076_2021-10-01_final
2021-10-10 11:45:26	ga_ls8c_ard_3-2-0_114075_2021-10-10_final
2021-10-12 09:57:23	ga_ls8c_ard_3-2-0_096083_2021-10-12_final
2021-11-02 10:12:45	ga_ls8c_ard_3-2-0_099075_2021-11-02_final
2021-11-05 10:45:38	ga_ls8c_ard_3-2-0_104080_2021-11-05_final
2021-11-11 11:46:36	ga_ls8c_ard_3-2-0_114078_2021-11-11_final
2021-11-15 09:41:46	ga_ls8c_ard_3-2-0_094075_2021-11-15_final
2021-11-21 10:43:10	ga_ls8c_ard_3-2-0_104074_2021-11-21_final
2021-11-22 09:49:08	ga_ls8c_ard_3-2-0_095078_2021-11-22_final
2021-11-27 11:46:35	ga_ls8c_ard_3-2-0_114078_2021-11-27_final
2021-11-29 09:57:20	ga_ls8c_ard_3-2-0_096083_2021-11-29_final
2021-12-01 11:23:04	ga_ls8c_ard_3-2-0_110081_2021-12-01_final
2021-12-10 09:36:24	ga_ls8c_ard_3-2-1_093077_2021-12-10_final
2021-12-10 09:37:59	ga_ls8c_ard_3-2-1_093081_2021-12-10_final
2021-12-11 11:58:08	ga_ls8c_ard_3-2-1_116076_2021-12-11_final
2021-12-12 09:26:02	ga_ls8c_ard_3-2-1_091082_2021-12-11_final
2021-12-15 11:33:01	ga_ls8c_ard_3-2-1_112075_2021-12-15_final
2021-12-16 10:40:11	ga_ls8c_ard_3-2-1_103082_2021-12-16_final
2021-12-23 10:45:32	ga_ls8c_ard_3-2-1_104080_2021-12-23_final
2022-01-04 09:30:54	ga_ls8c_ard_3-2-1_092079_2022-01-04_final
2022-01-08 10:42:40	ga_ls8c_ard_3-2-1_104073_2022-01-08_final
2022-01-09 09:48:14	ga_ls8c_ard_3-2-1_095076_2022-01-09_final
2022-01-11 09:39:52	ga_ls8c_ard_3-2-1_093086_2022-01-11_final
2022-01-15 10:51:13	ga_ls8c_ard_3-2-1_105079_2022-01-15_final
2022-01-16 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-01-16_final
2022-01-19 10:26:29	ga_ls8c_ard_3-2-1_101079_2022-01-19_final
2022-01-22 10:57:46	ga_ls8c_ard_3-2-1_106080_2022-01-22_final
2022-01-30 11:45:34	ga_ls8c_ard_3-2-1_114076_2022-01-30_final
2022-02-10 09:48:06	ga_ls8c_ard_3-2-1_095076_2022-02-10_final
2022-02-11 10:32:58	ga_ls8c_ard_3-2-1_102080_2022-02-11_final
2022-02-14 09:24:10	ga_ls8c_ard_3-2-1_091078_2022-02-13_final
2022-02-14 09:25:45	ga_ls8c_ard_3-2-1_091082_2022-02-13_final
2022-02-17 09:56:38	ga_ls8c_ard_3-2-1_096082_2022-02-17_final
2022-02-24 10:02:47	ga_ls8c_ard_3-2-1_097082_2022-02-24_final
2022-03-03 10:06:09	ga_ls8c_ard_3-2-1_098075_2022-03-03_final
2022-03-03 11:46:14	ga_ls8c_ard_3-2-1_114078_2022-03-03_final
2022-03-06 10:36:15	ga_ls8c_ard_3-2-1_103073_2022-03-06_final
2022-03-17 10:20:49	ga_ls8c_ard_3-2-1_100081_2022-03-17_final
2022-03-18 09:23:59	ga_ls8c_ard_3-2-1_091078_2022-03-17_final
2022-03-18 09:25:35	ga_ls8c_ard_3-2-1_091082_2022-03-17_final
2022-03-21 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-03-21_final
2022-03-31 10:31:24	ga_ls8c_ard_3-2-1_102077_2022-03-31_final
2022-04-12 09:18:07	ga_ls8c_ard_3-2-1_090079_2022-04-11_final
2022-04-13 10:01:23	ga_ls8c_ard_3-2-1_097079_2022-04-13_final
2022-04-14 10:43:04	ga_ls8c_ard_3-2-1_104075_2022-04-14_final
2022-04-15 09:47:50	ga_ls8c_ard_3-2-1_095076_2022-04-15_final
2022-04-29 10:00:31	ga_ls8c_ard_3-2-1_097077_2022-04-29_final
2022-05-04 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-05-04_final
2022-05-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-05-17_final
2022-05-20 11:57:44	ga_ls8c_ard_3-2-1_116076_2022-05-20_final
2022-05-21 11:05:18	ga_ls8c_ard_3-2-1_107084_2022-05-21_final
2022-05-29 11:52:45	ga_ls8c_ard_3-2-1_115079_2022-05-29_final
2022-06-04 11:15:45	ga_ls8c_ard_3-2-1_109079_2022-06-04_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-22 09:27:05	ga_ls8c_ard_3-2-1_091085_2022-06-21_final
2022-07-04 11:26:44	ga_ls8c_ard_3-2-1_111075_2022-07-04_final
2022-07-07 10:18:45	ga_ls8c_ard_3-2-1_100075_2022-07-07_final
2022-07-10 10:47:39	ga_ls8c_ard_3-2-1_105070_2022-07-10_final
2022-07-14 10:24:54	ga_ls8c_ard_3-2-1_101075_2022-07-14_final
2022-07-20 09:48:17	ga_ls8c_ard_3-2-1_095076_2022-07-20_final
2022-07-23 10:22:25	ga_ls8c_ard_3-2-1_100084_2022-07-23_final
2022-07-27 11:33:02	ga_ls8c_ard_3-2-1_112075_2022-07-27_final
2022-07-29 09:44:12	ga_ls8c_ard_3-2-1_094081_2022-07-29_final
2022-08-05 11:26:57	ga_ls8c_ard_3-2-1_111075_2022-08-05_final
2022-09-09 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-09-09_final
2022-09-28 10:52:50	ga_ls8c_ard_3-2-1_105082_2022-09-28_final
2022-09-29 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-09-29_final
2022-10-06 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-06_final
2022-10-12 09:26:11	ga_ls8c_ard_3-2-1_091082_2022-10-11_final
2022-10-15 09:55:29	ga_ls8c_ard_3-2-1_096078_2022-10-15_final
2022-10-29 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-10-29_final
2022-11-02 09:42:28	ga_ls8c_ard_3-2-1_094076_2022-11-02_final
2022-11-06 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-11-06_final
2022-11-29 09:24:38	ga_ls8c_ard_3-2-1_091078_2022-11-28_final
2022-11-29 11:05:55	ga_ls8c_ard_3-2-1_107084_2022-11-29_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-20 09:43:26	ga_ls8c_ard_3-2-1_094079_2022-12-20_final
2022-12-23 10:15:05	ga_ls8c_ard_3-2-1_099081_2022-12-23_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-05 09:46:13	ga_ls8c_ard_3-2-1_094086_2023-01-05_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-19 11:34:57	ga_ls8c_ard_3-2-1_112080_2023-01-19_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-02-20 09:55:09	ga_ls8c_ard_3-2-1_096078_2023-02-20_final
2023-02-20 11:35:38	ga_ls8c_ard_3-2-1_112082_2023-02-20_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-08 11:32:39	ga_ls8c_ard_3-2-1_112075_2023-03-08_final
2023-03-16 10:41:35	ga_ls8c_ard_3-2-1_104071_2023-03-16_final
2023-03-19 09:36:45	ga_ls8c_ard_3-2-1_093079_2023-03-19_final
2023-03-22 10:05:12	ga_ls8c_ard_3-2-1_098073_2023-03-22_final
2023-03-23 10:50:03	ga_ls8c_ard_3-2-1_105077_2023-03-23_final
2023-04-07 10:08:36	ga_ls8c_ard_3-2-1_098082_2023-04-07_final
2023-04-13 09:34:36	ga_ls8c_ard_3-2-1_092090_2023-04-13_final
2023-04-21 10:20:24	ga_ls8c_ard_3-2-1_100081_2023-04-21_final
2023-04-24 09:14:02	ga_ls8c_ard_3-2-1_089085_2023-04-23_final
2023-04-26 10:36:57	ga_ls8c_ard_3-2-1_103076_2023-04-26_final
2023-04-27 09:44:07	ga_ls8c_ard_3-2-1_094083_2023-04-27_final
2023-04-29 09:31:45	ga_ls8c_ard_3-2-1_092083_2023-04-29_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-05-01 10:56:15	ga_ls8c_ard_3-2-1_106078_2023-05-01_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