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
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-09-05 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-09-04_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-08 11:13:06	ga_ls8c_ard_3-2-1_109071_2022-09-08_final
2022-09-20 11:40:17	ga_ls8c_ard_3-2-1_113077_2022-09-20_final
2022-09-26 11:01:13	ga_ls8c_ard_3-2-1_107072_2022-09-26_final
2022-09-27 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-09-27_final
2022-09-27 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-09-27_final
2022-09-27 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-09-27_final
2022-10-01 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-10-01_final
2022-10-02 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-10-02_final
2022-10-04 10:12:08	ga_ls8c_ard_3-2-1_099073_2022-10-04_final
2022-10-06 10:00:10	ga_ls8c_ard_3-2-1_097074_2022-10-06_final
2022-10-06 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-06_final
2022-10-07 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-07_final
2022-10-07 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-07_final
2022-10-08 11:29:51	ga_ls8c_ard_3-2-1_111082_2022-10-08_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-13 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-10-13_final
2022-10-13 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-10-13_final
2022-10-14 10:47:30	ga_ls8c_ard_3-2-1_105069_2022-10-14_final
2022-10-16 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-10-16_final
2022-10-16 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-10-16_final
2022-10-18 10:27:13	ga_ls8c_ard_3-2-1_101080_2022-10-18_final
2022-10-21 10:57:22	ga_ls8c_ard_3-2-1_106078_2022-10-21_final
2022-10-22 10:02:33	ga_ls8c_ard_3-2-1_097080_2022-10-22_final
2022-10-26 09:36:16	ga_ls8c_ard_3-2-1_093076_2022-10-26_final
2022-10-27 10:21:31	ga_ls8c_ard_3-2-1_100081_2022-10-27_final
2022-10-28 11:04:00	ga_ls8c_ard_3-2-1_107079_2022-10-28_final
2022-10-29 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-10-29_final
2022-11-02 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-11-02_final
2022-11-03 10:24:32	ga_ls8c_ard_3-2-1_101073_2022-11-03_final
2022-11-03 10:25:44	ga_ls8c_ard_3-2-1_101076_2022-11-03_final
2022-11-06 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-11-06_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-09 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-11-09_final
2022-11-10 10:31:52	ga_ls8c_ard_3-2-1_102076_2022-11-10_final
2022-11-11 11:13:55	ga_ls8c_ard_3-2-1_109073_2022-11-11_final
2022-11-13 11:02:20	ga_ls8c_ard_3-2-1_107075_2022-11-13_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-16 09:52:43	ga_ls8c_ard_3-2-1_096071_2022-11-16_final
2022-11-16 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-11-16_final
2022-11-21 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-11-21_final
2022-11-23 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-11-23_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-11-25 11:25:26	ga_ls8c_ard_3-2-1_111071_2022-11-25_final
2022-11-27 09:38:12	ga_ls8c_ard_3-2-1_093081_2022-11-27_final
2022-11-29 09:26:14	ga_ls8c_ard_3-2-1_091082_2022-11-28_final
2022-11-29 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-29_final
2022-11-29 11:01:56	ga_ls8c_ard_3-2-1_107074_2022-11-29_final
2022-11-30 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-30_final
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_final
2022-12-05 10:26:50	ga_ls8c_ard_3-2-1_101079_2022-12-05_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-07 10:11:41	ga_ls8c_ard_3-2-1_099072_2022-12-07_final
2022-12-07 11:53:45	ga_ls8c_ard_3-2-1_115080_2022-12-07_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-10 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-12-10_final
2022-12-10 10:43:45	ga_ls8c_ard_3-2-1_104075_2022-12-10_final
2022-12-11 09:51:43	ga_ls8c_ard_3-2-1_095084_2022-12-11_final
2022-12-15 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-12-14_final
2022-12-15 09:28:09	ga_ls8c_ard_3-2-1_091087_2022-12-14_final
2022-12-16 10:05:49	ga_ls8c_ard_3-2-1_098073_2022-12-16_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-25 10:01:33	ga_ls8c_ard_3-2-1_097078_2022-12-25_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-31 09:26:05	ga_ls8c_ard_3-2-1_091082_2022-12-30_final
2022-12-31 09:27:41	ga_ls8c_ard_3-2-1_091086_2022-12-30_final
2023-01-01 11:47:02	ga_ls8c_ard_3-2-1_114079_2023-01-01_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-04 10:35:04	ga_ls8c_ard_3-2-1_103069_2023-01-04_final
2023-01-14 11:16:51	ga_ls8c_ard_3-2-1_109081_2023-01-14_final
2023-01-16 09:27:34	ga_ls8c_ard_3-2-1_091086_2023-01-15_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-01-23 09:32:12	ga_ls8c_ard_3-2-1_092082_2023-01-23_final
2023-01-23 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-01-23_final
2023-01-23 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-01-23_final
2023-01-25 09:18:39	ga_ls8c_ard_3-2-1_090079_2023-01-24_final
2023-01-26 09:57:08	ga_ls8c_ard_3-2-1_097067_2023-01-26_final
2023-01-26 10:02:19	ga_ls8c_ard_3-2-1_097080_2023-01-26_final
2023-02-01 09:25:15	ga_ls8c_ard_3-2-1_091080_2023-01-31_final
2023-02-05 10:35:01	ga_ls8c_ard_3-2-1_103069_2023-02-05_final
2023-02-05 10:36:37	ga_ls8c_ard_3-2-1_103073_2023-02-05_final
2023-02-08 09:32:13	ga_ls8c_ard_3-2-1_092082_2023-02-08_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-10 10:58:19	ga_ls8c_ard_3-2-1_106081_2023-02-10_final
2023-02-11 09:58:41	ga_ls8c_ard_3-2-1_097071_2023-02-11_final
2023-02-11 11:40:46	ga_ls8c_ard_3-2-1_113079_2023-02-11_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-18 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-02-18_final
2023-02-22 09:44:44	ga_ls8c_ard_3-2-1_094083_2023-02-22_final
2023-02-27 11:39:42	ga_ls8c_ard_3-2-1_113077_2023-02-27_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_final
2023-03-02 10:31:43	ga_ls8c_ard_3-2-1_102077_2023-03-02_final
2023-03-11 10:25:04	ga_ls8c_ard_3-2-1_101076_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