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
2022-03-19 11:44:31	ga_ls8c_ard_3-2-1_114074_2022-03-19_final
2022-03-23 09:46:03	ga_ls8c_ard_3-2-1_094087_2022-03-23_final
2022-03-23 11:22:56	ga_ls8c_ard_3-2-1_110082_2022-03-23_final
2022-03-25 11:06:57	ga_ls8c_ard_3-2-1_108073_2022-03-25_final
2022-03-26 10:15:42	ga_ls8c_ard_3-2-1_099084_2022-03-26_final
2022-03-30 11:27:25	ga_ls8c_ard_3-2-1_111078_2022-03-30_final
2022-04-01 11:12:16	ga_ls8c_ard_3-2-1_109071_2022-04-01_final
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-04 10:09:53	ga_ls8c_ard_3-2-1_098085_2022-04-04_final
2022-04-11 10:14:56	ga_ls8c_ard_3-2-1_099082_2022-04-11_final
2022-04-13 10:03:23	ga_ls8c_ard_3-2-1_097084_2022-04-13_final
2022-04-20 10:03:58	ga_ls8c_ard_3-2-1_098070_2022-04-20_final
2022-04-26 09:32:26	ga_ls8c_ard_3-2-1_092084_2022-04-26_final
2022-05-08 11:36:08	ga_ls8c_ard_3-2-1_112084_2022-05-08_final
2022-05-10 09:45:42	ga_ls8c_ard_3-2-1_094086_2022-05-10_final
2022-05-13 10:13:50	ga_ls8c_ard_3-2-1_099079_2022-05-13_final
2022-05-26 11:23:02	ga_ls8c_ard_3-2-1_110082_2022-05-26_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-07 10:05:01	ga_ls8c_ard_3-2-1_098072_2022-06-07_final
2022-06-07 11:44:42	ga_ls8c_ard_3-2-1_114074_2022-06-07_final
2022-06-08 09:12:12	ga_ls8c_ard_3-2-1_089079_2022-06-07_final
2022-06-09 09:53:29	ga_ls8c_ard_3-2-1_096074_2022-06-09_final
2022-06-18 09:51:23	ga_ls8c_ard_3-2-1_095084_2022-06-18_final
2022-06-22 11:05:11	ga_ls8c_ard_3-2-1_107083_2022-06-22_final
2022-06-23 10:09:33	ga_ls8c_ard_3-2-1_098083_2022-06-23_final
2022-06-25 09:58:00	ga_ls8c_ard_3-2-1_096085_2022-06-25_final
2022-06-27 09:41:15	ga_ls8c_ard_3-2-1_094074_2022-06-27_final
2022-06-29 11:07:23	ga_ls8c_ard_3-2-1_108073_2022-06-29_final
2022-06-29 11:09:47	ga_ls8c_ard_3-2-1_108079_2022-06-29_final
2022-07-03 09:06:35	ga_ls8c_ard_3-2-1_088080_2022-07-02_final
2022-07-06 09:39:52	ga_ls8c_ard_3-2-1_093086_2022-07-06_final
2022-07-09 10:04:47	ga_ls8c_ard_3-2-1_098071_2022-07-09_final
2022-07-13 09:41:15	ga_ls8c_ard_3-2-1_094074_2022-07-13_final
2022-07-13 11:24:07	ga_ls8c_ard_3-2-1_110084_2022-07-13_final
2022-07-14 10:23:18	ga_ls8c_ard_3-2-1_101071_2022-07-14_final
2022-07-15 11:05:46	ga_ls8c_ard_3-2-1_108069_2022-07-15_final
2022-07-22 09:37:09	ga_ls8c_ard_3-2-1_093079_2022-07-22_final
2022-07-22 09:40:44	ga_ls8c_ard_3-2-1_093088_2022-07-22_final
2022-07-25 10:07:41	ga_ls8c_ard_3-2-1_098078_2022-07-25_final
2022-08-02 09:21:31	ga_ls8c_ard_3-2-1_090086_2022-08-01_final
2022-08-06 10:28:56	ga_ls8c_ard_3-2-1_102069_2022-08-06_final
2022-08-09 11:00:15	ga_ls8c_ard_3-2-1_107070_2022-08-09_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-24 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-08-24_final
2022-08-25 09:25:49	ga_ls8c_ard_3-2-1_091081_2022-08-24_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-08-26 11:47:57	ga_ls8c_ard_3-2-1_114081_2022-08-26_final
2022-08-27 10:47:33	ga_ls8c_ard_3-2-1_105069_2022-08-27_final
2022-09-01 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-09-01_final
2022-09-03 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-09-03_final
2022-09-03 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-09-03_final
2022-09-11 10:09:56	ga_ls8c_ard_3-2-1_098083_2022-09-11_final
2022-09-15 09:46:50	ga_ls8c_ard_3-2-1_094087_2022-09-15_final
2022-09-15 11:24:08	ga_ls8c_ard_3-2-1_110083_2022-09-15_final
2022-09-17 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-09-17_final
2022-09-17 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-09-17_final
2022-09-23 10:29:31	ga_ls8c_ard_3-2-1_102070_2022-09-23_final
2022-09-24 11:12:47	ga_ls8c_ard_3-2-1_109070_2022-09-24_final
2022-09-29 09:53:38	ga_ls8c_ard_3-2-1_096073_2022-09-29_final
2022-10-01 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-10-01_final
2022-10-05 10:55:24	ga_ls8c_ard_3-2-1_106073_2022-10-05_final
2022-10-06 09:58:58	ga_ls8c_ard_3-2-1_097071_2022-10-06_final
2022-10-11 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-10-11_final
2022-10-13 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-10-13_final
2022-10-17 09:41:33	ga_ls8c_ard_3-2-1_094074_2022-10-17_final
2022-10-19 09:34:01	ga_ls8c_ard_3-2-1_092086_2022-10-19_final
2022-10-19 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-10-19_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-11-06 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-11-05_final
2022-11-11 09:37:50	ga_ls8c_ard_3-2-1_093080_2022-11-11_final
2022-11-12 10:20:17	ga_ls8c_ard_3-2-1_100078_2022-11-12_final
2022-11-13 09:23:51	ga_ls8c_ard_3-2-1_091076_2022-11-12_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-08 09:18:27	ga_ls8c_ard_3-2-1_090078_2022-12-07_final
2022-12-08 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-12-07_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-11 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-12-11_final
2022-12-16 10:05:25	ga_ls8c_ard_3-2-1_098072_2022-12-16_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2023-01-01 11:47:50	ga_ls8c_ard_3-2-1_114081_2023-01-01_final
2023-01-05 09:41:02	ga_ls8c_ard_3-2-1_094073_2023-01-05_final
2023-01-07 09:33:03	ga_ls8c_ard_3-2-1_092084_2023-01-07_final
2023-01-09 09:23:05	ga_ls8c_ard_3-2-1_090090_2023-01-08_final
2023-01-15 10:20:01	ga_ls8c_ard_3-2-1_100078_2023-01-15_final
2023-01-16 09:25:11	ga_ls8c_ard_3-2-1_091080_2023-01-15_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-24 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-01-24_final
2023-02-06 11:19:29	ga_ls8c_ard_3-2-1_110072_2023-02-06_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-19 09:13:07	ga_ls8c_ard_3-2-1_089081_2023-02-18_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-24 09:33:55	ga_ls8c_ard_3-2-1_092087_2023-02-24_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-03-08 11:31:51	ga_ls8c_ard_3-2-1_112073_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