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
2022-07-15 09:29:16	ga_ls8c_ard_3-2-1_092075_2022-07-14_final
2022-07-27 11:36:14	ga_ls8c_ard_3-2-1_112083_2022-07-27_final
2022-08-05 09:51:39	ga_ls8c_ard_3-2-1_095084_2022-08-05_final
2022-08-15 10:25:36	ga_ls8c_ard_3-2-1_101076_2022-08-15_final
2022-08-17 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-08-17_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-08-23 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-08-23_final
2022-08-25 09:27:24	ga_ls8c_ard_3-2-1_091085_2022-08-24_final
2022-08-28 11:36:48	ga_ls8c_ard_3-2-1_112084_2022-08-28_final
2022-09-01 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-09-01_final
2022-09-03 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-09-03_final
2022-09-03 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-09-03_final
2022-09-04 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-09-04_final
2022-09-08 09:35:25	ga_ls8c_ard_3-2-1_093074_2022-09-08_final
2022-09-11 10:05:33	ga_ls8c_ard_3-2-1_098072_2022-09-11_final
2022-09-11 10:07:09	ga_ls8c_ard_3-2-1_098076_2022-09-11_final
2022-09-15 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-09-15_final
2022-09-17 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-09-17_final
2022-09-18 11:51:27	ga_ls8c_ard_3-2-1_115074_2022-09-18_final
2022-09-19 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-09-18_final
2022-09-24 09:35:53	ga_ls8c_ard_3-2-1_093075_2022-09-24_final
2022-09-25 10:18:45	ga_ls8c_ard_3-2-1_100074_2022-09-25_final
2022-09-28 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-09-27_final
2022-10-12 09:25:23	ga_ls8c_ard_3-2-1_091080_2022-10-11_final
2022-10-13 10:04:15	ga_ls8c_ard_3-2-1_098069_2022-10-13_final
2022-10-20 10:12:06	ga_ls8c_ard_3-2-1_099073_2022-10-20_final
2022-10-21 10:55:46	ga_ls8c_ard_3-2-1_106074_2022-10-21_final
2022-10-22 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-22_final
2022-10-26 11:17:32	ga_ls8c_ard_3-2-1_109082_2022-10-26_final
2022-10-29 10:04:47	ga_ls8c_ard_3-2-1_098070_2022-10-29_final
2022-10-29 10:05:35	ga_ls8c_ard_3-2-1_098072_2022-10-29_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-11-05 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-11-05_final
2022-11-07 11:42:40	ga_ls8c_ard_3-2-1_113083_2022-11-07_final
2022-11-08 10:41:27	ga_ls8c_ard_3-2-1_104069_2022-11-08_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-12 10:20:41	ga_ls8c_ard_3-2-1_100079_2022-11-12_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-20 09:33:58	ga_ls8c_ard_3-2-1_092086_2022-11-20_final
2022-11-20 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-11-20_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-11-25 11:27:02	ga_ls8c_ard_3-2-1_111075_2022-11-25_final
2022-12-02 11:36:25	ga_ls8c_ard_3-2-1_112083_2022-12-02_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-06 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-12-06_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-08 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-12-07_final
2022-12-09 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-12-09_final
2022-12-10 10:44:09	ga_ls8c_ard_3-2-1_104076_2022-12-10_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-20 11:22:19	ga_ls8c_ard_3-2-1_110079_2022-12-20_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-22 09:29:50	ga_ls8c_ard_3-2-1_092076_2022-12-21_final
2022-12-29 09:39:15	ga_ls8c_ard_3-2-1_093084_2022-12-29_final
2023-01-01 10:08:33	ga_ls8c_ard_3-2-1_098080_2023-01-01_final
2023-01-05 09:44:38	ga_ls8c_ard_3-2-1_094082_2023-01-05_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-08 10:16:19	ga_ls8c_ard_3-2-1_099084_2023-01-08_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-19 09:57:40	ga_ls8c_ard_3-2-1_096084_2023-01-19_final
2023-01-21 09:45:20	ga_ls8c_ard_3-2-1_094084_2023-01-21_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-31 10:19:17	ga_ls8c_ard_3-2-1_100076_2023-01-31_final
2023-02-07 10:24:39	ga_ls8c_ard_3-2-1_101074_2023-02-07_final
2023-02-09 10:16:39	ga_ls8c_ard_3-2-1_099085_2023-02-09_final
2023-02-15 09:35:54	ga_ls8c_ard_3-2-1_093076_2023-02-15_final
2023-02-17 09:25:07	ga_ls8c_ard_3-2-1_091080_2023-02-16_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-02-17 11:00:24	ga_ls8c_ard_3-2-1_107071_2023-02-17_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-02-24 11:10:49	ga_ls8c_ard_3-2-1_108082_2023-02-24_final
2023-02-26 10:54:26	ga_ls8c_ard_3-2-1_106072_2023-02-26_final
2023-02-26 10:56:02	ga_ls8c_ard_3-2-1_106076_2023-02-26_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-03 11:17:22	ga_ls8c_ard_3-2-1_109083_2023-03-03_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-05 11:00:36	ga_ls8c_ard_3-2-1_107072_2023-03-05_final
2023-03-06 10:07:45	ga_ls8c_ard_3-2-1_098079_2023-03-06_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_final
2023-03-10 09:44:11	ga_ls8c_ard_3-2-1_094082_2023-03-10_final
2023-03-14 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-03-13_final
2023-03-14 10:54:21	ga_ls8c_ard_3-2-1_106072_2023-03-14_final
2023-03-14 10:54:45	ga_ls8c_ard_3-2-1_106073_2023-03-14_final
2023-03-31 11:37:26	ga_ls8c_ard_3-2-1_113072_2023-03-31_final
2023-04-02 09:46:58	ga_ls8c_ard_3-2-1_095074_2023-04-02_final
2023-04-08 10:47:02	ga_ls8c_ard_3-2-1_105070_2023-04-08_final
2023-04-11 09:45:22	ga_ls8c_ard_3-2-1_094086_2023-04-11_final
2023-04-13 11:11:06	ga_ls8c_ard_3-2-1_108084_2023-04-13_final
2023-04-14 11:51:34	ga_ls8c_ard_3-2-1_115077_2023-04-14_final
2023-04-16 10:01:30	ga_ls8c_ard_3-2-1_097080_2023-04-16_final
2023-04-18 11:29:36	ga_ls8c_ard_3-2-1_111084_2023-04-18_final
2023-04-19 10:28:47	ga_ls8c_ard_3-2-1_102071_2023-04-19_final
2023-05-02 09:58:14	ga_ls8c_ard_3-2-1_097072_2023-05-02_final
2023-05-05 10:27:54	ga_ls8c_ard_3-2-1_102069_2023-05-05_final
2023-05-06 11:11:56	ga_ls8c_ard_3-2-1_109071_2023-05-06_final
2023-05-08 09:25:03	ga_ls8c_ard_3-2-1_091082_2023-05-07_final
2023-05-13 09:40:19	ga_ls8c_ard_3-2-1_094074_2023-05-13_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_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