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
2022-07-27 09:56:09	ga_ls8c_ard_3-2-1_096080_2022-07-27_final
2022-08-05 11:29:44	ga_ls8c_ard_3-2-1_111082_2022-08-05_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-15 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-08-15_final
2022-08-21 11:29:49	ga_ls8c_ard_3-2-1_111082_2022-08-21_final
2022-08-23 11:13:04	ga_ls8c_ard_3-2-1_109071_2022-08-23_final
2022-08-23 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-08-23_final
2022-08-25 09:27:01	ga_ls8c_ard_3-2-1_091084_2022-08-24_final
2022-08-30 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-08-30_final
2022-09-01 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-09-01_final
2022-09-13 09:53:36	ga_ls8c_ard_3-2-1_096073_2022-09-13_final
2022-09-17 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-09-17_final
2022-09-19 10:55:02	ga_ls8c_ard_3-2-1_106072_2022-09-19_final
2022-09-22 11:27:08	ga_ls8c_ard_3-2-1_111075_2022-09-22_final
2022-09-28 10:52:27	ga_ls8c_ard_3-2-1_105081_2022-09-28_final
2022-09-29 11:35:42	ga_ls8c_ard_3-2-1_112081_2022-09-29_final
2022-10-02 10:24:07	ga_ls8c_ard_3-2-1_101072_2022-10-02_final
2022-10-03 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-10-03_final
2022-10-03 11:11:22	ga_ls8c_ard_3-2-1_108082_2022-10-03_final
2022-10-08 09:52:10	ga_ls8c_ard_3-2-1_095085_2022-10-08_final
2022-10-10 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-10-10_final
2022-10-11 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-10-11_final
2022-10-12 11:04:40	ga_ls8c_ard_3-2-1_107081_2022-10-12_final
2022-10-23 10:45:01	ga_ls8c_ard_3-2-1_104078_2022-10-23_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-10-26 09:37:03	ga_ls8c_ard_3-2-1_093078_2022-10-26_final
2022-10-28 09:26:18	ga_ls8c_ard_3-2-1_091082_2022-10-27_final
2022-10-29 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-10-29_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-05 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-11-05_final
2022-11-06 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-11-06_final
2022-11-10 10:31:52	ga_ls8c_ard_3-2-1_102076_2022-11-10_final
2022-11-17 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-11-17_final
2022-12-02 09:53:57	ga_ls8c_ard_3-2-1_096074_2022-12-02_final
2022-12-03 10:36:00	ga_ls8c_ard_3-2-1_103071_2022-12-03_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-03 10:38:00	ga_ls8c_ard_3-2-1_103076_2022-12-03_final
2022-12-04 09:41:59	ga_ls8c_ard_3-2-1_094075_2022-12-04_final
2022-12-05 10:27:38	ga_ls8c_ard_3-2-1_101081_2022-12-05_final
2022-12-09 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-12-09_final
2022-12-14 10:19:00	ga_ls8c_ard_3-2-1_100075_2022-12-14_final
2022-12-18 09:53:26	ga_ls8c_ard_3-2-1_096073_2022-12-18_final
2022-12-20 09:44:14	ga_ls8c_ard_3-2-1_094081_2022-12-20_final
2022-12-21 10:25:29	ga_ls8c_ard_3-2-1_101076_2022-12-21_final
2022-12-22 09:30:38	ga_ls8c_ard_3-2-1_092078_2022-12-22_final
2022-12-23 10:15:29	ga_ls8c_ard_3-2-1_099082_2022-12-23_final
2022-12-28 10:30:04	ga_ls8c_ard_3-2-1_102072_2022-12-28_final
2022-12-28 10:32:28	ga_ls8c_ard_3-2-1_102078_2022-12-28_final
2023-01-04 10:36:40	ga_ls8c_ard_3-2-1_103073_2023-01-04_final
2023-01-11 10:42:24	ga_ls8c_ard_3-2-1_104072_2023-01-11_final
2023-01-11 10:42:48	ga_ls8c_ard_3-2-1_104073_2023-01-11_final
2023-01-11 10:45:35	ga_ls8c_ard_3-2-1_104080_2023-01-11_final
2023-01-13 10:31:13	ga_ls8c_ard_3-2-1_102075_2023-01-13_final
2023-02-04 11:35:26	ga_ls8c_ard_3-2-1_112081_2023-02-04_final
2023-02-05 10:37:49	ga_ls8c_ard_3-2-1_103076_2023-02-05_final
2023-02-08 11:08:42	ga_ls8c_ard_3-2-1_108076_2023-02-08_final
2023-02-09 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-02-09_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-13 09:48:17	ga_ls8c_ard_3-2-1_095076_2023-02-13_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-20 09:57:09	ga_ls8c_ard_3-2-1_096083_2023-02-20_final
2023-02-22 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-02-22_final
2023-03-15 09:59:55	ga_ls8c_ard_3-2-1_097075_2023-03-15_final
2023-03-16 10:40:47	ga_ls8c_ard_3-2-1_104069_2023-03-16_final
2023-03-19 09:37:33	ga_ls8c_ard_3-2-1_093081_2023-03-19_final
2023-03-21 09:25:33	ga_ls8c_ard_3-2-1_091082_2023-03-20_final
2023-03-23 10:48:03	ga_ls8c_ard_3-2-1_105072_2023-03-23_final
2023-03-24 09:52:49	ga_ls8c_ard_3-2-1_096073_2023-03-24_final
2023-03-26 09:45:38	ga_ls8c_ard_3-2-1_094086_2023-03-26_final
2023-03-26 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-03-26_final
2023-03-27 10:26:06	ga_ls8c_ard_3-2-1_101079_2023-03-27_final
2023-04-04 09:36:58	ga_ls8c_ard_3-2-1_093080_2023-04-04_final
2023-04-06 11:03:50	ga_ls8c_ard_3-2-1_107081_2023-04-06_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-04-18 11:29:12	ga_ls8c_ard_3-2-1_111083_2023-04-18_final
2023-04-24 10:52:07	ga_ls8c_ard_3-2-1_105083_2023-04-24_final
2023-04-27 11:22:12	ga_ls8c_ard_3-2-1_110081_2023-04-27_final
2023-04-28 10:22:59	ga_ls8c_ard_3-2-1_101072_2023-04-28_final
2023-04-29 11:09:50	ga_ls8c_ard_3-2-1_108081_2023-04-29_final
2023-04-30 10:11:48	ga_ls8c_ard_3-2-1_099075_2023-04-30_final
2023-05-01 09:18:58	ga_ls8c_ard_3-2-1_090082_2023-04-30_final
2023-05-12 10:36:44	ga_ls8c_ard_3-2-1_103076_2023-05-12_final
2023-05-20 09:50:04	ga_ls8c_ard_3-2-1_095083_2023-05-20_final
2023-05-20 11:28:57	ga_ls8c_ard_3-2-1_111083_2023-05-20_final
2023-05-22 11:11:49	ga_ls8c_ard_3-2-1_109071_2023-05-22_final
2023-05-28 10:34:22	ga_ls8c_ard_3-2-1_103070_2023-05-28_final
2023-05-28 10:36:21	ga_ls8c_ard_3-2-1_103075_2023-05-28_final
2023-05-31 09:31:10	ga_ls8c_ard_3-2-1_092082_2023-05-31_final
2023-06-04 10:44:34	ga_ls8c_ard_3-2-1_104080_2023-06-04_final
2023-06-23 09:36:18	ga_ls8c_ard_3-2-1_093079_2023-06-23_final
2023-07-07 09:49:16	ga_ls8c_ard_3-2-1_095080_2023-07-07_final
2023-07-13 10:52:18	ga_ls8c_ard_3-2-1_105083_2023-07-13_final
2023-07-14 09:55:53	ga_ls8c_ard_3-2-1_096081_2023-07-14_final
2023-07-29 10:52:25	ga_ls8c_ard_3-2-1_105083_2023-07-29_final
2023-08-12 11:00:50	ga_ls8c_ard_3-2-1_107073_2023-08-12_final
2023-08-12 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-08-12_final
2023-08-16 10:37:22	ga_ls8c_ard_3-2-1_103076_2023-08-16_final
2023-08-18 10:24:38	ga_ls8c_ard_3-2-1_101075_2023-08-18_final
2023-08-24 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-08-24_final
2023-09-04 09:31:26	ga_ls8c_ard_3-2-1_092081_2023-09-04_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