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
2015-04-14 09:38:37	ga_ls8c_ard_3-0-0_093085_2015-04-14_final
2015-04-14 11:17:30	ga_ls8c_ard_3-0-0_109085_2015-04-14_final
2015-04-15 10:21:53	ga_ls8c_ard_3-0-0_100085_2015-04-15_final
2015-04-16 09:26:15	ga_ls8c_ard_3-0-0_091085_2015-04-15_final
2015-04-16 11:05:08	ga_ls8c_ard_3-0-0_107085_2015-04-16_final
2015-05-16 09:37:51	ga_ls8c_ard_3-0-0_093084_2015-05-16_final
2015-05-16 09:38:15	ga_ls8c_ard_3-0-0_093085_2015-05-16_final
2015-05-16 11:16:44	ga_ls8c_ard_3-0-0_109084_2015-05-16_final
2015-05-18 09:25:30	ga_ls8c_ard_3-0-0_091084_2015-05-17_final
2015-05-18 09:25:54	ga_ls8c_ard_3-0-0_091085_2015-05-17_final
2015-05-18 11:04:23	ga_ls8c_ard_3-0-0_107084_2015-05-18_final
2015-05-18 11:04:47	ga_ls8c_ard_3-0-0_107085_2015-05-18_final
2017-04-21 09:26:16	ga_ls8c_ard_3-0-0_091085_2017-04-20_final
2017-04-21 11:05:09	ga_ls8c_ard_3-0-0_107085_2017-04-21_final
2017-05-08 10:09:28	ga_ls8c_ard_3-0-0_098085_2017-05-08_final
2017-05-09 09:13:52	ga_ls8c_ard_3-0-0_089085_2017-05-08_final
2017-05-10 09:56:44	ga_ls8c_ard_3-0-0_096084_2017-05-10_final
2017-05-10 09:57:08	ga_ls8c_ard_3-0-0_096085_2017-05-10_final
2017-05-10 11:36:01	ga_ls8c_ard_3-0-0_112085_2017-05-10_final
2017-06-09 10:09:24	ga_ls8c_ard_3-0-0_098084_2017-06-09_final
2017-06-09 10:09:48	ga_ls8c_ard_3-0-0_098085_2017-06-09_final
2017-06-10 09:14:11	ga_ls8c_ard_3-0-0_089085_2017-06-09_final
2017-06-11 09:57:03	ga_ls8c_ard_3-0-0_096084_2017-06-11_final
2017-06-11 09:57:27	ga_ls8c_ard_3-0-0_096085_2017-06-11_final
2017-06-11 11:36:20	ga_ls8c_ard_3-0-0_112085_2017-06-11_final
2017-06-25 10:09:29	ga_ls8c_ard_3-0-0_098084_2017-06-25_final
2017-06-25 10:09:53	ga_ls8c_ard_3-0-0_098085_2017-06-25_final
2017-06-26 09:14:16	ga_ls8c_ard_3-0-0_089085_2017-06-25_final
2017-06-27 09:57:08	ga_ls8c_ard_3-0-0_096084_2017-06-27_final
2017-06-27 09:57:32	ga_ls8c_ard_3-0-0_096085_2017-06-27_final
2017-06-27 11:36:25	ga_ls8c_ard_3-0-0_112085_2017-06-27_final
2017-07-17 09:32:29	ga_ls8c_ard_3-0-0_092084_2017-07-17_final
2017-07-17 09:32:53	ga_ls8c_ard_3-0-0_092085_2017-07-17_final
2017-07-17 11:11:46	ga_ls8c_ard_3-0-0_108085_2017-07-17_final
2017-07-18 10:16:10	ga_ls8c_ard_3-0-0_099085_2017-07-18_final
2017-07-19 09:20:33	ga_ls8c_ard_3-0-0_090085_2017-07-18_final
2017-07-19 10:59:02	ga_ls8c_ard_3-0-0_106084_2017-07-19_final
2017-07-27 10:10:03	ga_ls8c_ard_3-0-0_098085_2017-07-27_final
2017-07-28 09:14:03	ga_ls8c_ard_3-0-0_089084_2017-07-27_final
2017-07-28 09:14:27	ga_ls8c_ard_3-0-0_089085_2017-07-27_final
2017-07-29 09:57:43	ga_ls8c_ard_3-0-0_096085_2017-07-29_final
2017-07-29 11:36:36	ga_ls8c_ard_3-0-0_112085_2017-07-29_final
2017-08-28 10:10:14	ga_ls8c_ard_3-0-0_098085_2017-08-28_final
2017-08-29 09:14:13	ga_ls8c_ard_3-0-0_089084_2017-08-28_final
2017-08-29 09:14:37	ga_ls8c_ard_3-0-0_089085_2017-08-28_final
2017-08-30 09:57:52	ga_ls8c_ard_3-0-0_096085_2017-08-30_final
2017-08-30 11:36:45	ga_ls8c_ard_3-0-0_112085_2017-08-30_final
2022-05-19 09:39:10	ga_ls8c_ard_3-2-1_093085_2022-05-19_final
2022-05-21 09:26:49	ga_ls8c_ard_3-2-1_091085_2022-05-20_final
2022-05-22 10:10:04	ga_ls8c_ard_3-2-1_098085_2022-05-22_final
2022-06-04 09:39:16	ga_ls8c_ard_3-2-1_093085_2022-06-04_final
2022-06-05 10:22:09	ga_ls8c_ard_3-2-1_100084_2022-06-05_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-15 09:20:52	ga_ls8c_ard_3-2-1_090085_2022-06-14_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-07-13 11:24:31	ga_ls8c_ard_3-2-1_110085_2022-07-13_final
2022-07-15 09:33:16	ga_ls8c_ard_3-2-1_092085_2022-07-15_final
2022-07-15 11:11:45	ga_ls8c_ard_3-2-1_108084_2022-07-15_final
2022-07-16 10:16:32	ga_ls8c_ard_3-2-1_099085_2022-07-16_final
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-18 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-18_final
2022-07-18 11:42:41	ga_ls8c_ard_3-2-1_113084_2022-07-18_final
2022-07-20 09:51:52	ga_ls8c_ard_3-2-1_095085_2022-07-20_final
2022-07-20 11:30:22	ga_ls8c_ard_3-2-1_111084_2022-07-20_final
2022-07-22 09:39:32	ga_ls8c_ard_3-2-1_093085_2022-07-22_final
2022-07-23 10:22:25	ga_ls8c_ard_3-2-1_100084_2022-07-23_final
2022-07-24 09:27:12	ga_ls8c_ard_3-2-1_091085_2022-07-23_final
2022-07-26 09:14:52	ga_ls8c_ard_3-2-1_089085_2022-07-25_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-07-29 11:24:41	ga_ls8c_ard_3-2-1_110085_2022-07-29_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-01 10:16:44	ga_ls8c_ard_3-2-1_099085_2022-08-01_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-08 09:39:49	ga_ls8c_ard_3-2-1_093085_2022-09-08_final
2022-10-26 09:39:51	ga_ls8c_ard_3-2-1_093085_2022-10-26_final
2022-10-28 09:27:30	ga_ls8c_ard_3-2-1_091085_2022-10-27_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-10-30 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-10-29_final
2022-12-11 09:52:07	ga_ls8c_ard_3-2-1_095085_2022-12-11_final
2022-12-20 11:24:43	ga_ls8c_ard_3-2-1_110085_2022-12-20_final
2022-12-22 09:33:26	ga_ls8c_ard_3-2-1_092085_2022-12-22_final
2022-12-23 10:16:41	ga_ls8c_ard_3-2-1_099085_2022-12-23_final
2022-12-24 09:21:04	ga_ls8c_ard_3-2-1_090085_2022-12-23_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-31 09:27:17	ga_ls8c_ard_3-2-1_091085_2022-12-30_final
2023-01-01 10:10:33	ga_ls8c_ard_3-2-1_098085_2023-01-01_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-03 09:58:11	ga_ls8c_ard_3-2-1_096085_2023-01-03_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-05 11:24:42	ga_ls8c_ard_3-2-1_110085_2023-01-05_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-17 10:10:25	ga_ls8c_ard_3-2-1_098085_2023-01-17_final
2023-01-18 09:14:47	ga_ls8c_ard_3-2-1_089085_2023-01-17_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-21 11:24:37	ga_ls8c_ard_3-2-1_110085_2023-01-21_final
2023-01-23 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-01-23_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years