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
2022-08-10 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-08-10_final
2022-08-22 10:30:36	ga_ls8c_ard_3-2-1_102073_2022-08-22_final
2022-08-27 10:47:09	ga_ls8c_ard_3-2-1_105068_2022-08-27_final
2022-09-02 10:16:26	ga_ls8c_ard_3-2-1_099084_2022-09-02_final
2022-09-03 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-09-02_final
2022-09-04 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-09-04_final
2022-09-04 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-09-04_final
2022-09-05 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-09-04_final
2022-09-08 09:35:01	ga_ls8c_ard_3-2-1_093073_2022-09-08_final
2022-09-09 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-09-09_final
2022-09-11 10:04:21	ga_ls8c_ard_3-2-1_098069_2022-09-11_final
2022-09-13 09:57:59	ga_ls8c_ard_3-2-1_096084_2022-09-13_final
2022-09-15 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-09-15_final
2022-09-17 09:34:29	ga_ls8c_ard_3-2-1_092087_2022-09-17_final
2022-09-18 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-09-18_final
2022-09-18 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-09-18_final
2022-09-19 09:17:21	ga_ls8c_ard_3-2-1_090075_2022-09-18_final
2022-09-19 09:18:32	ga_ls8c_ard_3-2-1_090078_2022-09-18_final
2022-09-26 09:29:07	ga_ls8c_ard_3-2-1_091089_2022-09-25_final
2022-09-28 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-09-28_final
2022-09-29 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-09-29_final
2022-10-01 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-10-01_final
2022-10-01 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-10-01_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-09 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-10-09_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-20 11:51:47	ga_ls8c_ard_3-2-1_115075_2022-10-20_final
2022-11-01 10:34:54	ga_ls8c_ard_3-2-1_103068_2022-11-01_final
2022-11-02 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-11-02_final
2022-11-04 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-11-04_final
2022-11-04 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-11-04_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-06 09:22:55	ga_ls8c_ard_3-2-1_090089_2022-11-05_final
2022-11-08 10:43:27	ga_ls8c_ard_3-2-1_104074_2022-11-08_final
2022-11-13 09:27:51	ga_ls8c_ard_3-2-1_091086_2022-11-12_final
2022-11-15 09:13:28	ga_ls8c_ard_3-2-1_089081_2022-11-14_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-11-27 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-11-27_final
2022-12-02 09:52:45	ga_ls8c_ard_3-2-1_096071_2022-12-02_final
2022-12-02 11:33:14	ga_ls8c_ard_3-2-1_112075_2022-12-02_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-12 10:28:35	ga_ls8c_ard_3-2-1_102068_2022-12-12_final
2022-12-13 09:38:56	ga_ls8c_ard_3-2-1_093083_2022-12-13_final
2022-12-15 09:26:34	ga_ls8c_ard_3-2-1_091083_2022-12-14_final
2022-12-16 10:03:25	ga_ls8c_ard_3-2-1_098067_2022-12-16_final
2022-12-16 10:04:37	ga_ls8c_ard_3-2-1_098070_2022-12-16_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-22 09:28:15	ga_ls8c_ard_3-2-1_092072_2022-12-21_final
2022-12-22 11:08:19	ga_ls8c_ard_3-2-1_108075_2022-12-22_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2022-12-29 09:35:39	ga_ls8c_ard_3-2-1_093075_2022-12-29_final
2022-12-31 09:28:05	ga_ls8c_ard_3-2-1_091087_2022-12-30_final
2022-12-31 09:28:29	ga_ls8c_ard_3-2-1_091088_2022-12-30_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-09 09:22:17	ga_ls8c_ard_3-2-1_090088_2023-01-08_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-18 10:49:41	ga_ls8c_ard_3-2-1_105075_2023-01-18_final
2023-01-22 10:28:13	ga_ls8c_ard_3-2-1_101083_2023-01-22_final
2023-01-30 11:14:54	ga_ls8c_ard_3-2-1_109076_2023-01-30_final
2023-02-01 09:26:27	ga_ls8c_ard_3-2-1_091083_2023-01-31_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-10 10:55:31	ga_ls8c_ard_3-2-1_106074_2023-02-10_final
2023-02-14 10:30:21	ga_ls8c_ard_3-2-1_102073_2023-02-14_final
2023-02-15 11:17:59	ga_ls8c_ard_3-2-1_109084_2023-02-15_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-17 11:00:48	ga_ls8c_ard_3-2-1_107072_2023-02-17_final
2023-02-18 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-02-18_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-02-20 09:52:22	ga_ls8c_ard_3-2-1_096071_2023-02-20_final
2023-02-20 11:36:26	ga_ls8c_ard_3-2-1_112084_2023-02-20_final
2023-02-24 09:34:19	ga_ls8c_ard_3-2-1_092088_2023-02-24_final
2023-02-26 09:17:57	ga_ls8c_ard_3-2-1_090078_2023-02-25_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-17 11:25:14	ga_ls8c_ard_3-2-1_111072_2023-03-17_final
2023-03-21 10:59:39	ga_ls8c_ard_3-2-1_107070_2023-03-21_final
2023-03-26 09:40:27	ga_ls8c_ard_3-2-1_094073_2023-03-26_final
2023-03-27 10:25:42	ga_ls8c_ard_3-2-1_101078_2023-03-27_final
2023-03-30 09:20:29	ga_ls8c_ard_3-2-1_090085_2023-03-29_final
2023-03-30 10:55:47	ga_ls8c_ard_3-2-1_106076_2023-03-30_final
2023-03-31 09:57:45	ga_ls8c_ard_3-2-1_097070_2023-03-31_final
2023-03-31 09:58:33	ga_ls8c_ard_3-2-1_097072_2023-03-31_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-04-01 10:40:12	ga_ls8c_ard_3-2-1_104068_2023-04-01_final
2023-04-06 09:28:33	ga_ls8c_ard_3-2-1_091090_2023-04-05_final
2023-04-09 09:57:23	ga_ls8c_ard_3-2-1_096085_2023-04-09_final
2023-04-09 11:35:28	ga_ls8c_ard_3-2-1_112083_2023-04-09_final
2023-04-11 09:39:47	ga_ls8c_ard_3-2-1_094072_2023-04-11_final
2023-04-16 09:56:43	ga_ls8c_ard_3-2-1_097068_2023-04-16_final
2023-04-19 10:27:59	ga_ls8c_ard_3-2-1_102069_2023-04-19_final
2023-04-30 11:52:41	ga_ls8c_ard_3-2-1_115080_2023-04-30_final
2023-05-02 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-05-02_final
2023-05-03 10:41:53	ga_ls8c_ard_3-2-1_104073_2023-05-03_final
2023-05-11 09:56:41	ga_ls8c_ard_3-2-1_096084_2023-05-11_final
2023-05-13 09:45:30	ga_ls8c_ard_3-2-1_094087_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