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
2022-12-04 11:19:40	ga_ls8c_ard_3-2-1_110072_2022-12-04_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-09 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-12-09_final
2022-12-12 10:28:35	ga_ls8c_ard_3-2-1_102068_2022-12-12_final
2022-12-13 09:34:33	ga_ls8c_ard_3-2-1_093072_2022-12-13_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-22 11:09:55	ga_ls8c_ard_3-2-1_108079_2022-12-22_final
2022-12-31 09:28:29	ga_ls8c_ard_3-2-1_091088_2022-12-30_final
2023-01-05 09:41:02	ga_ls8c_ard_3-2-1_094073_2023-01-05_final
2023-01-08 10:15:07	ga_ls8c_ard_3-2-1_099081_2023-01-08_final
2023-01-09 09:21:05	ga_ls8c_ard_3-2-1_090085_2023-01-08_final
2023-01-09 09:22:17	ga_ls8c_ard_3-2-1_090088_2023-01-08_final
2023-01-11 10:44:00	ga_ls8c_ard_3-2-1_104076_2023-01-11_final
2023-01-20 10:36:09	ga_ls8c_ard_3-2-1_103072_2023-01-20_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-01-23 09:29:48	ga_ls8c_ard_3-2-1_092076_2023-01-22_final
2023-01-24 11:51:58	ga_ls8c_ard_3-2-1_115076_2023-01-24_final
2023-01-25 10:55:09	ga_ls8c_ard_3-2-1_106073_2023-01-25_final
2023-01-25 10:55:57	ga_ls8c_ard_3-2-1_106075_2023-01-25_final
2023-02-01 11:02:33	ga_ls8c_ard_3-2-1_107076_2023-02-01_final
2023-02-09 10:16:15	ga_ls8c_ard_3-2-1_099084_2023-02-09_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-13 09:47:05	ga_ls8c_ard_3-2-1_095073_2023-02-13_final
2023-02-15 11:12:24	ga_ls8c_ard_3-2-1_109070_2023-02-15_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-12 09:29:50	ga_ls8c_ard_3-2-1_092077_2023-03-11_final
2023-03-17 09:46:21	ga_ls8c_ard_3-2-1_095072_2023-03-17_final
2023-03-18 10:29:12	ga_ls8c_ard_3-2-1_102071_2023-03-18_final
2023-03-24 09:52:25	ga_ls8c_ard_3-2-1_096072_2023-03-24_final
2023-03-26 11:18:56	ga_ls8c_ard_3-2-1_110072_2023-03-26_final
2023-03-31 09:58:09	ga_ls8c_ard_3-2-1_097071_2023-03-31_final
2023-04-06 11:05:02	ga_ls8c_ard_3-2-1_107084_2023-04-06_final
2023-04-08 09:14:09	ga_ls8c_ard_3-2-1_089085_2023-04-07_final
2023-04-16 09:57:31	ga_ls8c_ard_3-2-1_097070_2023-04-16_final
2023-04-18 09:51:31	ga_ls8c_ard_3-2-1_095086_2023-04-18_final
2023-04-18 11:24:49	ga_ls8c_ard_3-2-1_111072_2023-04-18_final
2023-04-25 11:31:47	ga_ls8c_ard_3-2-1_112074_2023-04-25_final
2023-04-27 11:18:37	ga_ls8c_ard_3-2-1_110072_2023-04-27_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-04-29 09:32:57	ga_ls8c_ard_3-2-1_092086_2023-04-29_final
2023-05-06 11:11:32	ga_ls8c_ard_3-2-1_109070_2023-05-06_final
2023-05-09 10:08:41	ga_ls8c_ard_3-2-1_098083_2023-05-09_final
2023-05-13 11:19:12	ga_ls8c_ard_3-2-1_110074_2023-05-13_final
2023-05-15 11:09:13	ga_ls8c_ard_3-2-1_108080_2023-05-15_final
2023-05-19 09:05:36	ga_ls8c_ard_3-2-1_088080_2023-05-18_final
2023-05-25 10:06:15	ga_ls8c_ard_3-2-1_098077_2023-05-25_final
2023-05-27 09:57:05	ga_ls8c_ard_3-2-1_096085_2023-05-27_final
2023-05-29 09:45:07	ga_ls8c_ard_3-2-1_094086_2023-05-29_final
2023-06-01 11:51:43	ga_ls8c_ard_3-2-1_115078_2023-06-01_final
2023-06-14 11:22:57	ga_ls8c_ard_3-2-1_110083_2023-06-14_final
2023-06-23 09:33:31	ga_ls8c_ard_3-2-1_093072_2023-06-23_final
2023-06-29 10:35:25	ga_ls8c_ard_3-2-1_103072_2023-06-29_final
2023-07-01 10:27:29	ga_ls8c_ard_3-2-1_101083_2023-07-01_final
2023-07-08 10:29:44	ga_ls8c_ard_3-2-1_102073_2023-07-08_final
2023-07-12 10:03:03	ga_ls8c_ard_3-2-1_098068_2023-07-12_final
2023-07-13 09:13:25	ga_ls8c_ard_3-2-1_089083_2023-07-12_final
2023-07-13 10:51:54	ga_ls8c_ard_3-2-1_105082_2023-07-13_final
2023-07-17 10:27:11	ga_ls8c_ard_3-2-1_101082_2023-07-17_final
2023-07-18 09:33:33	ga_ls8c_ard_3-2-1_092087_2023-07-18_final
2023-07-22 10:42:09	ga_ls8c_ard_3-2-1_104073_2023-07-22_final
2023-07-24 10:29:49	ga_ls8c_ard_3-2-1_102073_2023-07-24_final
2023-07-27 09:27:52	ga_ls8c_ard_3-2-1_091088_2023-07-26_final
2023-07-31 10:35:41	ga_ls8c_ard_3-2-1_103072_2023-07-31_final
2023-08-04 10:09:23	ga_ls8c_ard_3-2-1_099068_2023-08-04_final
2023-08-05 10:55:50	ga_ls8c_ard_3-2-1_106076_2023-08-05_final
2023-08-08 11:25:33	ga_ls8c_ard_3-2-1_111073_2023-08-08_final
2023-08-10 11:17:34	ga_ls8c_ard_3-2-1_109084_2023-08-10_final
2023-08-12 11:02:02	ga_ls8c_ard_3-2-1_107076_2023-08-12_final
2023-08-13 11:47:18	ga_ls8c_ard_3-2-1_114081_2023-08-13_final
2023-08-14 10:49:18	ga_ls8c_ard_3-2-1_105075_2023-08-14_final
2023-08-16 10:39:22	ga_ls8c_ard_3-2-1_103081_2023-08-16_final
2023-08-19 11:07:30	ga_ls8c_ard_3-2-1_108074_2023-08-19_final
2023-08-25 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-08-25_final
2023-08-29 10:03:21	ga_ls8c_ard_3-2-1_098068_2023-08-29_final
2023-09-04 11:05:56	ga_ls8c_ard_3-2-1_108070_2023-09-04_final
2023-09-06 09:21:03	ga_ls8c_ard_3-2-1_090086_2023-09-05_final
2023-09-09 09:46:24	ga_ls8c_ard_3-2-1_095072_2023-09-09_final
2023-09-14 11:47:04	ga_ls8c_ard_3-2-1_114080_2023-09-14_final
2023-09-16 11:36:19	ga_ls8c_ard_3-2-1_112084_2023-09-16_final
2023-09-18 11:19:58	ga_ls8c_ard_3-2-1_110074_2023-09-18_final
2023-09-28 10:17:25	ga_ls8c_ard_3-2-1_100072_2023-09-28_final
2023-09-30 10:03:28	ga_ls8c_ard_3-2-1_098068_2023-09-30_final
2023-10-02 11:32:23	ga_ls8c_ard_3-2-1_112074_2023-10-02_final
2023-10-06 11:06:27	ga_ls8c_ard_3-2-1_108071_2023-10-06_final
2023-10-08 09:22:49	ga_ls8c_ard_3-2-1_090090_2023-10-07_final
2023-10-09 10:01:42	ga_ls8c_ard_3-2-1_097079_2023-10-09_final
2023-10-15 10:59:56	ga_ls8c_ard_3-2-1_107070_2023-10-15_final
2023-10-15 11:05:07	ga_ls8c_ard_3-2-1_107083_2023-10-15_final
2023-10-17 09:11:52	ga_ls8c_ard_3-2-1_089078_2023-10-16_final
2023-10-24 10:56:10	ga_ls8c_ard_3-2-1_106076_2023-10-24_final
2023-10-30 10:17:07	ga_ls8c_ard_3-2-1_100071_2023-10-30_final
2023-10-30 10:17:31	ga_ls8c_ard_3-2-1_100072_2023-10-30_final
2023-10-30 10:21:55	ga_ls8c_ard_3-2-1_100083_2023-10-30_final
2023-10-31 09:26:41	ga_ls8c_ard_3-2-1_091084_2023-10-30_final
2023-10-31 09:28:41	ga_ls8c_ard_3-2-1_091089_2023-10-30_final
2023-11-05 11:19:18	ga_ls8c_ard_3-2-1_110072_2023-11-05_final
2023-11-05 11:20:06	ga_ls8c_ard_3-2-1_110074_2023-11-05_final
2023-11-09 09:22:25	ga_ls8c_ard_3-2-1_090089_2023-11-08_final
2023-11-09 10:53:43	ga_ls8c_ard_3-2-1_106070_2023-11-09_final
2023-11-14 09:35:25	ga_ls8c_ard_3-2-1_093075_2023-11-14_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