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
2022-03-01 10:22:07	ga_ls8c_ard_3-2-1_100084_2022-03-01_final
2022-03-04 10:47:01	ga_ls8c_ard_3-2-1_105069_2022-03-04_final
2022-03-04 10:49:01	ga_ls8c_ard_3-2-1_105074_2022-03-04_final
2022-03-20 10:46:29	ga_ls8c_ard_3-2-1_105068_2022-03-20_final
2022-04-09 10:22:53	ga_ls8c_ard_3-2-1_101071_2022-04-09_final
2022-04-14 09:06:58	ga_ls8c_ard_3-2-1_088082_2022-04-13_final
2022-04-27 11:50:58	ga_ls8c_ard_3-2-1_115075_2022-04-27_final
2022-04-29 10:02:54	ga_ls8c_ard_3-2-1_097083_2022-04-29_final
2022-05-13 10:09:27	ga_ls8c_ard_3-2-1_099068_2022-05-13_final
2022-05-17 11:23:38	ga_ls8c_ard_3-2-1_111068_2022-05-17_final
2022-05-21 09:27:37	ga_ls8c_ard_3-2-1_091087_2022-05-20_final
2022-05-21 09:28:01	ga_ls8c_ard_3-2-1_091088_2022-05-20_final
2022-05-21 10:59:43	ga_ls8c_ard_3-2-1_107070_2022-05-21_final
2022-05-22 11:44:34	ga_ls8c_ard_3-2-1_114074_2022-05-22_final
2022-05-25 10:34:11	ga_ls8c_ard_3-2-1_103068_2022-05-25_final
2022-05-28 09:34:58	ga_ls8c_ard_3-2-1_092090_2022-05-28_final
2022-06-05 11:58:14	ga_ls8c_ard_3-2-1_116077_2022-06-05_final
2022-07-04 09:52:38	ga_ls8c_ard_3-2-1_095087_2022-07-04_final
2022-07-09 10:07:35	ga_ls8c_ard_3-2-1_098078_2022-07-09_final
2022-07-20 11:24:22	ga_ls8c_ard_3-2-1_111069_2022-07-20_final
2022-07-24 11:04:30	ga_ls8c_ard_3-2-1_107081_2022-07-24_final
2022-08-05 09:52:27	ga_ls8c_ard_3-2-1_095086_2022-08-05_final
2022-08-06 10:28:32	ga_ls8c_ard_3-2-1_102068_2022-08-06_final
2022-08-17 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-08-17_final
2022-09-02 10:09:39	ga_ls8c_ard_3-2-1_099067_2022-09-02_final
2022-09-02 10:10:03	ga_ls8c_ard_3-2-1_099068_2022-09-02_final
2022-09-15 11:23:20	ga_ls8c_ard_3-2-1_110081_2022-09-15_final
2022-09-20 11:38:18	ga_ls8c_ard_3-2-1_113072_2022-09-20_final
2022-10-07 09:07:43	ga_ls8c_ard_3-2-1_088082_2022-10-06_final
2022-10-14 10:48:18	ga_ls8c_ard_3-2-1_105071_2022-10-14_final
2022-10-16 10:39:58	ga_ls8c_ard_3-2-1_103081_2022-10-16_final
2022-10-17 09:40:45	ga_ls8c_ard_3-2-1_094072_2022-10-17_final
2022-10-18 10:24:02	ga_ls8c_ard_3-2-1_101072_2022-10-18_final
2022-10-18 10:24:26	ga_ls8c_ard_3-2-1_101073_2022-10-18_final
2022-10-28 09:22:43	ga_ls8c_ard_3-2-1_091073_2022-10-27_final
2022-11-04 09:33:18	ga_ls8c_ard_3-2-1_092084_2022-11-04_final
2022-11-05 10:09:22	ga_ls8c_ard_3-2-1_099066_2022-11-05_final
2022-11-08 10:45:03	ga_ls8c_ard_3-2-1_104078_2022-11-08_final
2022-11-13 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-12_final
2022-11-18 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-11-18_final
2022-11-20 09:33:11	ga_ls8c_ard_3-2-1_092084_2022-11-20_final
2022-11-20 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-11-20_final
2022-11-25 11:26:38	ga_ls8c_ard_3-2-1_111074_2022-11-25_final
2022-11-27 11:14:17	ga_ls8c_ard_3-2-1_109074_2022-11-27_final
2022-11-29 09:27:26	ga_ls8c_ard_3-2-1_091085_2022-11-28_final
2022-12-15 09:27:21	ga_ls8c_ard_3-2-1_091085_2022-12-14_final
2022-12-15 11:00:15	ga_ls8c_ard_3-2-1_107070_2022-12-15_final
2022-12-17 09:12:11	ga_ls8c_ard_3-2-1_089078_2022-12-16_final
2022-12-28 10:29:16	ga_ls8c_ard_3-2-1_102070_2022-12-28_final
2022-12-29 09:40:50	ga_ls8c_ard_3-2-1_093088_2022-12-29_final
2023-01-09 10:53:11	ga_ls8c_ard_3-2-1_106068_2023-01-09_final
2023-01-15 10:22:25	ga_ls8c_ard_3-2-1_100084_2023-01-15_final
2023-01-18 09:14:47	ga_ls8c_ard_3-2-1_089085_2023-01-17_final
2023-02-01 11:00:33	ga_ls8c_ard_3-2-1_107071_2023-02-01_final
2023-02-04 11:32:39	ga_ls8c_ard_3-2-1_112074_2023-02-04_final
2023-02-18 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-02-18_final
2023-03-05 09:22:31	ga_ls8c_ard_3-2-1_091074_2023-03-04_final
2023-03-08 09:52:58	ga_ls8c_ard_3-2-1_096073_2023-03-08_final
2023-03-20 10:19:36	ga_ls8c_ard_3-2-1_100078_2023-03-20_final
2023-03-22 11:44:29	ga_ls8c_ard_3-2-1_114074_2023-03-22_final
2023-03-23 09:12:22	ga_ls8c_ard_3-2-1_089080_2023-03-22_final
2023-03-25 10:35:41	ga_ls8c_ard_3-2-1_103072_2023-03-25_final
2023-03-30 09:17:18	ga_ls8c_ard_3-2-1_090077_2023-03-29_final
2023-04-07 10:07:00	ga_ls8c_ard_3-2-1_098078_2023-04-07_final
2023-04-15 10:54:20	ga_ls8c_ard_3-2-1_106073_2023-04-15_final
2023-04-16 09:57:07	ga_ls8c_ard_3-2-1_097069_2023-04-16_final
2023-05-04 09:45:27	ga_ls8c_ard_3-2-1_095071_2023-05-04_final
2023-05-04 11:23:08	ga_ls8c_ard_3-2-1_111068_2023-05-04_final
2023-05-07 10:16:18	ga_ls8c_ard_3-2-1_100071_2023-05-07_final
2023-05-17 09:15:57	ga_ls8c_ard_3-2-1_090075_2023-05-16_final
2023-06-02 10:58:05	ga_ls8c_ard_3-2-1_106083_2023-06-02_final
2023-06-22 10:27:56	ga_ls8c_ard_3-2-1_102069_2023-06-22_final
2023-06-30 09:39:25	ga_ls8c_ard_3-2-1_094071_2023-06-30_final
2023-07-02 09:32:40	ga_ls8c_ard_3-2-1_092085_2023-07-02_final
2023-07-25 11:13:29	ga_ls8c_ard_3-2-1_109074_2023-07-25_final
2023-08-01 11:23:44	ga_ls8c_ard_3-2-1_110084_2023-08-01_final
2023-08-12 11:02:02	ga_ls8c_ard_3-2-1_107076_2023-08-12_final
2023-08-16 10:35:46	ga_ls8c_ard_3-2-1_103072_2023-08-16_final
2023-08-17 11:18:39	ga_ls8c_ard_3-2-1_110071_2023-08-17_final
2023-08-19 09:34:13	ga_ls8c_ard_3-2-1_092088_2023-08-19_final
2023-09-13 09:21:43	ga_ls8c_ard_3-2-1_091072_2023-09-12_final
2023-09-18 11:18:23	ga_ls8c_ard_3-2-1_110070_2023-09-18_final
2023-09-29 09:22:12	ga_ls8c_ard_3-2-1_091073_2023-09-28_final
2023-10-03 10:34:22	ga_ls8c_ard_3-2-1_103068_2023-10-03_final
2023-10-19 10:35:59	ga_ls8c_ard_3-2-1_103072_2023-10-19_final
2023-10-25 09:58:10	ga_ls8c_ard_3-2-1_097070_2023-10-25_final
2023-10-27 11:23:54	ga_ls8c_ard_3-2-1_111068_2023-10-27_final
2023-11-03 11:31:41	ga_ls8c_ard_3-2-1_112072_2023-11-03_final
2023-11-12 11:23:51	ga_ls8c_ard_3-2-1_111068_2023-11-12_final
2023-11-21 11:18:09	ga_ls8c_ard_3-2-1_110069_2023-11-21_final
2023-12-09 09:29:10	ga_ls8c_ard_3-2-1_092075_2023-12-08_final
2023-12-15 10:30:15	ga_ls8c_ard_3-2-1_102073_2023-12-15_final
2023-12-30 09:52:09	ga_ls8c_ard_3-2-1_095086_2023-12-30_final
2024-01-26 09:29:04	ga_ls8c_ard_3-2-1_092075_2024-01-25_final
2024-01-29 11:38:28	ga_ls8c_ard_3-2-1_113074_2024-01-29_final
2024-01-31 09:46:03	ga_ls8c_ard_3-2-1_095071_2024-01-31_final
2024-02-09 09:46:19	ga_ls8c_ard_3-2-1_094087_2024-02-09_final
2024-02-11 09:29:10	ga_ls8c_ard_3-2-1_092075_2024-02-10_final
2024-02-15 10:41:42	ga_ls8c_ard_3-2-1_104071_2024-02-15_final
2024-02-18 09:35:18	ga_ls8c_ard_3-2-1_093075_2024-02-18_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