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
2022-01-03 10:23:44	ga_ls8c_ard_3-2-1_101072_2022-01-03_final
2022-01-04 11:06:12	ga_ls8c_ard_3-2-1_108070_2022-01-04_final
2022-01-20 11:07:20	ga_ls8c_ard_3-2-1_108073_2022-01-20_final
2022-01-22 09:19:17	ga_ls8c_ard_3-2-1_090081_2022-01-21_final
2022-02-01 09:53:07	ga_ls8c_ard_3-2-1_096073_2022-02-01_final
2022-02-07 09:22:49	ga_ls8c_ard_3-2-1_090090_2022-02-06_final
2022-02-16 09:13:47	ga_ls8c_ard_3-2-1_089083_2022-02-15_final
2022-02-17 11:35:55	ga_ls8c_ard_3-2-1_112083_2022-02-17_final
2022-02-18 10:35:06	ga_ls8c_ard_3-2-1_103070_2022-02-18_final
2022-02-19 11:20:44	ga_ls8c_ard_3-2-1_110076_2022-02-19_final
2022-02-24 10:01:11	ga_ls8c_ard_3-2-1_097078_2022-02-24_final
2022-03-03 10:10:09	ga_ls8c_ard_3-2-1_098085_2022-03-03_final
2022-03-23 11:19:21	ga_ls8c_ard_3-2-1_110073_2022-03-23_final
2022-04-05 09:13:04	ga_ls8c_ard_3-2-1_089082_2022-04-04_final
2022-04-06 09:56:21	ga_ls8c_ard_3-2-1_096082_2022-04-06_final
2022-04-12 10:53:01	ga_ls8c_ard_3-2-1_106069_2022-04-12_final
2022-04-30 10:42:12	ga_ls8c_ard_3-2-1_104073_2022-04-30_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-04 10:20:43	ga_ls8c_ard_3-2-1_100081_2022-05-04_final
2022-05-10 11:20:36	ga_ls8c_ard_3-2-1_110076_2022-05-10_final
2022-05-12 11:05:51	ga_ls8c_ard_3-2-1_108070_2022-05-12_final
2022-05-15 10:01:53	ga_ls8c_ard_3-2-1_097080_2022-05-15_final
2022-05-23 10:46:09	ga_ls8c_ard_3-2-1_105067_2022-05-23_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_2022-05-24_final
2022-05-28 09:30:59	ga_ls8c_ard_3-2-1_092080_2022-05-28_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-15 10:53:46	ga_ls8c_ard_3-2-1_106070_2022-06-15_final
2022-06-23 11:47:39	ga_ls8c_ard_3-2-1_114081_2022-06-23_final
2022-07-08 11:00:24	ga_ls8c_ard_3-2-1_107071_2022-07-08_final
2022-07-11 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-07-11_final
2022-07-11 11:36:29	ga_ls8c_ard_3-2-1_112084_2022-07-11_final
2022-07-13 09:45:38	ga_ls8c_ard_3-2-1_094085_2022-07-13_final
2022-07-23 10:22:01	ga_ls8c_ard_3-2-1_100083_2022-07-23_final
2022-07-30 10:23:05	ga_ls8c_ard_3-2-1_101070_2022-07-30_final
2022-08-02 10:53:37	ga_ls8c_ard_3-2-1_106069_2022-08-02_final
2022-08-05 11:25:45	ga_ls8c_ard_3-2-1_111072_2022-08-05_final
2022-08-09 11:00:15	ga_ls8c_ard_3-2-1_107070_2022-08-09_final
2022-08-13 10:39:57	ga_ls8c_ard_3-2-1_103081_2022-08-13_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-19 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-08-19_final
2022-08-23 09:39:22	ga_ls8c_ard_3-2-1_093084_2022-08-23_final
2022-08-23 09:40:10	ga_ls8c_ard_3-2-1_093086_2022-08-23_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-08-24 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-08-24_final
2022-08-24 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-08-24_final
2022-08-27 10:47:33	ga_ls8c_ard_3-2-1_105069_2022-08-27_final
2022-08-30 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-08-30_final
2022-08-31 10:23:37	ga_ls8c_ard_3-2-1_101071_2022-08-31_final
2022-09-01 11:06:29	ga_ls8c_ard_3-2-1_108070_2022-09-01_final
2022-09-01 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-09-01_final
2022-09-07 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-09-07_final
2022-09-17 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-09-17_final
2022-09-17 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-09-17_final
2022-09-19 10:54:38	ga_ls8c_ard_3-2-1_106071_2022-09-19_final
2022-09-28 09:13:34	ga_ls8c_ard_3-2-1_089081_2022-09-27_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-13 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-10-13_final
2022-10-14 09:15:00	ga_ls8c_ard_3-2-1_089085_2022-10-13_final
2022-11-07 11:42:40	ga_ls8c_ard_3-2-1_113083_2022-11-07_final
2022-11-12 10:18:17	ga_ls8c_ard_3-2-1_100073_2022-11-12_final
2022-11-14 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-14_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-16 09:52:43	ga_ls8c_ard_3-2-1_096071_2022-11-16_final
2022-11-20 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-11-20_final
2022-11-21 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-11-21_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-30 10:09:54	ga_ls8c_ard_3-2-1_098083_2022-11-30_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-26 10:44:25	ga_ls8c_ard_3-2-1_104077_2022-12-26_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-06 10:24:18	ga_ls8c_ard_3-2-1_101073_2023-01-06_final
2023-01-07 11:10:44	ga_ls8c_ard_3-2-1_108081_2023-01-07_final
2023-01-10 11:42:25	ga_ls8c_ard_3-2-1_113083_2023-01-10_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-22 10:26:13	ga_ls8c_ard_3-2-1_101078_2023-01-22_final
2023-01-23 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-01-23_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-10 09:19:26	ga_ls8c_ard_3-2-1_090081_2023-02-09_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-11 09:59:53	ga_ls8c_ard_3-2-1_097074_2023-02-11_final
2023-02-17 09:25:07	ga_ls8c_ard_3-2-1_091080_2023-02-16_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-24 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-03-24_final
2023-03-27 10:25:42	ga_ls8c_ard_3-2-1_101078_2023-03-27_final
2023-04-13 09:34:12	ga_ls8c_ard_3-2-1_092089_2023-04-13_final
2023-04-24 09:10:50	ga_ls8c_ard_3-2-1_089077_2023-04-23_final
2023-04-29 11:06:38	ga_ls8c_ard_3-2-1_108073_2023-04-29_final
2023-05-03 09:06:59	ga_ls8c_ard_3-2-1_088083_2023-05-02_final
2023-05-12 10:33:33	ga_ls8c_ard_3-2-1_103068_2023-05-12_final
2023-05-13 09:40:19	ga_ls8c_ard_3-2-1_094074_2023-05-13_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-14 10:26:46	ga_ls8c_ard_3-2-1_101082_2023-05-14_final
2023-05-16 11:51:40	ga_ls8c_ard_3-2-1_115078_2023-05-16_final
2023-05-17 09:19:33	ga_ls8c_ard_3-2-1_090084_2023-05-16_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