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
2022-01-04 09:31:18	ga_ls8c_ard_3-2-1_092080_2022-01-04_final
2022-01-04 09:33:18	ga_ls8c_ard_3-2-1_092085_2022-01-04_final
2022-01-06 09:18:56	ga_ls8c_ard_3-2-1_090080_2022-01-05_final
2022-01-22 10:56:34	ga_ls8c_ard_3-2-1_106077_2022-01-22_final
2022-01-23 10:00:32	ga_ls8c_ard_3-2-1_097076_2022-01-23_final
2022-01-25 11:27:02	ga_ls8c_ard_3-2-1_111076_2022-01-25_final
2022-01-26 10:31:49	ga_ls8c_ard_3-2-1_102077_2022-01-26_final
2022-01-30 11:45:58	ga_ls8c_ard_3-2-1_114077_2022-01-30_final
2022-02-05 11:11:16	ga_ls8c_ard_3-2-1_108083_2022-02-05_final
2022-02-06 11:50:56	ga_ls8c_ard_3-2-1_115074_2022-02-06_final
2022-02-07 09:20:01	ga_ls8c_ard_3-2-1_090083_2022-02-06_final
2022-02-07 09:20:25	ga_ls8c_ard_3-2-1_090084_2022-02-06_final
2022-02-08 11:38:58	ga_ls8c_ard_3-2-1_113075_2022-02-08_final
2022-02-11 10:28:58	ga_ls8c_ard_3-2-1_102070_2022-02-11_final
2022-02-14 11:00:39	ga_ls8c_ard_3-2-1_107072_2022-02-14_final
2022-02-22 11:52:02	ga_ls8c_ard_3-2-1_115077_2022-02-22_final
2022-03-09 09:31:50	ga_ls8c_ard_3-2-1_092082_2022-03-09_final
2022-03-12 11:41:36	ga_ls8c_ard_3-2-1_113082_2022-03-12_final
2022-03-14 11:29:37	ga_ls8c_ard_3-2-1_111083_2022-03-14_final
2022-03-18 11:04:51	ga_ls8c_ard_3-2-1_107083_2022-03-18_final
2022-03-19 11:47:19	ga_ls8c_ard_3-2-1_114081_2022-03-19_final
2022-03-22 10:34:54	ga_ls8c_ard_3-2-1_103070_2022-03-22_final
2022-03-27 10:55:46	ga_ls8c_ard_3-2-1_106076_2022-03-27_final
2022-03-28 10:02:07	ga_ls8c_ard_3-2-1_097081_2022-03-28_final
2022-03-30 09:50:08	ga_ls8c_ard_3-2-1_095082_2022-03-30_final
2022-03-31 10:29:00	ga_ls8c_ard_3-2-1_102071_2022-03-31_final
2022-04-01 11:11:52	ga_ls8c_ard_3-2-1_109070_2022-04-01_final
2022-04-05 09:12:16	ga_ls8c_ard_3-2-1_089080_2022-04-04_final
2022-04-05 09:12:40	ga_ls8c_ard_3-2-1_089081_2022-04-04_final
2022-04-10 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-04-10_final
2022-04-18 10:19:56	ga_ls8c_ard_3-2-1_100079_2022-04-18_final
2022-04-24 09:44:01	ga_ls8c_ard_3-2-1_094082_2022-04-24_final
2022-04-29 10:01:19	ga_ls8c_ard_3-2-1_097079_2022-04-29_final
2022-05-02 10:30:16	ga_ls8c_ard_3-2-1_102074_2022-05-02_final
2022-05-12 11:10:39	ga_ls8c_ard_3-2-1_108082_2022-05-12_final
2022-05-14 10:54:42	ga_ls8c_ard_3-2-1_106073_2022-05-14_final
2022-06-02 09:46:49	ga_ls8c_ard_3-2-1_095073_2022-06-02_final
2022-06-08 09:13:00	ga_ls8c_ard_3-2-1_089081_2022-06-07_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-13 11:06:30	ga_ls8c_ard_3-2-1_108071_2022-06-13_final
2022-06-15 09:19:16	ga_ls8c_ard_3-2-1_090081_2022-06-14_final
2022-06-15 09:20:52	ga_ls8c_ard_3-2-1_090085_2022-06-14_final
2022-06-18 11:30:16	ga_ls8c_ard_3-2-1_111084_2022-06-18_final
2022-06-20 11:12:20	ga_ls8c_ard_3-2-1_109070_2022-06-20_final
2022-06-24 09:13:08	ga_ls8c_ard_3-2-1_089081_2022-06-23_final
2022-06-29 09:32:06	ga_ls8c_ard_3-2-1_092082_2022-06-29_final
2022-06-29 11:05:47	ga_ls8c_ard_3-2-1_108069_2022-06-29_final
2022-06-29 11:06:35	ga_ls8c_ard_3-2-1_108071_2022-06-29_final
2022-07-04 09:51:26	ga_ls8c_ard_3-2-1_095084_2022-07-04_final
2022-07-10 10:48:26	ga_ls8c_ard_3-2-1_105072_2022-07-10_final
2022-07-15 11:05:46	ga_ls8c_ard_3-2-1_108069_2022-07-15_final
2022-07-21 10:29:34	ga_ls8c_ard_3-2-1_102071_2022-07-21_final
2022-07-23 10:22:01	ga_ls8c_ard_3-2-1_100083_2022-07-23_final
2022-08-01 10:16:20	ga_ls8c_ard_3-2-1_099084_2022-08-01_final
2022-08-02 10:58:01	ga_ls8c_ard_3-2-1_106080_2022-08-02_final
2022-08-03 11:40:05	ga_ls8c_ard_3-2-1_113077_2022-08-03_final
2022-08-19 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-08-19_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-25 11:40:26	ga_ls8c_ard_3-2-1_113078_2022-12-25_final
2022-12-29 09:36:03	ga_ls8c_ard_3-2-1_093076_2022-12-29_final
2023-02-10 09:20:37	ga_ls8c_ard_3-2-1_090084_2023-02-09_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-03-22 10:06:48	ga_ls8c_ard_3-2-1_098077_2023-03-22_final
2023-03-28 11:07:22	ga_ls8c_ard_3-2-1_108074_2023-03-28_final
2023-04-16 09:58:42	ga_ls8c_ard_3-2-1_097073_2023-04-16_final
2023-04-19 10:28:47	ga_ls8c_ard_3-2-1_102071_2023-04-19_final
2023-04-24 10:48:07	ga_ls8c_ard_3-2-1_105073_2023-04-24_final
2023-05-05 10:30:17	ga_ls8c_ard_3-2-1_102075_2023-05-05_final
2023-05-06 11:11:56	ga_ls8c_ard_3-2-1_109071_2023-05-06_final
2023-05-08 09:24:15	ga_ls8c_ard_3-2-1_091080_2023-05-07_final
2023-05-10 09:11:03	ga_ls8c_ard_3-2-1_089078_2023-05-09_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_final
2023-05-10 09:13:27	ga_ls8c_ard_3-2-1_089084_2023-05-09_final
2023-05-11 11:35:10	ga_ls8c_ard_3-2-1_112083_2023-05-11_final
2023-05-18 09:57:37	ga_ls8c_ard_3-2-1_097071_2023-05-18_final
2023-05-21 10:28:33	ga_ls8c_ard_3-2-1_102071_2023-05-21_final
2023-05-24 09:24:11	ga_ls8c_ard_3-2-1_091080_2023-05-23_final
2023-05-24 09:24:35	ga_ls8c_ard_3-2-1_091081_2023-05-23_final
2023-05-26 09:11:49	ga_ls8c_ard_3-2-1_089080_2023-05-25_final
2023-05-26 10:51:54	ga_ls8c_ard_3-2-1_105083_2023-05-26_final
2023-06-07 11:14:18	ga_ls8c_ard_3-2-1_109077_2023-06-07_final
2023-06-22 10:28:20	ga_ls8c_ard_3-2-1_102070_2023-06-22_final
2023-06-26 10:04:04	ga_ls8c_ard_3-2-1_098071_2023-06-26_final
2023-06-27 09:11:16	ga_ls8c_ard_3-2-1_089078_2023-06-26_final
2023-06-29 10:39:01	ga_ls8c_ard_3-2-1_103081_2023-06-29_final
2023-07-07 11:28:57	ga_ls8c_ard_3-2-1_111082_2023-07-07_final
2023-07-12 10:07:50	ga_ls8c_ard_3-2-1_098080_2023-07-12_final
2023-07-13 09:14:13	ga_ls8c_ard_3-2-1_089085_2023-07-12_final
2023-07-14 11:34:46	ga_ls8c_ard_3-2-1_112081_2023-07-14_final
2023-07-16 09:44:43	ga_ls8c_ard_3-2-1_094084_2023-07-16_final
2023-07-18 09:30:45	ga_ls8c_ard_3-2-1_092080_2023-07-18_final
2023-08-01 11:18:33	ga_ls8c_ard_3-2-1_110071_2023-08-01_final
2023-08-05 10:53:51	ga_ls8c_ard_3-2-1_106071_2023-08-05_final
2023-08-13 10:04:50	ga_ls8c_ard_3-2-1_098072_2023-08-13_final
2023-08-26 09:35:14	ga_ls8c_ard_3-2-1_093075_2023-08-26_nrt
2023-08-29 10:04:57	ga_ls8c_ard_3-2-1_098072_2023-08-29_nrt
2023-08-30 10:48:36	ga_ls8c_ard_3-2-1_105073_2023-08-30_nrt
2023-09-04 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-09-04_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