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
2023-02-02 11:45:24	ga_ls8c_ard_3-2-1_114075_2023-02-02_final
2023-02-03 09:15:17	ga_ls8c_ard_3-2-1_089086_2023-02-02_final
2023-03-21 09:28:21	ga_ls8c_ard_3-2-1_091089_2023-03-20_final
2023-03-22 10:06:48	ga_ls8c_ard_3-2-1_098077_2023-03-22_final
2023-07-13 09:13:01	ga_ls8c_ard_3-2-1_089082_2023-07-12_final
2023-07-16 09:45:07	ga_ls8c_ard_3-2-1_094085_2023-07-16_final
2023-07-20 09:19:59	ga_ls8c_ard_3-2-1_090084_2023-07-19_final
2023-07-20 09:20:23	ga_ls8c_ard_3-2-1_090085_2023-07-19_final
2023-07-20 10:53:17	ga_ls8c_ard_3-2-1_106070_2023-07-20_final
2023-07-23 09:51:20	ga_ls8c_ard_3-2-1_095085_2023-07-23_final
2023-07-27 11:01:33	ga_ls8c_ard_3-2-1_107075_2023-07-27_final
2023-07-28 10:04:45	ga_ls8c_ard_3-2-1_098072_2023-07-28_final
2023-07-28 11:46:50	ga_ls8c_ard_3-2-1_114080_2023-07-28_final
2023-07-29 09:14:43	ga_ls8c_ard_3-2-1_089086_2023-07-28_final
2023-08-02 10:27:43	ga_ls8c_ard_3-2-1_101083_2023-08-02_final
2023-08-03 11:05:24	ga_ls8c_ard_3-2-1_108069_2023-08-03_final
2023-08-05 09:18:09	ga_ls8c_ard_3-2-1_090079_2023-08-04_final
2023-08-10 09:34:42	ga_ls8c_ard_3-2-1_093074_2023-08-10_final
2023-08-10 11:11:59	ga_ls8c_ard_3-2-1_109070_2023-08-10_final
2023-08-10 11:15:58	ga_ls8c_ard_3-2-1_109080_2023-08-10_final
2023-08-10 11:17:34	ga_ls8c_ard_3-2-1_109084_2023-08-10_final
2023-08-11 10:21:33	ga_ls8c_ard_3-2-1_100083_2023-08-11_final
2023-08-13 11:45:43	ga_ls8c_ard_3-2-1_114077_2023-08-13_final
2023-08-13 11:46:54	ga_ls8c_ard_3-2-1_114080_2023-08-13_final
2023-08-14 09:12:49	ga_ls8c_ard_3-2-1_089081_2023-08-13_final
2023-08-14 10:49:42	ga_ls8c_ard_3-2-1_105076_2023-08-14_final
2023-08-15 09:57:17	ga_ls8c_ard_3-2-1_096084_2023-08-15_final
2023-08-15 09:58:05	ga_ls8c_ard_3-2-1_096086_2023-08-15_final
2023-08-17 09:45:45	ga_ls8c_ard_3-2-1_094086_2023-08-17_final
2023-08-17 09:46:09	ga_ls8c_ard_3-2-1_094087_2023-08-17_final
2023-08-19 11:11:30	ga_ls8c_ard_3-2-1_108084_2023-08-19_final
2023-08-26 11:12:08	ga_ls8c_ard_3-2-1_109070_2023-08-26_final
2023-08-26 11:14:07	ga_ls8c_ard_3-2-1_109075_2023-08-26_final
2023-08-29 10:09:44	ga_ls8c_ard_3-2-1_098084_2023-08-29_final
2023-08-30 09:12:55	ga_ls8c_ard_3-2-1_089081_2023-08-29_final
2023-08-30 09:14:55	ga_ls8c_ard_3-2-1_089086_2023-08-29_final
2023-08-30 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-08-30_final
2023-08-31 09:52:11	ga_ls8c_ard_3-2-1_096071_2023-08-31_final
2023-09-04 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-09-04_final
2023-09-05 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-09-05_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-09-05_final
2023-09-09 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-09-09_final
2023-09-11 11:14:09	ga_ls8c_ard_3-2-1_109075_2023-09-11_final
2023-09-13 09:23:19	ga_ls8c_ard_3-2-1_091076_2023-09-12_final
2023-09-13 09:27:19	ga_ls8c_ard_3-2-1_091086_2023-09-12_final
2023-09-22 10:54:27	ga_ls8c_ard_3-2-1_106072_2023-09-22_final
2023-09-22 10:55:15	ga_ls8c_ard_3-2-1_106074_2023-09-22_final
2023-09-27 09:39:44	ga_ls8c_ard_3-2-1_093086_2023-09-27_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-09-29 09:28:35	ga_ls8c_ard_3-2-1_091089_2023-09-28_final
2023-09-30 10:07:52	ga_ls8c_ard_3-2-1_098079_2023-09-30_final
2023-10-04 11:20:01	ga_ls8c_ard_3-2-1_110074_2023-10-04_final
2023-10-04 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-10-04_final
2023-10-06 09:34:45	ga_ls8c_ard_3-2-1_092089_2023-10-06_final
2023-10-08 09:20:50	ga_ls8c_ard_3-2-1_090085_2023-10-07_final
2023-10-08 10:55:43	ga_ls8c_ard_3-2-1_106075_2023-10-08_final
2023-10-09 09:58:31	ga_ls8c_ard_3-2-1_097071_2023-10-09_final
2023-10-13 11:13:54	ga_ls8c_ard_3-2-1_109074_2023-10-13_final
2023-10-14 10:17:04	ga_ls8c_ard_3-2-1_100071_2023-10-14_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_final
2023-10-16 11:45:59	ga_ls8c_ard_3-2-1_114077_2023-10-16_final
2023-10-16 11:46:23	ga_ls8c_ard_3-2-1_114078_2023-10-16_final
2023-10-17 10:49:10	ga_ls8c_ard_3-2-1_105074_2023-10-17_final
2023-10-19 10:34:23	ga_ls8c_ard_3-2-1_103068_2023-10-19_final
2023-10-20 09:40:45	ga_ls8c_ard_3-2-1_094073_2023-10-20_final
2023-10-22 11:06:31	ga_ls8c_ard_3-2-1_108071_2023-10-22_final
2023-10-23 10:11:42	ga_ls8c_ard_3-2-1_099073_2023-10-23_final
2023-10-23 10:12:54	ga_ls8c_ard_3-2-1_099076_2023-10-23_final
2023-10-23 10:14:29	ga_ls8c_ard_3-2-1_099080_2023-10-23_final
2023-10-23 11:51:23	ga_ls8c_ard_3-2-1_115075_2023-10-23_final
2023-10-24 09:17:41	ga_ls8c_ard_3-2-1_090077_2023-10-23_final
2023-10-24 09:20:52	ga_ls8c_ard_3-2-1_090085_2023-10-23_final
2023-10-24 10:58:34	ga_ls8c_ard_3-2-1_106082_2023-10-24_final
2023-10-25 09:58:33	ga_ls8c_ard_3-2-1_097071_2023-10-25_final
2023-10-27 09:46:13	ga_ls8c_ard_3-2-1_095071_2023-10-27_final
2023-10-27 09:47:01	ga_ls8c_ard_3-2-1_095073_2023-10-27_final
2023-10-29 09:33:52	ga_ls8c_ard_3-2-1_093071_2023-10-29_final
2023-10-29 09:38:39	ga_ls8c_ard_3-2-1_093083_2023-10-29_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-10-30 10:17:07	ga_ls8c_ard_3-2-1_100071_2023-10-30_final
2023-10-31 09:25:06	ga_ls8c_ard_3-2-1_091080_2023-10-30_final
2023-10-31 09:27:05	ga_ls8c_ard_3-2-1_091085_2023-10-30_final
2023-10-31 11:02:23	ga_ls8c_ard_3-2-1_107076_2023-10-31_final
2023-11-01 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-01_final
2023-11-01 10:05:10	ga_ls8c_ard_3-2-1_098072_2023-11-01_final
2023-11-01 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-11-01_final
2023-11-01 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-01_final
2023-11-05 09:41:13	ga_ls8c_ard_3-2-1_094074_2023-11-05_final
2023-11-05 11:21:18	ga_ls8c_ard_3-2-1_110077_2023-11-05_final
2023-11-05 11:24:29	ga_ls8c_ard_3-2-1_110085_2023-11-05_final
2023-11-07 09:29:14	ga_ls8c_ard_3-2-1_092075_2023-11-06_final
2023-11-07 11:06:07	ga_ls8c_ard_3-2-1_108070_2023-11-07_final
2023-11-10 09:58:29	ga_ls8c_ard_3-2-1_097071_2023-11-10_final
2023-11-10 09:59:41	ga_ls8c_ard_3-2-1_097074_2023-11-10_final
2023-11-11 10:40:58	ga_ls8c_ard_3-2-1_104069_2023-11-11_final
2023-11-12 09:47:21	ga_ls8c_ard_3-2-1_095074_2023-11-12_final
2023-11-12 11:25:26	ga_ls8c_ard_3-2-1_111072_2023-11-12_final
2023-11-17 10:06:45	ga_ls8c_ard_3-2-1_098076_2023-11-17_final
2023-11-17 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-11-17_final
2023-11-17 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-17_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