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
2022-03-04 09:10:32	ga_ls8c_ard_3-2-1_089075_2022-03-03_final
2022-03-04 09:14:31	ga_ls8c_ard_3-2-1_089085_2022-03-03_final
2022-03-04 09:14:55	ga_ls8c_ard_3-2-1_089086_2022-03-03_final
2022-03-04 10:49:01	ga_ls8c_ard_3-2-1_105074_2022-03-04_final
2022-03-04 10:49:49	ga_ls8c_ard_3-2-1_105076_2022-03-04_final
2022-03-04 10:51:48	ga_ls8c_ard_3-2-1_105081_2022-03-04_final
2022-03-04 10:52:36	ga_ls8c_ard_3-2-1_105083_2022-03-04_final
2022-03-05 09:52:11	ga_ls8c_ard_3-2-1_096071_2022-03-05_final
2022-03-05 09:54:11	ga_ls8c_ard_3-2-1_096076_2022-03-05_final
2022-03-05 09:54:35	ga_ls8c_ard_3-2-1_096077_2022-03-05_final
2022-03-05 09:54:59	ga_ls8c_ard_3-2-1_096078_2022-03-05_final
2022-03-05 09:56:35	ga_ls8c_ard_3-2-1_096082_2022-03-05_final
2022-03-05 09:58:11	ga_ls8c_ard_3-2-1_096086_2022-03-05_final
2022-03-05 11:31:52	ga_ls8c_ard_3-2-1_112073_2022-03-05_final
2022-03-05 11:32:16	ga_ls8c_ard_3-2-1_112074_2022-03-05_final
2022-03-05 11:33:28	ga_ls8c_ard_3-2-1_112077_2022-03-05_final
2022-03-05 11:34:16	ga_ls8c_ard_3-2-1_112079_2022-03-05_final
2022-03-05 11:35:52	ga_ls8c_ard_3-2-1_112083_2022-03-05_final
2022-03-05 11:36:16	ga_ls8c_ard_3-2-1_112084_2022-03-05_final
2022-03-06 10:37:03	ga_ls8c_ard_3-2-1_103075_2022-03-06_final
2022-03-07 11:18:42	ga_ls8c_ard_3-2-1_110071_2022-03-07_final
2022-03-07 11:21:54	ga_ls8c_ard_3-2-1_110079_2022-03-07_final
2022-03-07 11:22:42	ga_ls8c_ard_3-2-1_110081_2022-03-07_final
2022-03-07 11:23:30	ga_ls8c_ard_3-2-1_110083_2022-03-07_final
2022-03-08 10:23:05	ga_ls8c_ard_3-2-1_101071_2022-03-08_final
2022-03-08 10:24:40	ga_ls8c_ard_3-2-1_101075_2022-03-08_final
2022-03-08 10:27:04	ga_ls8c_ard_3-2-1_101081_2022-03-08_final
2022-03-08 10:27:28	ga_ls8c_ard_3-2-1_101082_2022-03-08_final
2022-03-09 09:34:14	ga_ls8c_ard_3-2-1_092088_2022-03-09_final
2022-03-09 11:06:20	ga_ls8c_ard_3-2-1_108071_2022-03-09_final
2022-03-09 11:06:44	ga_ls8c_ard_3-2-1_108072_2022-03-09_final
2022-03-09 11:09:07	ga_ls8c_ard_3-2-1_108078_2022-03-09_final
2022-03-09 11:10:43	ga_ls8c_ard_3-2-1_108082_2022-03-09_final
2022-03-10 10:09:06	ga_ls8c_ard_3-2-1_099067_2022-03-10_final
2022-03-10 10:16:17	ga_ls8c_ard_3-2-1_099085_2022-03-10_final
2022-03-10 11:52:47	ga_ls8c_ard_3-2-1_115079_2022-03-10_final
2022-03-10 11:53:11	ga_ls8c_ard_3-2-1_115080_2022-03-10_final
2022-03-11 09:17:04	ga_ls8c_ard_3-2-1_090076_2022-03-10_final
2022-03-11 09:17:52	ga_ls8c_ard_3-2-1_090078_2022-03-10_final
2022-03-11 09:19:28	ga_ls8c_ard_3-2-1_090082_2022-03-10_final
2022-03-11 09:20:40	ga_ls8c_ard_3-2-1_090085_2022-03-10_final
2022-03-11 09:21:52	ga_ls8c_ard_3-2-1_090088_2022-03-10_final
2022-03-11 10:52:46	ga_ls8c_ard_3-2-1_106068_2022-03-11_final
2022-03-11 10:55:09	ga_ls8c_ard_3-2-1_106074_2022-03-11_final
2022-03-11 10:55:33	ga_ls8c_ard_3-2-1_106075_2022-03-11_final
2022-03-11 10:56:45	ga_ls8c_ard_3-2-1_106078_2022-03-11_final
2022-03-11 10:58:21	ga_ls8c_ard_3-2-1_106082_2022-03-11_final
2022-03-12 09:57:08	ga_ls8c_ard_3-2-1_097068_2022-03-12_final
2022-03-12 11:38:01	ga_ls8c_ard_3-2-1_113073_2022-03-12_final
2022-03-12 11:38:25	ga_ls8c_ard_3-2-1_113074_2022-03-12_final
2022-03-12 11:39:36	ga_ls8c_ard_3-2-1_113077_2022-03-12_final
2022-03-12 11:40:48	ga_ls8c_ard_3-2-1_113080_2022-03-12_final
2022-03-12 11:42:00	ga_ls8c_ard_3-2-1_113083_2022-03-12_final
2022-03-14 09:46:45	ga_ls8c_ard_3-2-1_095073_2022-03-14_final
2022-03-14 09:47:09	ga_ls8c_ard_3-2-1_095074_2022-03-14_final
2022-03-14 09:48:21	ga_ls8c_ard_3-2-1_095077_2022-03-14_final
2022-03-14 09:49:09	ga_ls8c_ard_3-2-1_095079_2022-03-14_final
2022-03-14 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-03-14_final
2022-03-14 11:24:02	ga_ls8c_ard_3-2-1_111069_2022-03-14_final
2022-03-14 11:27:38	ga_ls8c_ard_3-2-1_111078_2022-03-14_final
2022-03-14 11:29:13	ga_ls8c_ard_3-2-1_111082_2022-03-14_final
2022-03-15 10:28:24	ga_ls8c_ard_3-2-1_102069_2022-03-15_final
2022-03-15 10:28:48	ga_ls8c_ard_3-2-1_102070_2022-03-15_final
2022-03-15 10:30:00	ga_ls8c_ard_3-2-1_102073_2022-03-15_final
2022-03-15 10:30:24	ga_ls8c_ard_3-2-1_102074_2022-03-15_final
2022-03-15 10:31:12	ga_ls8c_ard_3-2-1_102076_2022-03-15_final
2022-03-15 10:32:48	ga_ls8c_ard_3-2-1_102080_2022-03-15_final
2022-03-15 10:33:11	ga_ls8c_ard_3-2-1_102081_2022-03-15_final
2022-03-16 09:34:46	ga_ls8c_ard_3-2-1_093074_2022-03-16_final
2022-03-16 09:36:46	ga_ls8c_ard_3-2-1_093079_2022-03-16_final
2022-03-16 09:38:45	ga_ls8c_ard_3-2-1_093084_2022-03-16_final
2022-03-16 09:39:33	ga_ls8c_ard_3-2-1_093086_2022-03-16_final
2022-03-16 11:12:27	ga_ls8c_ard_3-2-1_109071_2022-03-16_final
2022-03-16 11:15:15	ga_ls8c_ard_3-2-1_109078_2022-03-16_final
2022-03-16 11:16:03	ga_ls8c_ard_3-2-1_109080_2022-03-16_final
2022-03-17 10:16:49	ga_ls8c_ard_3-2-1_100071_2022-03-17_final
2022-03-17 10:17:13	ga_ls8c_ard_3-2-1_100072_2022-03-17_final
2022-03-17 10:18:25	ga_ls8c_ard_3-2-1_100075_2022-03-17_final
2022-03-17 10:18:49	ga_ls8c_ard_3-2-1_100076_2022-03-17_final
2022-03-17 10:19:13	ga_ls8c_ard_3-2-1_100077_2022-03-17_final
2022-03-17 10:19:37	ga_ls8c_ard_3-2-1_100078_2022-03-17_final
2022-03-17 10:20:25	ga_ls8c_ard_3-2-1_100080_2022-03-17_final
2022-03-17 10:20:49	ga_ls8c_ard_3-2-1_100081_2022-03-17_final
2022-03-17 10:21:13	ga_ls8c_ard_3-2-1_100082_2022-03-17_final
2022-03-17 11:57:42	ga_ls8c_ard_3-2-1_116076_2022-03-17_final
2022-03-17 11:58:30	ga_ls8c_ard_3-2-1_116078_2022-03-17_final
2022-03-18 09:21:35	ga_ls8c_ard_3-2-1_091072_2022-03-17_final
2022-03-18 09:22:47	ga_ls8c_ard_3-2-1_091075_2022-03-17_final
2022-03-18 09:23:11	ga_ls8c_ard_3-2-1_091076_2022-03-17_final
2022-03-18 09:23:35	ga_ls8c_ard_3-2-1_091077_2022-03-17_final
2022-03-18 09:25:11	ga_ls8c_ard_3-2-1_091081_2022-03-17_final
2022-03-18 09:25:35	ga_ls8c_ard_3-2-1_091082_2022-03-17_final
2022-03-18 09:26:46	ga_ls8c_ard_3-2-1_091085_2022-03-17_final
2022-03-18 09:27:10	ga_ls8c_ard_3-2-1_091086_2022-03-17_final
2022-03-18 09:27:34	ga_ls8c_ard_3-2-1_091087_2022-03-17_final
2022-03-18 09:27:58	ga_ls8c_ard_3-2-1_091088_2022-03-17_final
2022-03-18 11:00:04	ga_ls8c_ard_3-2-1_107071_2022-03-18_final
2022-03-18 11:01:40	ga_ls8c_ard_3-2-1_107075_2022-03-18_final
2022-03-18 11:02:04	ga_ls8c_ard_3-2-1_107076_2022-03-18_final
2022-03-18 11:02:28	ga_ls8c_ard_3-2-1_107077_2022-03-18_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