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
2022-03-30 11:23:26	ga_ls8c_ard_3-2-1_111068_2022-03-30_final
2022-03-30 11:23:50	ga_ls8c_ard_3-2-1_111069_2022-03-30_final
2022-03-30 11:24:14	ga_ls8c_ard_3-2-1_111070_2022-03-30_final
2022-03-30 11:24:38	ga_ls8c_ard_3-2-1_111071_2022-03-30_final
2022-03-30 11:25:01	ga_ls8c_ard_3-2-1_111072_2022-03-30_final
2022-03-30 11:25:25	ga_ls8c_ard_3-2-1_111073_2022-03-30_final
2022-03-30 11:25:49	ga_ls8c_ard_3-2-1_111074_2022-03-30_final
2022-03-30 11:26:13	ga_ls8c_ard_3-2-1_111075_2022-03-30_final
2022-03-30 11:26:37	ga_ls8c_ard_3-2-1_111076_2022-03-30_final
2022-03-30 11:27:01	ga_ls8c_ard_3-2-1_111077_2022-03-30_final
2022-04-01 11:11:28	ga_ls8c_ard_3-2-1_109069_2022-04-01_final
2022-04-01 11:11:52	ga_ls8c_ard_3-2-1_109070_2022-04-01_final
2022-04-01 11:12:16	ga_ls8c_ard_3-2-1_109071_2022-04-01_final
2022-04-01 11:12:40	ga_ls8c_ard_3-2-1_109072_2022-04-01_final
2022-04-01 11:13:04	ga_ls8c_ard_3-2-1_109073_2022-04-01_final
2022-04-01 11:13:28	ga_ls8c_ard_3-2-1_109074_2022-04-01_final
2022-04-01 11:13:52	ga_ls8c_ard_3-2-1_109075_2022-04-01_final
2022-04-01 11:14:15	ga_ls8c_ard_3-2-1_109076_2022-04-01_final
2022-04-01 11:14:39	ga_ls8c_ard_3-2-1_109077_2022-04-01_final
2022-04-01 11:15:03	ga_ls8c_ard_3-2-1_109078_2022-04-01_final
2022-04-01 11:15:27	ga_ls8c_ard_3-2-1_109079_2022-04-01_final
2022-04-01 11:15:51	ga_ls8c_ard_3-2-1_109080_2022-04-01_final
2022-04-01 11:16:15	ga_ls8c_ard_3-2-1_109081_2022-04-01_final
2022-04-01 11:16:39	ga_ls8c_ard_3-2-1_109082_2022-04-01_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-01 11:17:27	ga_ls8c_ard_3-2-1_109084_2022-04-01_final
2022-04-03 11:02:42	ga_ls8c_ard_3-2-1_107078_2022-04-03_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-03 11:03:54	ga_ls8c_ard_3-2-1_107081_2022-04-03_final
2022-04-03 11:04:17	ga_ls8c_ard_3-2-1_107082_2022-04-03_final
2022-04-03 11:04:41	ga_ls8c_ard_3-2-1_107083_2022-04-03_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-06 11:31:14	ga_ls8c_ard_3-2-1_112072_2022-04-06_final
2022-04-08 11:17:42	ga_ls8c_ard_3-2-1_110069_2022-04-08_final
2022-04-08 11:18:06	ga_ls8c_ard_3-2-1_110070_2022-04-08_final
2022-04-08 11:18:30	ga_ls8c_ard_3-2-1_110071_2022-04-08_final
2022-04-08 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-08_final
2022-04-08 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-08_final
2022-04-08 11:19:42	ga_ls8c_ard_3-2-1_110074_2022-04-08_final
2022-04-08 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-08_final
2022-04-08 11:20:30	ga_ls8c_ard_3-2-1_110076_2022-04-08_final
2022-04-08 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-08_final
2022-04-08 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-08_final
2022-04-08 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-08_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-08 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-08_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-10 11:07:45	ga_ls8c_ard_3-2-1_108075_2022-04-10_final
2022-04-10 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-04-10_final
2022-04-10 11:08:33	ga_ls8c_ard_3-2-1_108077_2022-04-10_final
2022-04-10 11:08:57	ga_ls8c_ard_3-2-1_108078_2022-04-10_final
2022-04-10 11:09:21	ga_ls8c_ard_3-2-1_108079_2022-04-10_final
2022-04-10 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-04-10_final
2022-04-10 11:10:09	ga_ls8c_ard_3-2-1_108081_2022-04-10_final
2022-04-10 11:10:33	ga_ls8c_ard_3-2-1_108082_2022-04-10_final
2022-04-10 11:10:57	ga_ls8c_ard_3-2-1_108083_2022-04-10_final
2022-04-10 11:11:21	ga_ls8c_ard_3-2-1_108084_2022-04-10_final
2022-04-12 10:58:12	ga_ls8c_ard_3-2-1_106082_2022-04-12_final
2022-04-12 10:58:36	ga_ls8c_ard_3-2-1_106083_2022-04-12_final
2022-04-15 11:23:32	ga_ls8c_ard_3-2-1_111068_2022-04-15_final
2022-04-15 11:23:56	ga_ls8c_ard_3-2-1_111069_2022-04-15_final
2022-04-15 11:24:20	ga_ls8c_ard_3-2-1_111070_2022-04-15_final
2022-04-15 11:24:44	ga_ls8c_ard_3-2-1_111071_2022-04-15_final
2022-04-15 11:25:08	ga_ls8c_ard_3-2-1_111072_2022-04-15_final
2022-04-15 11:25:32	ga_ls8c_ard_3-2-1_111073_2022-04-15_final
2022-04-15 11:25:56	ga_ls8c_ard_3-2-1_111074_2022-04-15_final
2022-04-15 11:26:19	ga_ls8c_ard_3-2-1_111075_2022-04-15_final
2022-04-15 11:26:43	ga_ls8c_ard_3-2-1_111076_2022-04-15_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_final
2022-04-17 11:11:34	ga_ls8c_ard_3-2-1_109069_2022-04-17_final
2022-04-17 11:11:58	ga_ls8c_ard_3-2-1_109070_2022-04-17_final
2022-04-17 11:12:22	ga_ls8c_ard_3-2-1_109071_2022-04-17_final
2022-04-17 11:12:46	ga_ls8c_ard_3-2-1_109072_2022-04-17_final
2022-04-17 11:13:10	ga_ls8c_ard_3-2-1_109073_2022-04-17_final
2022-04-17 11:13:34	ga_ls8c_ard_3-2-1_109074_2022-04-17_final
2022-04-17 11:13:57	ga_ls8c_ard_3-2-1_109075_2022-04-17_final
2022-04-17 11:14:21	ga_ls8c_ard_3-2-1_109076_2022-04-17_final
2022-04-17 11:14:45	ga_ls8c_ard_3-2-1_109077_2022-04-17_final
2022-04-17 11:15:09	ga_ls8c_ard_3-2-1_109078_2022-04-17_final
2022-04-17 11:15:33	ga_ls8c_ard_3-2-1_109079_2022-04-17_final
2022-04-17 11:15:57	ga_ls8c_ard_3-2-1_109080_2022-04-17_final
2022-04-17 11:16:21	ga_ls8c_ard_3-2-1_109081_2022-04-17_final
2022-04-17 11:16:45	ga_ls8c_ard_3-2-1_109082_2022-04-17_final
2022-04-17 11:17:09	ga_ls8c_ard_3-2-1_109083_2022-04-17_final
2022-04-17 11:17:33	ga_ls8c_ard_3-2-1_109084_2022-04-17_final
2022-04-19 11:02:47	ga_ls8c_ard_3-2-1_107078_2022-04-19_final
2022-04-19 11:03:11	ga_ls8c_ard_3-2-1_107079_2022-04-19_final
2022-04-19 11:03:35	ga_ls8c_ard_3-2-1_107080_2022-04-19_final
2022-04-19 11:03:59	ga_ls8c_ard_3-2-1_107081_2022-04-19_final
2022-04-19 11:04:23	ga_ls8c_ard_3-2-1_107082_2022-04-19_final
2022-04-19 11:04:47	ga_ls8c_ard_3-2-1_107083_2022-04-19_final
2022-04-19 11:05:11	ga_ls8c_ard_3-2-1_107084_2022-04-19_final
2022-04-22 11:31:17	ga_ls8c_ard_3-2-1_112072_2022-04-22_final
2022-04-24 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-24_final
2022-04-24 11:20:30	ga_ls8c_ard_3-2-1_110076_2022-04-24_final
2022-04-24 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-24_final
2022-04-24 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-24_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-26 11:10:31	ga_ls8c_ard_3-2-1_108082_2022-04-26_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