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
2017-07-18 10:12:58	ga_ls8c_ard_3-0-0_099077_2017-07-18_final
2017-07-18 10:13:22	ga_ls8c_ard_3-0-0_099078_2017-07-18_final
2017-07-18 10:13:46	ga_ls8c_ard_3-0-0_099079_2017-07-18_final
2017-07-18 10:14:10	ga_ls8c_ard_3-0-0_099080_2017-07-18_final
2017-07-18 10:14:34	ga_ls8c_ard_3-0-0_099081_2017-07-18_final
2017-07-18 10:14:58	ga_ls8c_ard_3-0-0_099082_2017-07-18_final
2017-07-18 10:15:22	ga_ls8c_ard_3-0-0_099083_2017-07-18_final
2017-07-27 10:08:52	ga_ls8c_ard_3-0-0_098082_2017-07-27_final
2017-07-27 10:09:16	ga_ls8c_ard_3-0-0_098083_2017-07-27_final
2017-07-27 10:09:40	ga_ls8c_ard_3-0-0_098084_2017-07-27_final
2017-07-27 10:10:03	ga_ls8c_ard_3-0-0_098085_2017-07-27_final
2017-07-27 10:10:27	ga_ls8c_ard_3-0-0_098086_2017-07-27_final
2021-05-15 10:27:15	ga_ls8c_ard_3-2-0_102067_2021-05-15_final
2021-05-15 10:27:39	ga_ls8c_ard_3-2-0_102068_2021-05-15_final
2021-05-15 10:28:03	ga_ls8c_ard_3-2-0_102069_2021-05-15_final
2021-05-19 10:08:10	ga_ls8c_ard_3-2-0_098081_2021-05-19_final
2021-05-19 10:08:34	ga_ls8c_ard_3-2-0_098082_2021-05-19_final
2021-05-19 10:08:58	ga_ls8c_ard_3-2-0_098083_2021-05-19_final
2021-05-19 10:09:22	ga_ls8c_ard_3-2-0_098084_2021-05-19_final
2021-05-19 10:09:45	ga_ls8c_ard_3-2-0_098085_2021-05-19_final
2021-05-19 10:10:09	ga_ls8c_ard_3-2-0_098086_2021-05-19_final
2021-09-24 10:09:14	ga_ls8c_ard_3-2-0_098082_2021-09-24_final
2021-09-24 10:09:38	ga_ls8c_ard_3-2-0_098083_2021-09-24_final
2021-09-24 10:10:02	ga_ls8c_ard_3-2-0_098084_2021-09-24_final
2021-09-24 10:10:26	ga_ls8c_ard_3-2-0_098085_2021-09-24_final
2021-09-24 10:10:50	ga_ls8c_ard_3-2-0_098086_2021-09-24_final
2021-09-29 10:22:14	ga_ls8c_ard_3-2-0_101068_2021-09-29_final
2021-09-29 10:22:38	ga_ls8c_ard_3-2-0_101069_2021-09-29_final
2021-09-29 10:23:02	ga_ls8c_ard_3-2-0_101070_2021-09-29_final
2021-09-29 10:23:26	ga_ls8c_ard_3-2-0_101071_2021-09-29_final
2021-09-29 10:23:50	ga_ls8c_ard_3-2-0_101072_2021-09-29_final
2021-09-29 10:24:14	ga_ls8c_ard_3-2-0_101073_2021-09-29_final
2021-09-29 10:24:38	ga_ls8c_ard_3-2-0_101074_2021-09-29_final
2021-10-10 10:09:20	ga_ls8c_ard_3-2-0_098082_2021-10-10_final
2021-10-10 10:09:44	ga_ls8c_ard_3-2-0_098083_2021-10-10_final
2021-10-10 10:10:08	ga_ls8c_ard_3-2-0_098084_2021-10-10_final
2021-10-10 10:10:32	ga_ls8c_ard_3-2-0_098085_2021-10-10_final
2021-10-10 10:10:56	ga_ls8c_ard_3-2-0_098086_2021-10-10_final
2021-10-15 10:22:19	ga_ls8c_ard_3-2-0_101068_2021-10-15_final
2021-10-15 10:22:43	ga_ls8c_ard_3-2-0_101069_2021-10-15_final
2021-10-15 10:23:06	ga_ls8c_ard_3-2-0_101070_2021-10-15_final
2021-10-15 10:23:30	ga_ls8c_ard_3-2-0_101071_2021-10-15_final
2021-10-15 10:23:54	ga_ls8c_ard_3-2-0_101072_2021-10-15_final
2021-10-15 10:24:18	ga_ls8c_ard_3-2-0_101073_2021-10-15_final
2021-10-15 10:24:42	ga_ls8c_ard_3-2-0_101074_2021-10-15_final
2023-06-24 10:17:12	ga_ls8c_ard_3-2-1_100073_2023-06-24_final
2023-06-24 10:17:36	ga_ls8c_ard_3-2-1_100074_2023-06-24_final
2023-06-24 10:18:00	ga_ls8c_ard_3-2-1_100075_2023-06-24_final
2023-06-24 10:18:23	ga_ls8c_ard_3-2-1_100076_2023-06-24_final
2023-06-24 10:18:47	ga_ls8c_ard_3-2-1_100077_2023-06-24_final
2023-06-24 10:19:11	ga_ls8c_ard_3-2-1_100078_2023-06-24_final
2023-06-24 10:19:35	ga_ls8c_ard_3-2-1_100079_2023-06-24_final
2023-06-26 10:08:28	ga_ls8c_ard_3-2-1_098082_2023-06-26_final
2023-06-26 10:08:52	ga_ls8c_ard_3-2-1_098083_2023-06-26_final
2023-06-26 10:09:16	ga_ls8c_ard_3-2-1_098084_2023-06-26_final
2023-06-26 10:09:40	ga_ls8c_ard_3-2-1_098085_2023-06-26_final
2023-07-03 10:12:45	ga_ls8c_ard_3-2-1_099077_2023-07-03_final
2023-07-03 10:13:09	ga_ls8c_ard_3-2-1_099078_2023-07-03_final
2023-07-03 10:13:33	ga_ls8c_ard_3-2-1_099079_2023-07-03_final
2023-07-03 10:13:57	ga_ls8c_ard_3-2-1_099080_2023-07-03_final
2023-07-03 10:14:21	ga_ls8c_ard_3-2-1_099081_2023-07-03_final
2023-07-03 10:14:45	ga_ls8c_ard_3-2-1_099082_2023-07-03_final
2023-07-03 10:15:09	ga_ls8c_ard_3-2-1_099083_2023-07-03_final
2023-07-21 10:03:39	ga_ls8c_ard_3-2-1_097085_2023-07-21_final
2023-07-24 10:27:25	ga_ls8c_ard_3-2-1_102067_2023-07-24_final
2023-07-24 10:27:49	ga_ls8c_ard_3-2-1_102068_2023-07-24_final
2023-07-24 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-07-24_final
2023-07-26 10:17:29	ga_ls8c_ard_3-2-1_100073_2023-07-26_final
2023-07-26 10:17:53	ga_ls8c_ard_3-2-1_100074_2023-07-26_final
2023-07-26 10:18:17	ga_ls8c_ard_3-2-1_100075_2023-07-26_final
2023-07-26 10:18:41	ga_ls8c_ard_3-2-1_100076_2023-07-26_final
2023-07-26 10:19:05	ga_ls8c_ard_3-2-1_100077_2023-07-26_final
2023-07-26 10:19:29	ga_ls8c_ard_3-2-1_100078_2023-07-26_final
2023-07-26 10:19:53	ga_ls8c_ard_3-2-1_100079_2023-07-26_final
2023-09-10 10:27:41	ga_ls8c_ard_3-2-1_102067_2023-09-10_final
2023-09-10 10:28:05	ga_ls8c_ard_3-2-1_102068_2023-09-10_final
2023-09-10 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-09-10_final
2023-09-12 10:17:44	ga_ls8c_ard_3-2-1_100073_2023-09-12_final
2023-09-12 10:18:08	ga_ls8c_ard_3-2-1_100074_2023-09-12_final
2023-09-12 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-09-12_final
2023-09-12 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-09-12_final
2023-09-12 10:19:20	ga_ls8c_ard_3-2-1_100077_2023-09-12_final
2023-09-12 10:19:44	ga_ls8c_ard_3-2-1_100078_2023-09-12_final
2023-09-12 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-09-12_final
2023-10-12 10:27:50	ga_ls8c_ard_3-2-1_102067_2023-10-12_final
2023-10-12 10:28:14	ga_ls8c_ard_3-2-1_102068_2023-10-12_final
2023-10-12 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-10-12_final
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_final
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_nrt
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_nrt
2023-10-14 10:18:40	ga_ls8c_ard_3-2-1_100075_2023-10-14_final
2023-10-14 10:18:40	ga_ls8c_ard_3-2-1_100075_2023-10-14_nrt
2023-10-14 10:19:04	ga_ls8c_ard_3-2-1_100076_2023-10-14_final
2023-10-14 10:19:04	ga_ls8c_ard_3-2-1_100076_2023-10-14_nrt
2023-10-14 10:19:28	ga_ls8c_ard_3-2-1_100077_2023-10-14_final
2023-10-14 10:19:28	ga_ls8c_ard_3-2-1_100077_2023-10-14_nrt
2023-10-14 10:19:52	ga_ls8c_ard_3-2-1_100078_2023-10-14_final
2023-10-14 10:19:52	ga_ls8c_ard_3-2-1_100078_2023-10-14_nrt
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_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