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
2018-09-29 11:10:39	ga_ls8c_ard_3-0-0_109067_2018-09-29_final
2018-09-29 11:11:03	ga_ls8c_ard_3-0-0_109068_2018-09-29_final
2018-09-29 11:11:27	ga_ls8c_ard_3-0-0_109069_2018-09-29_final
2018-09-29 11:11:51	ga_ls8c_ard_3-0-0_109070_2018-09-29_final
2018-09-29 11:12:15	ga_ls8c_ard_3-0-0_109071_2018-09-29_final
2018-09-29 11:12:39	ga_ls8c_ard_3-0-0_109072_2018-09-29_final
2018-09-29 11:13:03	ga_ls8c_ard_3-0-0_109073_2018-09-29_final
2018-10-31 11:10:51	ga_ls8c_ard_3-0-0_109067_2018-10-31_final
2018-10-31 11:11:15	ga_ls8c_ard_3-0-0_109068_2018-10-31_final
2018-10-31 11:11:38	ga_ls8c_ard_3-0-0_109069_2018-10-31_final
2018-10-31 11:12:02	ga_ls8c_ard_3-0-0_109070_2018-10-31_final
2018-10-31 11:12:26	ga_ls8c_ard_3-0-0_109071_2018-10-31_final
2018-10-31 11:12:50	ga_ls8c_ard_3-0-0_109072_2018-10-31_final
2018-10-31 11:13:14	ga_ls8c_ard_3-0-0_109073_2018-10-31_final
2018-12-18 11:10:48	ga_ls8c_ard_3-0-0_109067_2018-12-18_final
2018-12-18 11:11:12	ga_ls8c_ard_3-0-0_109068_2018-12-18_final
2018-12-18 11:11:36	ga_ls8c_ard_3-0-0_109069_2018-12-18_final
2018-12-18 11:12:00	ga_ls8c_ard_3-0-0_109070_2018-12-18_final
2018-12-18 11:12:24	ga_ls8c_ard_3-0-0_109071_2018-12-18_final
2018-12-18 11:12:48	ga_ls8c_ard_3-0-0_109072_2018-12-18_final
2018-12-18 11:13:12	ga_ls8c_ard_3-0-0_109073_2018-12-18_final
2018-12-25 11:16:59	ga_ls8c_ard_3-0-0_110067_2018-12-25_final
2018-12-25 11:17:23	ga_ls8c_ard_3-0-0_110068_2018-12-25_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
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_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
2022-04-28 10:57:20	ga_ls8c_ard_3-2-1_106080_2022-04-28_final
2022-04-28 10:57:44	ga_ls8c_ard_3-2-1_106081_2022-04-28_final
2022-04-28 10:58:08	ga_ls8c_ard_3-2-1_106082_2022-04-28_final
2022-04-28 10:58:32	ga_ls8c_ard_3-2-1_106083_2022-04-28_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-03 11:11:56	ga_ls8c_ard_3-2-1_109070_2022-05-03_final
2022-05-03 11:12:20	ga_ls8c_ard_3-2-1_109071_2022-05-03_final
2022-05-03 11:12:44	ga_ls8c_ard_3-2-1_109072_2022-05-03_final
2022-05-03 11:13:08	ga_ls8c_ard_3-2-1_109073_2022-05-03_final
2022-05-05 11:02:00	ga_ls8c_ard_3-2-1_107076_2022-05-05_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-05 11:02:48	ga_ls8c_ard_3-2-1_107078_2022-05-05_final
2022-05-05 11:03:12	ga_ls8c_ard_3-2-1_107079_2022-05-05_final
2022-05-05 11:03:36	ga_ls8c_ard_3-2-1_107080_2022-05-05_final
2022-05-05 11:04:00	ga_ls8c_ard_3-2-1_107081_2022-05-05_final
2022-05-05 11:04:24	ga_ls8c_ard_3-2-1_107082_2022-05-05_final
2022-05-14 10:57:30	ga_ls8c_ard_3-2-1_106080_2022-05-14_final
2022-05-14 10:57:54	ga_ls8c_ard_3-2-1_106081_2022-05-14_final
2022-05-14 10:58:18	ga_ls8c_ard_3-2-1_106082_2022-05-14_final
2022-05-14 10:58:42	ga_ls8c_ard_3-2-1_106083_2022-05-14_final
2023-08-26 11:11:44	ga_ls8c_ard_3-2-1_109069_2023-08-26_final
2023-08-26 11:12:08	ga_ls8c_ard_3-2-1_109070_2023-08-26_final
2023-08-26 11:12:32	ga_ls8c_ard_3-2-1_109071_2023-08-26_final
2023-08-26 11:12:56	ga_ls8c_ard_3-2-1_109072_2023-08-26_final
2023-08-26 11:13:19	ga_ls8c_ard_3-2-1_109073_2023-08-26_final
2023-08-28 11:02:10	ga_ls8c_ard_3-2-1_107076_2023-08-28_final
2023-08-28 11:02:34	ga_ls8c_ard_3-2-1_107077_2023-08-28_final
2023-08-28 11:02:58	ga_ls8c_ard_3-2-1_107078_2023-08-28_final
2023-08-28 11:03:22	ga_ls8c_ard_3-2-1_107079_2023-08-28_final
2023-08-28 11:03:46	ga_ls8c_ard_3-2-1_107080_2023-08-28_final
2023-08-28 11:04:10	ga_ls8c_ard_3-2-1_107081_2023-08-28_final
2023-08-28 11:04:33	ga_ls8c_ard_3-2-1_107082_2023-08-28_final
2023-12-16 11:11:56	ga_ls8c_ard_3-2-1_109069_2023-12-16_final
2023-12-16 11:12:20	ga_ls8c_ard_3-2-1_109070_2023-12-16_final
2023-12-16 11:12:43	ga_ls8c_ard_3-2-1_109071_2023-12-16_final
2023-12-16 11:13:07	ga_ls8c_ard_3-2-1_109072_2023-12-16_final
2023-12-16 11:13:31	ga_ls8c_ard_3-2-1_109073_2023-12-16_final
2023-12-18 11:03:58	ga_ls8c_ard_3-2-1_107080_2023-12-18_final
2023-12-18 11:04:46	ga_ls8c_ard_3-2-1_107082_2023-12-18_final
2023-12-25 11:06:57	ga_ls8c_ard_3-2-1_108072_2023-12-25_final
2023-12-25 11:07:21	ga_ls8c_ard_3-2-1_108073_2023-12-25_final
2023-12-25 11:07:45	ga_ls8c_ard_3-2-1_108074_2023-12-25_final
2023-12-25 11:08:09	ga_ls8c_ard_3-2-1_108075_2023-12-25_final
2023-12-25 11:08:33	ga_ls8c_ard_3-2-1_108076_2023-12-25_final
2023-12-25 11:08:57	ga_ls8c_ard_3-2-1_108077_2023-12-25_final
2023-12-27 10:57:46	ga_ls8c_ard_3-2-1_106080_2023-12-27_final
2023-12-27 10:58:10	ga_ls8c_ard_3-2-1_106081_2023-12-27_final
2023-12-27 10:58:34	ga_ls8c_ard_3-2-1_106082_2023-12-27_final
2023-12-27 10:58:58	ga_ls8c_ard_3-2-1_106083_2023-12-27_final
2024-01-01 11:11:52	ga_ls8c_ard_3-2-1_109069_2024-01-01_final
2024-01-01 11:12:15	ga_ls8c_ard_3-2-1_109070_2024-01-01_final
2024-01-01 11:12:39	ga_ls8c_ard_3-2-1_109071_2024-01-01_final
2024-01-01 11:13:03	ga_ls8c_ard_3-2-1_109072_2024-01-01_final
2024-01-01 11:13:27	ga_ls8c_ard_3-2-1_109073_2024-01-01_final
2024-01-03 11:02:15	ga_ls8c_ard_3-2-1_107076_2024-01-03_final
2024-01-03 11:02:39	ga_ls8c_ard_3-2-1_107077_2024-01-03_final
2024-01-03 11:03:03	ga_ls8c_ard_3-2-1_107078_2024-01-03_final
2024-01-03 11:03:27	ga_ls8c_ard_3-2-1_107079_2024-01-03_final
2024-01-03 11:03:51	ga_ls8c_ard_3-2-1_107080_2024-01-03_final
2024-01-03 11:04:15	ga_ls8c_ard_3-2-1_107081_2024-01-03_final
2024-01-03 11:04:39	ga_ls8c_ard_3-2-1_107082_2024-01-03_final
2024-01-10 11:07:16	ga_ls8c_ard_3-2-1_108073_2024-01-10_final
2024-01-10 11:07:39	ga_ls8c_ard_3-2-1_108074_2024-01-10_final
2024-01-10 11:08:03	ga_ls8c_ard_3-2-1_108075_2024-01-10_final
2024-01-10 11:08:27	ga_ls8c_ard_3-2-1_108076_2024-01-10_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