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
2021-11-05 10:46:50	ga_ls8c_ard_3-2-0_104083_2021-11-05_final
2021-11-10 11:00:33	ga_ls8c_ard_3-2-0_107071_2021-11-10_final
2021-11-10 11:00:57	ga_ls8c_ard_3-2-0_107072_2021-11-10_final
2021-11-10 11:01:21	ga_ls8c_ard_3-2-0_107073_2021-11-10_final
2021-11-10 11:01:45	ga_ls8c_ard_3-2-0_107074_2021-11-10_final
2021-11-10 11:02:09	ga_ls8c_ard_3-2-0_107075_2021-11-10_final
2021-11-10 11:02:33	ga_ls8c_ard_3-2-0_107076_2021-11-10_final
2021-11-12 10:51:22	ga_ls8c_ard_3-2-0_105079_2021-11-12_final
2021-11-12 10:51:46	ga_ls8c_ard_3-2-0_105080_2021-11-12_final
2021-11-12 10:52:10	ga_ls8c_ard_3-2-0_105081_2021-11-12_final
2021-11-12 10:52:34	ga_ls8c_ard_3-2-0_105082_2021-11-12_final
2021-11-12 10:52:58	ga_ls8c_ard_3-2-0_105083_2021-11-12_final
2021-11-17 11:05:05	ga_ls8c_ard_3-2-0_108067_2021-11-17_final
2021-11-17 11:05:29	ga_ls8c_ard_3-2-0_108068_2021-11-17_final
2021-11-17 11:05:53	ga_ls8c_ard_3-2-0_108069_2021-11-17_final
2021-11-17 11:06:17	ga_ls8c_ard_3-2-0_108070_2021-11-17_final
2021-11-17 11:06:41	ga_ls8c_ard_3-2-0_108071_2021-11-17_final
2021-11-19 10:55:55	ga_ls8c_ard_3-2-0_106075_2021-11-19_final
2021-11-19 10:56:19	ga_ls8c_ard_3-2-0_106076_2021-11-19_final
2021-11-19 10:56:43	ga_ls8c_ard_3-2-0_106077_2021-11-19_final
2021-11-19 10:57:07	ga_ls8c_ard_3-2-0_106078_2021-11-19_final
2021-11-19 10:57:31	ga_ls8c_ard_3-2-0_106079_2021-11-19_final
2021-11-19 10:57:54	ga_ls8c_ard_3-2-0_106080_2021-11-19_final
2021-11-19 10:58:18	ga_ls8c_ard_3-2-0_106081_2021-11-19_final
2021-11-21 10:46:45	ga_ls8c_ard_3-2-0_104083_2021-11-21_final
2021-11-26 11:00:31	ga_ls8c_ard_3-2-0_107071_2021-11-26_final
2021-11-26 11:00:55	ga_ls8c_ard_3-2-0_107072_2021-11-26_final
2021-11-26 11:01:19	ga_ls8c_ard_3-2-0_107073_2021-11-26_final
2021-11-26 11:01:43	ga_ls8c_ard_3-2-0_107074_2021-11-26_final
2021-11-26 11:02:07	ga_ls8c_ard_3-2-0_107075_2021-11-26_final
2021-11-26 11:02:31	ga_ls8c_ard_3-2-0_107076_2021-11-26_final
2021-11-28 10:51:21	ga_ls8c_ard_3-2-0_105079_2021-11-28_final
2021-11-28 10:51:45	ga_ls8c_ard_3-2-0_105080_2021-11-28_final
2021-11-28 10:52:09	ga_ls8c_ard_3-2-0_105081_2021-11-28_final
2021-11-28 10:52:33	ga_ls8c_ard_3-2-0_105082_2021-11-28_final
2021-11-28 10:52:57	ga_ls8c_ard_3-2-0_105083_2021-11-28_final
2021-12-03 11:05:55	ga_ls8c_ard_3-2-0_108069_2021-12-03_final
2021-12-03 11:06:19	ga_ls8c_ard_3-2-0_108070_2021-12-03_final
2021-12-03 11:06:43	ga_ls8c_ard_3-2-0_108071_2021-12-03_final
2021-12-05 10:55:57	ga_ls8c_ard_3-2-1_106075_2021-12-05_final
2021-12-05 10:56:21	ga_ls8c_ard_3-2-1_106076_2021-12-05_final
2021-12-05 10:56:45	ga_ls8c_ard_3-2-1_106077_2021-12-05_final
2021-12-05 10:57:09	ga_ls8c_ard_3-2-1_106078_2021-12-05_final
2021-12-05 10:57:32	ga_ls8c_ard_3-2-1_106079_2021-12-05_final
2021-12-05 10:57:56	ga_ls8c_ard_3-2-1_106080_2021-12-05_final
2021-12-05 10:58:20	ga_ls8c_ard_3-2-1_106081_2021-12-05_final
2021-12-12 11:00:31	ga_ls8c_ard_3-2-1_107071_2021-12-12_final
2021-12-12 11:00:55	ga_ls8c_ard_3-2-1_107072_2021-12-12_final
2021-12-12 11:01:19	ga_ls8c_ard_3-2-1_107073_2021-12-12_final
2021-12-12 11:01:43	ga_ls8c_ard_3-2-1_107074_2021-12-12_final
2021-12-12 11:02:07	ga_ls8c_ard_3-2-1_107075_2021-12-12_final
2021-12-12 11:02:31	ga_ls8c_ard_3-2-1_107076_2021-12-12_final
2022-04-10 11:05:22	ga_ls8c_ard_3-2-1_108069_2022-04-10_final
2022-04-10 11:05:46	ga_ls8c_ard_3-2-1_108070_2022-04-10_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-12 10:55:24	ga_ls8c_ard_3-2-1_106075_2022-04-12_final
2022-04-12 10:55:48	ga_ls8c_ard_3-2-1_106076_2022-04-12_final
2022-04-12 10:56:12	ga_ls8c_ard_3-2-1_106077_2022-04-12_final
2022-04-12 10:56:36	ga_ls8c_ard_3-2-1_106078_2022-04-12_final
2022-04-12 10:57:00	ga_ls8c_ard_3-2-1_106079_2022-04-12_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-12 10:57:48	ga_ls8c_ard_3-2-1_106081_2022-04-12_final
2022-04-19 10:59:36	ga_ls8c_ard_3-2-1_107070_2022-04-19_final
2022-04-19 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-04-19_final
2022-04-19 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-04-19_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-19 11:01:11	ga_ls8c_ard_3-2-1_107074_2022-04-19_final
2022-04-19 11:01:35	ga_ls8c_ard_3-2-1_107075_2022-04-19_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-26 11:06:08	ga_ls8c_ard_3-2-1_108071_2022-04-26_final
2022-04-28 10:55:20	ga_ls8c_ard_3-2-1_106075_2022-04-28_final
2022-04-28 10:55:44	ga_ls8c_ard_3-2-1_106076_2022-04-28_final
2022-04-28 10:56:08	ga_ls8c_ard_3-2-1_106077_2022-04-28_final
2022-04-28 10:56:32	ga_ls8c_ard_3-2-1_106078_2022-04-28_final
2022-04-28 10:56:56	ga_ls8c_ard_3-2-1_106079_2022-04-28_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
2022-05-05 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-05-05_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-05 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-05-05_final
2022-05-05 11:01:12	ga_ls8c_ard_3-2-1_107074_2022-05-05_final
2022-05-05 11:01:36	ga_ls8c_ard_3-2-1_107075_2022-05-05_final
2022-05-05 11:02:00	ga_ls8c_ard_3-2-1_107076_2022-05-05_final
2022-05-07 10:50:52	ga_ls8c_ard_3-2-1_105079_2022-05-07_final
2022-05-07 10:51:15	ga_ls8c_ard_3-2-1_105080_2022-05-07_final
2022-05-07 10:51:39	ga_ls8c_ard_3-2-1_105081_2022-05-07_final
2022-05-07 10:52:03	ga_ls8c_ard_3-2-1_105082_2022-05-07_final
2022-05-07 10:52:27	ga_ls8c_ard_3-2-1_105083_2022-05-07_final
2023-05-17 10:54:50	ga_ls8c_ard_3-2-1_106075_2023-05-17_final
2023-05-17 10:55:14	ga_ls8c_ard_3-2-1_106076_2023-05-17_final
2023-05-17 10:55:38	ga_ls8c_ard_3-2-1_106077_2023-05-17_final
2023-05-17 10:56:02	ga_ls8c_ard_3-2-1_106078_2023-05-17_final
2023-05-17 10:56:26	ga_ls8c_ard_3-2-1_106079_2023-05-17_final
2023-05-17 10:56:50	ga_ls8c_ard_3-2-1_106080_2023-05-17_final
2023-05-17 10:57:14	ga_ls8c_ard_3-2-1_106081_2023-05-17_final
2023-05-24 10:59:28	ga_ls8c_ard_3-2-1_107071_2023-05-24_final
2023-05-24 10:59:52	ga_ls8c_ard_3-2-1_107072_2023-05-24_final
2023-05-24 11:00:16	ga_ls8c_ard_3-2-1_107073_2023-05-24_final
2023-05-24 11:00:40	ga_ls8c_ard_3-2-1_107074_2023-05-24_final
2023-05-24 11:01:04	ga_ls8c_ard_3-2-1_107075_2023-05-24_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