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

63 results

Time (local)	Label
2022-01-03 10:22:32	ga_ls8c_ard_3-2-1_101069_2022-01-03_final
2022-01-19 10:22:29	ga_ls8c_ard_3-2-1_101069_2022-01-19_final
2022-01-22 09:23:16	ga_ls8c_ard_3-2-1_090091_2022-01-21_final
2022-02-07 09:23:13	ga_ls8c_ard_3-2-1_090091_2022-02-06_final
2022-02-13 11:57:29	ga_ls8c_ard_3-2-1_116075_2022-02-13_final
2022-02-23 09:23:07	ga_ls8c_ard_3-2-1_090091_2022-02-22_final
2022-03-15 10:27:36	ga_ls8c_ard_3-2-1_102067_2022-03-15_final
2022-04-18 11:57:13	ga_ls8c_ard_3-2-1_116075_2022-04-18_final
2022-04-25 10:22:05	ga_ls8c_ard_3-2-1_101069_2022-04-25_final
2022-05-04 11:57:13	ga_ls8c_ard_3-2-1_116075_2022-05-04_final
2022-05-20 11:57:20	ga_ls8c_ard_3-2-1_116075_2022-05-20_final
2022-05-30 09:23:03	ga_ls8c_ard_3-2-1_090091_2022-05-29_final
2022-05-30 10:52:21	ga_ls8c_ard_3-2-1_106067_2022-05-30_final
2022-06-01 10:40:01	ga_ls8c_ard_3-2-1_104067_2022-06-01_final
2022-06-05 11:57:26	ga_ls8c_ard_3-2-1_116075_2022-06-05_final
2022-06-06 10:59:02	ga_ls8c_ard_3-2-1_107068_2022-06-06_final
2022-06-15 09:23:15	ga_ls8c_ard_3-2-1_090091_2022-06-14_final
2022-07-10 09:15:57	ga_ls8c_ard_3-2-1_089088_2022-07-09_final
2022-07-14 10:22:30	ga_ls8c_ard_3-2-1_101069_2022-07-14_final
2022-07-30 10:22:41	ga_ls8c_ard_3-2-1_101069_2022-07-30_final
2022-08-02 09:23:31	ga_ls8c_ard_3-2-1_090091_2022-08-01_final
2022-08-25 10:59:54	ga_ls8c_ard_3-2-1_107069_2022-08-25_final
2022-09-25 11:58:02	ga_ls8c_ard_3-2-1_116075_2022-09-25_final
2022-09-26 11:00:01	ga_ls8c_ard_3-2-1_107069_2022-09-26_final
2022-10-30 09:16:21	ga_ls8c_ard_3-2-1_089088_2022-10-29_final
2022-11-06 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-11-06_final
2022-11-24 10:40:35	ga_ls8c_ard_3-2-1_104067_2022-11-24_final
2022-12-05 10:22:51	ga_ls8c_ard_3-2-1_101069_2022-12-05_final
2022-12-08 10:52:56	ga_ls8c_ard_3-2-1_106067_2022-12-08_final
2022-12-15 10:59:27	ga_ls8c_ard_3-2-1_107068_2022-12-15_final
2023-01-10 11:42:49	ga_ls8c_ard_3-2-1_113084_2023-01-10_final
2023-01-13 10:28:01	ga_ls8c_ard_3-2-1_102067_2023-01-13_final
2023-01-31 11:57:46	ga_ls8c_ard_3-2-1_116075_2023-01-31_final
2023-02-10 09:23:25	ga_ls8c_ard_3-2-1_090091_2023-02-09_final
2023-02-17 10:59:36	ga_ls8c_ard_3-2-1_107069_2023-02-17_final
2023-03-11 10:22:16	ga_ls8c_ard_3-2-1_101069_2023-03-11_final
2023-04-03 10:27:25	ga_ls8c_ard_3-2-1_102067_2023-04-03_final
2023-04-05 11:57:05	ga_ls8c_ard_3-2-1_116075_2023-04-05_final
2023-04-08 09:15:21	ga_ls8c_ard_3-2-1_089088_2023-04-07_final
2023-06-09 10:58:47	ga_ls8c_ard_3-2-1_107069_2023-06-09_final
2023-06-20 10:39:30	ga_ls8c_ard_3-2-1_104067_2023-06-20_final
2023-06-24 11:56:53	ga_ls8c_ard_3-2-1_116075_2023-06-24_final
2023-06-25 10:58:29	ga_ls8c_ard_3-2-1_107068_2023-06-25_final
2023-07-04 09:22:44	ga_ls8c_ard_3-2-1_090091_2023-07-03_final
2023-07-11 10:58:40	ga_ls8c_ard_3-2-1_107068_2023-07-11_final
2023-07-20 09:22:47	ga_ls8c_ard_3-2-1_090091_2023-07-19_final
2023-07-20 10:52:05	ga_ls8c_ard_3-2-1_106067_2023-07-20_final
2023-07-29 09:15:31	ga_ls8c_ard_3-2-1_089088_2023-07-28_final
2023-08-05 09:22:57	ga_ls8c_ard_3-2-1_090091_2023-08-04_final
2023-08-23 10:40:01	ga_ls8c_ard_3-2-1_104067_2023-08-23_final
2023-08-30 09:15:42	ga_ls8c_ard_3-2-1_089088_2023-08-29_final
2023-09-15 09:15:46	ga_ls8c_ard_3-2-1_089088_2023-09-14_final
2023-10-10 10:40:11	ga_ls8c_ard_3-2-1_104067_2023-10-10_final
2023-10-21 10:22:26	ga_ls8c_ard_3-2-1_101069_2023-10-21_final
2023-11-16 10:59:34	ga_ls8c_ard_3-2-1_107069_2023-11-16_final
2023-11-25 09:23:20	ga_ls8c_ard_3-2-1_090091_2023-11-24_final
2023-11-25 10:52:38	ga_ls8c_ard_3-2-1_106067_2023-11-25_final
2023-12-02 10:59:09	ga_ls8c_ard_3-2-1_107068_2023-12-02_final
2023-12-02 10:59:33	ga_ls8c_ard_3-2-1_107069_2023-12-02_final
2023-12-13 10:40:12	ga_ls8c_ard_3-2-1_104067_2023-12-13_final
2023-12-29 10:40:12	ga_ls8c_ard_3-2-1_104067_2023-12-29_final
2024-01-03 10:59:04	ga_ls8c_ard_3-2-1_107068_2024-01-03_final
2024-04-02 11:37:16	ga_ls8c_ard_3-2-1_113072_2024-04-02_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