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

52 results

Time (local)	Label
2022-01-13 10:59:36	ga_ls8c_ard_3-2-1_107069_2022-01-13_final
2022-02-14 10:59:27	ga_ls8c_ard_3-2-1_107069_2022-02-14_final
2022-03-01 11:57:24	ga_ls8c_ard_3-2-1_116075_2022-03-01_final
2022-03-18 10:58:52	ga_ls8c_ard_3-2-1_107068_2022-03-18_final
2022-03-24 10:22:07	ga_ls8c_ard_3-2-1_101069_2022-03-24_final
2022-04-12 10:52:13	ga_ls8c_ard_3-2-1_106067_2022-04-12_final
2022-04-13 11:42:16	ga_ls8c_ard_3-2-1_113084_2022-04-13_final
2022-04-14 10:39:52	ga_ls8c_ard_3-2-1_104067_2022-04-14_final
2022-04-30 10:39:48	ga_ls8c_ard_3-2-1_104067_2022-04-30_final
2022-05-05 10:58:48	ga_ls8c_ard_3-2-1_107068_2022-05-05_final
2022-06-16 11:42:37	ga_ls8c_ard_3-2-1_113084_2022-06-16_final
2022-07-01 10:52:38	ga_ls8c_ard_3-2-1_106067_2022-07-01_final
2022-07-08 10:59:37	ga_ls8c_ard_3-2-1_107069_2022-07-08_final
2022-07-19 10:40:18	ga_ls8c_ard_3-2-1_104067_2022-07-19_final
2022-07-23 11:57:43	ga_ls8c_ard_3-2-1_116075_2022-07-23_final
2022-08-18 09:23:37	ga_ls8c_ard_3-2-1_090091_2022-08-17_final
2022-08-22 10:28:12	ga_ls8c_ard_3-2-1_102067_2022-08-22_final
2022-09-19 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-09-19_final
2022-09-26 10:59:37	ga_ls8c_ard_3-2-1_107068_2022-09-26_final
2022-10-28 10:59:36	ga_ls8c_ard_3-2-1_107068_2022-10-28_final
2022-11-07 11:43:04	ga_ls8c_ard_3-2-1_113084_2022-11-07_final
2022-11-15 09:16:15	ga_ls8c_ard_3-2-1_089088_2022-11-14_final
2022-11-26 10:28:14	ga_ls8c_ard_3-2-1_102067_2022-11-26_final
2022-12-30 11:57:48	ga_ls8c_ard_3-2-1_116075_2022-12-30_final
2023-01-02 09:16:08	ga_ls8c_ard_3-2-1_089088_2023-01-01_final
2023-02-01 10:59:21	ga_ls8c_ard_3-2-1_107068_2023-02-01_final
2023-02-19 09:15:54	ga_ls8c_ard_3-2-1_089088_2023-02-18_final
2023-03-15 11:42:24	ga_ls8c_ard_3-2-1_113084_2023-03-15_final
2023-03-18 10:27:36	ga_ls8c_ard_3-2-1_102067_2023-03-18_final
2023-03-21 10:58:51	ga_ls8c_ard_3-2-1_107068_2023-03-21_final
2023-03-23 09:15:33	ga_ls8c_ard_3-2-1_089088_2023-03-22_final
2023-03-30 10:52:11	ga_ls8c_ard_3-2-1_106067_2023-03-30_final
2023-04-06 10:58:39	ga_ls8c_ard_3-2-1_107068_2023-04-06_final
2023-04-15 09:22:38	ga_ls8c_ard_3-2-1_090091_2023-04-14_final
2023-04-21 11:56:54	ga_ls8c_ard_3-2-1_116075_2023-04-21_final
2023-05-05 10:27:06	ga_ls8c_ard_3-2-1_102067_2023-05-05_final
2023-05-24 10:58:40	ga_ls8c_ard_3-2-1_107069_2023-05-24_final
2023-06-02 09:22:24	ga_ls8c_ard_3-2-1_090091_2023-06-01_final
2023-06-09 10:58:23	ga_ls8c_ard_3-2-1_107068_2023-06-09_final
2023-08-05 10:52:15	ga_ls8c_ard_3-2-1_106067_2023-08-05_final
2023-08-06 11:42:18	ga_ls8c_ard_3-2-1_113084_2023-08-06_final
2023-08-11 11:57:14	ga_ls8c_ard_3-2-1_116075_2023-08-11_final
2023-09-24 10:40:07	ga_ls8c_ard_3-2-1_104067_2023-09-24_final
2023-09-26 10:27:46	ga_ls8c_ard_3-2-1_102067_2023-09-26_final
2023-09-29 10:59:05	ga_ls8c_ard_3-2-1_107068_2023-09-29_final
2023-09-29 10:59:29	ga_ls8c_ard_3-2-1_107069_2023-09-29_final
2023-12-01 11:57:35	ga_ls8c_ard_3-2-1_116075_2023-12-01_final
2023-12-18 10:59:11	ga_ls8c_ard_3-2-1_107068_2023-12-18_final
2024-01-19 10:59:28	ga_ls8c_ard_3-2-1_107069_2024-01-19_final
2024-01-29 11:42:28	ga_ls8c_ard_3-2-1_113084_2024-01-29_final
2024-03-01 11:42:24	ga_ls8c_ard_3-2-1_113084_2024-03-01_final
2024-03-02 10:39:59	ga_ls8c_ard_3-2-1_104067_2024-03-02_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