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

67 results

Time (local)	Label
2022-01-28 11:57:31	ga_ls8c_ard_3-2-1_116075_2022-01-28_final
2022-02-25 10:40:03	ga_ls8c_ard_3-2-1_104067_2022-02-25_final
2022-03-02 10:59:23	ga_ls8c_ard_3-2-1_107069_2022-03-02_final
2022-03-17 11:57:18	ga_ls8c_ard_3-2-1_116075_2022-03-17_final
2022-03-27 09:22:52	ga_ls8c_ard_3-2-1_090091_2022-03-26_final
2022-04-03 10:59:06	ga_ls8c_ard_3-2-1_107069_2022-04-03_final
2022-04-16 10:27:30	ga_ls8c_ard_3-2-1_102067_2022-04-16_final
2022-04-28 09:22:51	ga_ls8c_ard_3-2-1_090091_2022-04-27_final
2022-04-29 11:42:11	ga_ls8c_ard_3-2-1_113084_2022-04-29_final
2022-05-05 10:59:12	ga_ls8c_ard_3-2-1_107069_2022-05-05_final
2022-05-07 09:15:34	ga_ls8c_ard_3-2-1_089088_2022-05-06_final
2022-06-17 10:40:13	ga_ls8c_ard_3-2-1_104067_2022-06-17_final
2022-06-22 10:59:11	ga_ls8c_ard_3-2-1_107068_2022-06-22_final
2022-06-22 10:59:35	ga_ls8c_ard_3-2-1_107069_2022-06-22_final
2022-08-09 10:59:52	ga_ls8c_ard_3-2-1_107069_2022-08-09_final
2022-08-24 11:57:55	ga_ls8c_ard_3-2-1_116075_2022-08-24_final
2022-08-31 10:22:49	ga_ls8c_ard_3-2-1_101069_2022-08-31_final
2022-09-10 10:59:34	ga_ls8c_ard_3-2-1_107068_2022-09-10_final
2022-10-14 09:16:12	ga_ls8c_ard_3-2-1_089088_2022-10-13_final
2022-10-27 11:58:01	ga_ls8c_ard_3-2-1_116075_2022-10-27_final
2022-10-28 11:00:00	ga_ls8c_ard_3-2-1_107069_2022-10-28_final
2022-12-09 11:42:59	ga_ls8c_ard_3-2-1_113084_2022-12-09_final
2022-12-12 10:28:11	ga_ls8c_ard_3-2-1_102067_2022-12-12_final
2022-12-25 11:42:50	ga_ls8c_ard_3-2-1_113084_2022-12-25_final
2023-01-09 09:23:29	ga_ls8c_ard_3-2-1_090091_2023-01-08_final
2023-01-15 11:57:42	ga_ls8c_ard_3-2-1_116075_2023-01-15_final
2023-01-25 09:23:27	ga_ls8c_ard_3-2-1_090091_2023-01-24_final
2023-01-25 10:52:45	ga_ls8c_ard_3-2-1_106067_2023-01-25_final
2023-01-26 11:42:48	ga_ls8c_ard_3-2-1_113084_2023-01-26_final
2023-02-07 10:22:39	ga_ls8c_ard_3-2-1_101069_2023-02-07_final
2023-02-16 11:57:38	ga_ls8c_ard_3-2-1_116075_2023-02-16_final
2023-02-27 11:42:30	ga_ls8c_ard_3-2-1_113084_2023-02-27_final
2023-03-02 10:27:43	ga_ls8c_ard_3-2-1_102067_2023-03-02_final
2023-03-14 09:23:03	ga_ls8c_ard_3-2-1_090091_2023-03-13_final
2023-03-21 10:59:15	ga_ls8c_ard_3-2-1_107069_2023-03-21_final
2023-03-27 10:22:07	ga_ls8c_ard_3-2-1_101069_2023-03-27_final
2023-03-30 09:22:53	ga_ls8c_ard_3-2-1_090091_2023-03-29_final
2023-04-06 10:59:03	ga_ls8c_ard_3-2-1_107069_2023-04-06_final
2023-05-03 10:39:29	ga_ls8c_ard_3-2-1_104067_2023-05-03_final
2023-05-08 10:58:45	ga_ls8c_ard_3-2-1_107069_2023-05-08_final
2023-05-14 10:21:34	ga_ls8c_ard_3-2-1_101069_2023-05-14_final
2023-05-17 10:51:39	ga_ls8c_ard_3-2-1_106067_2023-05-17_final
2023-05-21 10:26:57	ga_ls8c_ard_3-2-1_102067_2023-05-21_final
2023-05-24 10:58:16	ga_ls8c_ard_3-2-1_107068_2023-05-24_final
2023-05-30 10:21:36	ga_ls8c_ard_3-2-1_101069_2023-05-30_final
2023-06-02 10:51:42	ga_ls8c_ard_3-2-1_106067_2023-06-02_final
2023-06-08 11:56:47	ga_ls8c_ard_3-2-1_116075_2023-06-08_final
2023-07-17 10:22:00	ga_ls8c_ard_3-2-1_101069_2023-07-17_final
2023-07-21 11:42:08	ga_ls8c_ard_3-2-1_113084_2023-07-21_final
2023-08-12 10:59:14	ga_ls8c_ard_3-2-1_107069_2023-08-12_final
2023-08-14 09:15:36	ga_ls8c_ard_3-2-1_089088_2023-08-13_final
2023-08-28 10:59:22	ga_ls8c_ard_3-2-1_107069_2023-08-28_final
2023-09-19 10:22:22	ga_ls8c_ard_3-2-1_101069_2023-09-19_final
2023-09-22 09:23:09	ga_ls8c_ard_3-2-1_090091_2023-09-21_final
2023-10-05 10:22:24	ga_ls8c_ard_3-2-1_101069_2023-10-05_final
2023-10-08 09:23:13	ga_ls8c_ard_3-2-1_090091_2023-10-07_final
2023-10-26 10:40:14	ga_ls8c_ard_3-2-1_104067_2023-10-26_final
2023-11-02 09:15:55	ga_ls8c_ard_3-2-1_089088_2023-11-01_final
2023-11-09 10:52:31	ga_ls8c_ard_3-2-1_106067_2023-11-09_final
2023-11-11 10:40:10	ga_ls8c_ard_3-2-1_104067_2023-11-11_final
2023-11-27 10:40:16	ga_ls8c_ard_3-2-1_104067_2023-11-27_final
2024-01-12 09:23:13	ga_ls8c_ard_3-2-1_090091_2024-01-11_final
2024-02-03 11:57:28	ga_ls8c_ard_3-2-1_116075_2024-02-03_final
2024-02-04 10:59:27	ga_ls8c_ard_3-2-1_107069_2024-02-04_final
2024-02-06 09:15:48	ga_ls8c_ard_3-2-1_089088_2024-02-05_final
2024-02-26 10:22:19	ga_ls8c_ard_3-2-1_101069_2024-02-26_final
2024-04-02 09:59:58	ga_ls8c_ard_3-2-1_097076_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