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

69 results

Time (local)	Label
2022-01-13 10:59:12	ga_ls8c_ard_3-2-1_107068_2022-01-13_final
2022-01-23 11:42:37	ga_ls8c_ard_3-2-1_113084_2022-01-23_final
2022-01-24 10:40:12	ga_ls8c_ard_3-2-1_104067_2022-01-24_final
2022-01-28 11:57:31	ga_ls8c_ard_3-2-1_116075_2022-01-28_final
2022-02-07 10:52:31	ga_ls8c_ard_3-2-1_106067_2022-02-07_final
2022-02-16 09:15:46	ga_ls8c_ard_3-2-1_089088_2022-02-15_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
2022-03-29 10:39:47	ga_ls8c_ard_3-2-1_104067_2022-03-29_final
2022-04-09 10:22:05	ga_ls8c_ard_3-2-1_101069_2022-04-09_final
2022-04-29 11:42:11	ga_ls8c_ard_3-2-1_113084_2022-04-29_final
2022-05-11 10:22:11	ga_ls8c_ard_3-2-1_101069_2022-05-11_final
2022-05-14 10:52:19	ga_ls8c_ard_3-2-1_106067_2022-05-14_final
2022-05-16 10:39:58	ga_ls8c_ard_3-2-1_104067_2022-05-16_final
2022-05-23 09:15:39	ga_ls8c_ard_3-2-1_089088_2022-05-22_final
2022-06-03 10:27:42	ga_ls8c_ard_3-2-1_102067_2022-06-03_final
2022-06-19 10:27:52	ga_ls8c_ard_3-2-1_102067_2022-06-19_final
2022-07-01 09:23:20	ga_ls8c_ard_3-2-1_090091_2022-06-30_final
2022-07-24 10:59:42	ga_ls8c_ard_3-2-1_107069_2022-07-24_final
2022-07-26 09:16:04	ga_ls8c_ard_3-2-1_089088_2022-07-25_final
2022-08-11 09:16:13	ga_ls8c_ard_3-2-1_089088_2022-08-10_final
2022-08-27 09:16:15	ga_ls8c_ard_3-2-1_089088_2022-08-26_final
2022-09-03 09:23:37	ga_ls8c_ard_3-2-1_090091_2022-09-02_final
2022-09-09 11:57:59	ga_ls8c_ard_3-2-1_116075_2022-09-09_final
2022-09-21 10:40:41	ga_ls8c_ard_3-2-1_104067_2022-09-21_final
2022-10-02 10:22:55	ga_ls8c_ard_3-2-1_101069_2022-10-02_final
2022-10-14 09:16:12	ga_ls8c_ard_3-2-1_089088_2022-10-13_final
2022-10-25 10:28:17	ga_ls8c_ard_3-2-1_102067_2022-10-25_final
2022-10-27 11:58:01	ga_ls8c_ard_3-2-1_116075_2022-10-27_final
2022-11-28 11:57:57	ga_ls8c_ard_3-2-1_116075_2022-11-28_final
2022-12-08 09:23:38	ga_ls8c_ard_3-2-1_090091_2022-12-07_final
2022-12-09 11:42:59	ga_ls8c_ard_3-2-1_113084_2022-12-09_final
2022-12-21 10:22:41	ga_ls8c_ard_3-2-1_101069_2022-12-21_final
2022-12-24 09:23:28	ga_ls8c_ard_3-2-1_090091_2022-12-23_final
2022-12-25 11:42:50	ga_ls8c_ard_3-2-1_113084_2022-12-25_final
2023-02-01 10:59:45	ga_ls8c_ard_3-2-1_107069_2023-02-01_final
2023-02-17 10:59:12	ga_ls8c_ard_3-2-1_107068_2023-02-17_final
2023-02-26 09:23:08	ga_ls8c_ard_3-2-1_090091_2023-02-25_final
2023-02-26 10:52:27	ga_ls8c_ard_3-2-1_106067_2023-02-26_final
2023-04-12 10:21:51	ga_ls8c_ard_3-2-1_101069_2023-04-12_final
2023-04-17 10:39:34	ga_ls8c_ard_3-2-1_104067_2023-04-17_final
2023-05-23 11:56:41	ga_ls8c_ard_3-2-1_116075_2023-05-23_final
2023-06-19 11:41:54	ga_ls8c_ard_3-2-1_113084_2023-06-19_final
2023-07-04 10:52:02	ga_ls8c_ard_3-2-1_106067_2023-07-04_final
2023-07-05 11:42:05	ga_ls8c_ard_3-2-1_113084_2023-07-05_final
2023-07-06 10:39:42	ga_ls8c_ard_3-2-1_104067_2023-07-06_final
2023-07-22 10:39:45	ga_ls8c_ard_3-2-1_104067_2023-07-22_final
2023-08-21 10:52:22	ga_ls8c_ard_3-2-1_106067_2023-08-21_final
2023-09-03 10:22:16	ga_ls8c_ard_3-2-1_101069_2023-09-03_final
2023-10-09 11:42:35	ga_ls8c_ard_3-2-1_113084_2023-10-09_final
2023-10-30 11:57:36	ga_ls8c_ard_3-2-1_116075_2023-10-30_final
2023-10-31 10:59:35	ga_ls8c_ard_3-2-1_107069_2023-10-31_final
2023-11-13 10:27:50	ga_ls8c_ard_3-2-1_102067_2023-11-13_final
2023-12-08 10:22:23	ga_ls8c_ard_3-2-1_101069_2023-12-08_final
2023-12-18 10:59:35	ga_ls8c_ard_3-2-1_107069_2023-12-18_final
2023-12-24 10:22:30	ga_ls8c_ard_3-2-1_101069_2023-12-24_final
2023-12-28 11:42:37	ga_ls8c_ard_3-2-1_113084_2023-12-28_final
2024-01-03 10:59:28	ga_ls8c_ard_3-2-1_107069_2024-01-03_final
2024-01-05 09:15:46	ga_ls8c_ard_3-2-1_089088_2024-01-04_final
2024-01-09 10:22:24	ga_ls8c_ard_3-2-1_101069_2024-01-09_final
2024-01-18 11:57:30	ga_ls8c_ard_3-2-1_116075_2024-01-18_final
2024-01-28 09:23:06	ga_ls8c_ard_3-2-1_090091_2024-01-27_final
2024-01-28 10:52:24	ga_ls8c_ard_3-2-1_106067_2024-01-28_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
2024-02-29 10:52:23	ga_ls8c_ard_3-2-1_106067_2024-02-29_final
2024-04-02 09:59:34	ga_ls8c_ard_3-2-1_097075_2024-04-02_final
2024-04-02 09:59:58	ga_ls8c_ard_3-2-1_097076_2024-04-02_final
2024-04-02 10:02:22	ga_ls8c_ard_3-2-1_097082_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years