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
2021-01-24 09:39:46	ga_ls8c_ard_3-2-0_093086_2021-01-24_final
2021-01-24 11:18:15	ga_ls8c_ard_3-2-0_109085_2021-01-24_final
2021-01-25 10:22:38	ga_ls8c_ard_3-2-0_100085_2021-01-25_final
2021-01-26 09:27:25	ga_ls8c_ard_3-2-0_091086_2021-01-25_final
2021-01-26 11:05:54	ga_ls8c_ard_3-2-0_107085_2021-01-26_final
2021-01-27 10:10:16	ga_ls8c_ard_3-2-0_098085_2021-01-27_final
2021-01-27 10:10:40	ga_ls8c_ard_3-2-0_098086_2021-01-27_final
2021-01-28 09:15:03	ga_ls8c_ard_3-2-0_089086_2021-01-27_final
2021-01-29 09:58:18	ga_ls8c_ard_3-2-0_096086_2021-01-29_final
2021-02-18 09:33:31	ga_ls8c_ard_3-2-0_092086_2021-02-18_final
2021-02-18 11:12:00	ga_ls8c_ard_3-2-0_108085_2021-02-18_final
2021-02-20 09:20:44	ga_ls8c_ard_3-2-0_090085_2021-02-19_final
2021-02-20 09:21:08	ga_ls8c_ard_3-2-0_090086_2021-02-19_final
2021-03-06 09:33:24	ga_ls8c_ard_3-2-0_092086_2021-03-06_final
2021-03-08 09:20:37	ga_ls8c_ard_3-2-0_090085_2021-03-07_final
2021-03-08 09:21:01	ga_ls8c_ard_3-2-0_090086_2021-03-07_final
2021-03-11 09:51:53	ga_ls8c_ard_3-2-0_095086_2021-03-11_final
2021-03-13 09:39:30	ga_ls8c_ard_3-2-0_093086_2021-03-13_final
2021-03-15 09:27:07	ga_ls8c_ard_3-2-0_091086_2021-03-14_final
2021-03-16 10:10:22	ga_ls8c_ard_3-2-0_098086_2021-03-16_final
2021-03-17 09:14:44	ga_ls8c_ard_3-2-0_089086_2021-03-16_final
2021-03-18 09:57:59	ga_ls8c_ard_3-2-0_096086_2021-03-18_final
2021-03-20 09:45:38	ga_ls8c_ard_3-2-0_094086_2021-03-20_final
2021-03-22 09:33:16	ga_ls8c_ard_3-2-0_092086_2021-03-22_final
2021-03-22 11:11:45	ga_ls8c_ard_3-2-0_108085_2021-03-22_final
2021-03-29 09:39:25	ga_ls8c_ard_3-2-0_093086_2021-03-29_final
2021-03-30 10:22:17	ga_ls8c_ard_3-2-0_100085_2021-03-30_final
2021-04-02 09:14:41	ga_ls8c_ard_3-2-0_089086_2021-04-01_final
2021-04-03 09:57:56	ga_ls8c_ard_3-2-0_096086_2021-04-03_final
2021-04-05 09:45:34	ga_ls8c_ard_3-2-0_094086_2021-04-05_final
2022-07-20 09:52:16	ga_ls8c_ard_3-2-1_095086_2022-07-20_final
2022-07-24 09:27:12	ga_ls8c_ard_3-2-1_091085_2022-07-23_final
2022-07-24 09:27:36	ga_ls8c_ard_3-2-1_091086_2022-07-23_final
2022-07-25 10:10:29	ga_ls8c_ard_3-2-1_098085_2022-07-25_final
2022-07-26 09:14:52	ga_ls8c_ard_3-2-1_089085_2022-07-25_final
2022-07-26 09:15:16	ga_ls8c_ard_3-2-1_089086_2022-07-25_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2022-07-27 09:58:33	ga_ls8c_ard_3-2-1_096086_2022-07-27_final
2022-07-29 09:46:12	ga_ls8c_ard_3-2-1_094086_2022-07-29_final
2022-07-29 11:24:41	ga_ls8c_ard_3-2-1_110085_2022-07-29_final
2022-07-31 09:33:28	ga_ls8c_ard_3-2-1_092085_2022-07-31_final
2022-07-31 09:33:52	ga_ls8c_ard_3-2-1_092086_2022-07-31_final
2022-08-05 09:52:27	ga_ls8c_ard_3-2-1_095086_2022-08-05_final
2022-08-07 09:39:42	ga_ls8c_ard_3-2-1_093085_2022-08-07_final
2022-08-07 09:40:06	ga_ls8c_ard_3-2-1_093086_2022-08-07_final
2022-08-09 09:27:22	ga_ls8c_ard_3-2-1_091085_2022-08-08_final
2022-08-09 09:27:46	ga_ls8c_ard_3-2-1_091086_2022-08-08_final
2022-08-10 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-08-10_final
2022-08-11 09:15:01	ga_ls8c_ard_3-2-1_089085_2022-08-10_final
2022-08-11 09:15:25	ga_ls8c_ard_3-2-1_089086_2022-08-10_final
2022-08-12 09:58:17	ga_ls8c_ard_3-2-1_096085_2022-08-12_final
2022-08-12 09:58:41	ga_ls8c_ard_3-2-1_096086_2022-08-12_final
2022-08-17 10:16:50	ga_ls8c_ard_3-2-1_099085_2022-08-17_final
2022-08-18 09:21:13	ga_ls8c_ard_3-2-1_090085_2022-08-17_final
2022-08-18 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-08-17_final
2022-08-23 09:40:10	ga_ls8c_ard_3-2-1_093086_2022-08-23_final
2022-08-25 09:27:48	ga_ls8c_ard_3-2-1_091086_2022-08-24_final
2022-08-28 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-08-28_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-08-30 09:45:57	ga_ls8c_ard_3-2-1_094085_2022-08-30_final
2022-08-30 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-08-30_final
2022-08-30 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-08-30_final
2022-09-01 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-09-01_final
2022-09-02 10:16:50	ga_ls8c_ard_3-2-1_099085_2022-09-02_final
2022-09-03 09:21:13	ga_ls8c_ard_3-2-1_090085_2022-09-02_final
2022-09-03 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-09-02_final
2022-09-04 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-09-04_final
2022-09-06 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-09-06_final
2022-09-08 09:40:13	ga_ls8c_ard_3-2-1_093086_2022-09-08_final
2022-09-11 10:10:44	ga_ls8c_ard_3-2-1_098085_2022-09-11_final
2022-09-12 09:15:07	ga_ls8c_ard_3-2-1_089085_2022-09-11_final
2022-09-12 09:15:31	ga_ls8c_ard_3-2-1_089086_2022-09-11_final
2022-09-13 09:58:23	ga_ls8c_ard_3-2-1_096085_2022-09-13_final
2022-09-13 09:58:47	ga_ls8c_ard_3-2-1_096086_2022-09-13_final
2022-09-15 09:46:02	ga_ls8c_ard_3-2-1_094085_2022-09-15_final
2022-09-15 09:46:26	ga_ls8c_ard_3-2-1_094086_2022-09-15_final
2022-09-15 11:24:56	ga_ls8c_ard_3-2-1_110085_2022-09-15_final
2022-09-17 09:34:05	ga_ls8c_ard_3-2-1_092086_2022-09-17_final
2022-09-18 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-09-18_final
2022-09-19 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-09-18_final
2022-09-19 09:21:44	ga_ls8c_ard_3-2-1_090086_2022-09-18_final
2022-09-20 10:04:36	ga_ls8c_ard_3-2-1_097085_2022-09-20_final
2022-09-22 09:52:14	ga_ls8c_ard_3-2-1_095085_2022-09-22_final
2022-09-22 09:52:38	ga_ls8c_ard_3-2-1_095086_2022-09-22_final
2022-09-24 09:39:53	ga_ls8c_ard_3-2-1_093085_2022-09-24_final
2022-09-24 09:40:17	ga_ls8c_ard_3-2-1_093086_2022-09-24_final
2022-09-27 10:10:47	ga_ls8c_ard_3-2-1_098085_2022-09-27_final
2022-09-28 09:15:33	ga_ls8c_ard_3-2-1_089086_2022-09-27_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-12 09:27:23	ga_ls8c_ard_3-2-1_091085_2022-10-11_final
2022-10-12 09:27:47	ga_ls8c_ard_3-2-1_091086_2022-10-11_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2024-02-09 09:45:55	ga_ls8c_ard_3-2-1_094086_2024-02-09_final
2024-02-16 09:51:39	ga_ls8c_ard_3-2-1_095085_2024-02-16_final
2024-02-16 09:52:03	ga_ls8c_ard_3-2-1_095086_2024-02-16_final
2024-02-18 09:39:18	ga_ls8c_ard_3-2-1_093085_2024-02-18_final
2024-02-18 09:39:42	ga_ls8c_ard_3-2-1_093086_2024-02-18_final
2024-02-20 09:26:56	ga_ls8c_ard_3-2-1_091085_2024-02-19_final
2024-02-20 09:27:20	ga_ls8c_ard_3-2-1_091086_2024-02-19_final
2024-03-12 09:45:39	ga_ls8c_ard_3-2-1_094086_2024-03-12_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