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
2019-01-21 09:27:05	ga_ls8c_ard_3-0-0_091086_2019-01-20_final
2019-01-21 11:05:34	ga_ls8c_ard_3-0-0_107085_2019-01-21_final
2019-01-30 09:20:28	ga_ls8c_ard_3-0-0_090085_2019-01-29_final
2019-01-30 09:20:52	ga_ls8c_ard_3-0-0_090086_2019-01-29_final
2019-01-31 10:03:43	ga_ls8c_ard_3-0-0_097085_2019-01-31_final
2019-01-31 10:04:07	ga_ls8c_ard_3-0-0_097086_2019-01-31_final
2019-02-02 09:51:21	ga_ls8c_ard_3-0-0_095085_2019-02-02_final
2019-02-02 09:51:45	ga_ls8c_ard_3-0-0_095086_2019-02-02_final
2019-02-02 11:30:15	ga_ls8c_ard_3-0-0_111085_2019-02-02_final
2019-02-22 09:26:59	ga_ls8c_ard_3-0-0_091086_2019-02-21_final
2019-03-11 10:09:45	ga_ls8c_ard_3-1-0_098085_2019-03-11_final
2019-03-11 10:10:09	ga_ls8c_ard_3-1-0_098086_2019-03-11_final
2019-03-12 09:14:07	ga_ls8c_ard_3-1-0_089085_2019-03-11_final
2019-03-12 09:14:31	ga_ls8c_ard_3-1-0_089086_2019-03-11_final
2019-03-13 09:57:23	ga_ls8c_ard_3-1-0_096085_2019-03-13_final
2019-03-13 09:57:47	ga_ls8c_ard_3-1-0_096086_2019-03-13_final
2019-03-19 09:20:17	ga_ls8c_ard_3-1-0_090085_2019-03-18_final
2019-03-19 09:20:41	ga_ls8c_ard_3-1-0_090086_2019-03-18_final
2019-03-20 10:03:56	ga_ls8c_ard_3-1-0_097086_2019-03-20_final
2019-03-26 09:26:50	ga_ls8c_ard_3-1-0_091086_2019-03-25_final
2019-03-27 10:10:06	ga_ls8c_ard_3-1-0_098086_2019-03-27_final
2019-03-28 09:14:28	ga_ls8c_ard_3-1-0_089086_2019-03-27_final
2019-03-29 09:57:43	ga_ls8c_ard_3-1-0_096086_2019-03-29_final
2019-04-27 09:26:16	ga_ls8c_ard_3-0-0_091085_2019-04-26_final
2019-04-27 09:26:40	ga_ls8c_ard_3-0-0_091086_2019-04-26_final
2019-04-27 11:05:09	ga_ls8c_ard_3-0-0_107085_2019-04-27_final
2019-04-28 10:09:32	ga_ls8c_ard_3-0-0_098085_2019-04-28_final
2019-04-28 10:09:56	ga_ls8c_ard_3-0-0_098086_2019-04-28_final
2019-04-29 09:13:55	ga_ls8c_ard_3-0-0_089085_2019-04-28_final
2019-04-29 09:14:19	ga_ls8c_ard_3-0-0_089086_2019-04-28_final
2019-04-30 09:57:11	ga_ls8c_ard_3-0-0_096085_2019-04-30_final
2019-04-30 09:57:35	ga_ls8c_ard_3-0-0_096086_2019-04-30_final
2019-04-30 11:36:04	ga_ls8c_ard_3-0-0_112085_2019-04-30_final
2019-05-13 09:26:25	ga_ls8c_ard_3-0-0_091085_2019-05-12_final
2019-05-13 09:26:49	ga_ls8c_ard_3-0-0_091086_2019-05-12_final
2019-05-13 11:05:18	ga_ls8c_ard_3-0-0_107085_2019-05-13_final
2019-05-14 10:09:41	ga_ls8c_ard_3-0-0_098085_2019-05-14_final
2019-05-14 10:10:05	ga_ls8c_ard_3-0-0_098086_2019-05-14_final
2019-05-15 09:14:05	ga_ls8c_ard_3-0-0_089085_2019-05-14_final
2019-05-15 09:14:29	ga_ls8c_ard_3-0-0_089086_2019-05-14_final
2019-05-16 09:57:21	ga_ls8c_ard_3-0-0_096085_2019-05-16_final
2019-05-16 09:57:45	ga_ls8c_ard_3-0-0_096086_2019-05-16_final
2019-05-16 11:36:14	ga_ls8c_ard_3-0-0_112085_2019-05-16_final
2019-05-29 09:26:34	ga_ls8c_ard_3-0-0_091085_2019-05-28_final
2019-05-29 09:26:58	ga_ls8c_ard_3-0-0_091086_2019-05-28_final
2019-05-29 11:05:27	ga_ls8c_ard_3-0-0_107085_2019-05-29_final
2019-05-30 10:09:51	ga_ls8c_ard_3-0-0_098085_2019-05-30_final
2019-05-30 10:10:15	ga_ls8c_ard_3-0-0_098086_2019-05-30_final
2019-05-31 09:14:14	ga_ls8c_ard_3-0-0_089085_2019-05-30_final
2019-05-31 09:14:38	ga_ls8c_ard_3-0-0_089086_2019-05-30_final
2019-06-05 09:33:12	ga_ls8c_ard_3-0-0_092086_2019-06-05_final
2019-06-05 11:11:42	ga_ls8c_ard_3-0-0_108085_2019-06-05_final
2019-06-06 10:16:05	ga_ls8c_ard_3-0-0_099085_2019-06-06_final
2019-06-07 09:20:28	ga_ls8c_ard_3-0-0_090085_2019-06-06_final
2019-06-07 09:20:52	ga_ls8c_ard_3-0-0_090086_2019-06-06_final
2019-06-08 10:03:44	ga_ls8c_ard_3-0-0_097085_2019-06-08_final
2019-06-08 10:04:08	ga_ls8c_ard_3-0-0_097086_2019-06-08_final
2020-03-01 09:45:46	ga_ls8c_ard_3-1-0_094086_2020-03-01_final
2020-03-03 09:33:24	ga_ls8c_ard_3-1-0_092086_2020-03-03_final
2020-03-08 09:51:30	ga_ls8c_ard_3-1-0_095085_2020-03-08_final
2020-03-08 09:51:54	ga_ls8c_ard_3-1-0_095086_2020-03-08_final
2020-03-10 09:39:32	ga_ls8c_ard_3-1-0_093086_2020-03-10_final
2020-03-17 09:45:39	ga_ls8c_ard_3-1-0_094086_2020-03-17_final
2020-03-19 09:33:16	ga_ls8c_ard_3-1-0_092086_2020-03-19_final
2020-03-21 09:20:54	ga_ls8c_ard_3-1-0_090086_2020-03-20_final
2020-03-22 10:04:09	ga_ls8c_ard_3-1-0_097086_2020-03-22_final
2020-03-24 09:51:46	ga_ls8c_ard_3-1-0_095086_2020-03-24_final
2020-03-26 09:39:23	ga_ls8c_ard_3-1-0_093086_2020-03-26_final
2020-03-28 09:27:00	ga_ls8c_ard_3-1-0_091086_2020-03-27_final
2020-03-31 09:57:53	ga_ls8c_ard_3-1-0_096086_2020-03-31_final
2020-04-02 09:45:30	ga_ls8c_ard_3-1-0_094086_2020-04-02_final
2020-04-04 09:33:07	ga_ls8c_ard_3-1-0_092086_2020-04-04_final
2020-04-06 09:20:45	ga_ls8c_ard_3-1-0_090086_2020-04-05_final
2020-04-09 09:51:38	ga_ls8c_ard_3-1-0_095086_2020-04-09_final
2020-04-11 09:39:15	ga_ls8c_ard_3-1-0_093086_2020-04-11_final
2020-04-22 09:20:38	ga_ls8c_ard_3-1-0_090086_2020-04-21_final
2020-04-23 10:03:53	ga_ls8c_ard_3-1-0_097086_2020-04-23_final
2020-05-02 09:57:38	ga_ls8c_ard_3-1-0_096086_2020-05-02_final
2020-05-04 09:45:15	ga_ls8c_ard_3-1-0_094086_2020-05-04_final
2020-05-06 09:32:52	ga_ls8c_ard_3-1-0_092086_2020-05-06_final
2020-05-08 09:20:29	ga_ls8c_ard_3-1-0_090086_2020-05-07_final
2020-05-13 11:17:31	ga_ls8c_ard_3-1-0_109085_2020-05-13_final
2020-05-14 10:21:54	ga_ls8c_ard_3-1-0_100085_2020-05-14_final
2020-05-15 09:26:17	ga_ls8c_ard_3-1-0_091085_2020-05-14_final
2020-05-15 09:26:41	ga_ls8c_ard_3-1-0_091086_2020-05-14_final
2020-05-15 11:05:10	ga_ls8c_ard_3-1-0_107085_2020-05-15_final
2020-05-18 09:57:12	ga_ls8c_ard_3-1-0_096085_2020-05-18_final
2020-05-18 09:57:36	ga_ls8c_ard_3-1-0_096086_2020-05-18_final
2020-05-18 11:36:05	ga_ls8c_ard_3-1-0_112085_2020-05-18_final
2020-05-20 09:44:51	ga_ls8c_ard_3-1-0_094085_2020-05-20_final
2020-05-20 09:45:15	ga_ls8c_ard_3-1-0_094086_2020-05-20_final
2020-05-20 11:23:44	ga_ls8c_ard_3-1-0_110085_2020-05-20_final
2020-05-31 09:26:21	ga_ls8c_ard_3-1-0_091085_2020-05-30_final
2020-05-31 09:26:45	ga_ls8c_ard_3-1-0_091086_2020-05-30_final
2020-05-31 11:05:14	ga_ls8c_ard_3-1-0_107085_2020-05-31_final
2020-06-05 09:44:57	ga_ls8c_ard_3-1-0_094085_2020-06-05_final
2020-06-05 09:45:21	ga_ls8c_ard_3-1-0_094086_2020-06-05_final
2020-06-05 11:23:50	ga_ls8c_ard_3-1-0_110085_2020-06-05_final
2020-06-07 09:33:01	ga_ls8c_ard_3-1-0_092086_2020-06-07_final
2020-06-14 11:17:45	ga_ls8c_ard_3-1-0_109085_2020-06-14_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