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
2018-05-29 09:56:36	ga_ls8c_ard_3-0-0_096085_2018-05-29_final
2018-05-29 11:35:29	ga_ls8c_ard_3-0-0_112085_2018-05-29_final
2018-05-31 09:44:13	ga_ls8c_ard_3-0-0_094085_2018-05-31_final
2018-05-31 11:23:06	ga_ls8c_ard_3-0-0_110085_2018-05-31_final
2018-07-16 09:56:57	ga_ls8c_ard_3-0-0_096085_2018-07-16_final
2018-07-16 09:57:21	ga_ls8c_ard_3-0-0_096086_2018-07-16_final
2018-07-16 11:35:50	ga_ls8c_ard_3-0-0_112085_2018-07-16_final
2018-07-18 09:44:36	ga_ls8c_ard_3-0-0_094085_2018-07-18_final
2018-07-18 09:45:00	ga_ls8c_ard_3-0-0_094086_2018-07-18_final
2018-07-18 11:23:29	ga_ls8c_ard_3-0-0_110085_2018-07-18_final
2018-08-01 09:57:04	ga_ls8c_ard_3-0-0_096085_2018-08-01_final
2018-08-01 09:57:28	ga_ls8c_ard_3-0-0_096086_2018-08-01_final
2018-08-01 11:35:57	ga_ls8c_ard_3-0-0_112085_2018-08-01_final
2018-08-03 09:44:44	ga_ls8c_ard_3-0-0_094085_2018-08-03_final
2018-08-03 09:45:08	ga_ls8c_ard_3-0-0_094086_2018-08-03_final
2018-08-03 11:23:37	ga_ls8c_ard_3-0-0_110085_2018-08-03_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-16 10:10:09	ga_ls8c_ard_3-0-0_098086_2018-09-16_final
2018-09-17 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-09-16_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-08-21 09:52:08	ga_ls8c_ard_3-2-1_095085_2022-08-21_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
2022-09-20 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
2022-09-24 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
2022-09-26 09:27:31	ga_ls8c_ard_3-2-1_091085_2022-09-25_final
2022-09-27 10:10:47	ga_ls8c_ard_3-2-1_098085_2022-09-27_final
2022-09-28 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-09-27_final
2022-09-29 09:58:25	ga_ls8c_ard_3-2-1_096085_2022-09-29_final
2022-10-01 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-10-01_final
2022-10-01 11:24:56	ga_ls8c_ard_3-2-1_110085_2022-10-01_final
2022-10-03 09:33:40	ga_ls8c_ard_3-2-1_092085_2022-10-03_final
2022-10-04 10:16:56	ga_ls8c_ard_3-2-1_099085_2022-10-04_final
2022-10-05 09:21:18	ga_ls8c_ard_3-2-1_090085_2022-10-04_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-10 09:39:47	ga_ls8c_ard_3-2-1_093085_2022-10-10_final
2022-10-19 09:33:37	ga_ls8c_ard_3-2-1_092085_2022-10-19_final
2022-10-20 10:16:53	ga_ls8c_ard_3-2-1_099085_2022-10-20_final
2022-10-21 09:21:16	ga_ls8c_ard_3-2-1_090085_2022-10-20_final
2022-10-22 10:04:32	ga_ls8c_ard_3-2-1_097085_2022-10-22_final
2022-10-26 09:39:51	ga_ls8c_ard_3-2-1_093085_2022-10-26_final
2022-10-28 09:27:30	ga_ls8c_ard_3-2-1_091085_2022-10-27_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-10-30 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-10-29_final
2022-10-31 09:58:25	ga_ls8c_ard_3-2-1_096085_2022-10-31_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-02 11:24:56	ga_ls8c_ard_3-2-1_110085_2022-11-02_final
2022-11-04 09:33:42	ga_ls8c_ard_3-2-1_092085_2022-11-04_final
2022-11-05 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-11-05_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-09 09:52:12	ga_ls8c_ard_3-2-1_095085_2022-11-09_final
2022-11-15 09:15:04	ga_ls8c_ard_3-2-1_089085_2022-11-14_final
2022-11-16 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-11-16_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-08 10:16:43	ga_ls8c_ard_3-2-1_099085_2023-01-08_final
2023-03-10 09:45:23	ga_ls8c_ard_3-2-1_094085_2023-03-10_final
2023-03-10 11:24:16	ga_ls8c_ard_3-2-1_110085_2023-03-10_final
2023-03-12 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-03-12_final
2023-03-13 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-03-13_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-15 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-03-15_final
2023-03-17 09:51:32	ga_ls8c_ard_3-2-1_095085_2023-03-17_final
2023-04-11 11:23:51	ga_ls8c_ard_3-2-1_110085_2023-04-11_final
2023-04-13 09:32:37	ga_ls8c_ard_3-2-1_092085_2023-04-13_final
2023-04-14 10:15:52	ga_ls8c_ard_3-2-1_099085_2023-04-14_final
2023-04-15 09:20:14	ga_ls8c_ard_3-2-1_090085_2023-04-14_final
2023-04-16 10:03:30	ga_ls8c_ard_3-2-1_097085_2023-04-16_final
2023-05-29 11:23:36	ga_ls8c_ard_3-2-1_110085_2023-05-29_final
2023-05-31 09:32:22	ga_ls8c_ard_3-2-1_092085_2023-05-31_final
2023-06-01 10:15:37	ga_ls8c_ard_3-2-1_099085_2023-06-01_final
2023-06-02 09:20:00	ga_ls8c_ard_3-2-1_090085_2023-06-01_final
2023-06-02 09:20:24	ga_ls8c_ard_3-2-1_090086_2023-06-01_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-16 09:45:07	ga_ls8c_ard_3-2-1_094085_2023-07-16_final
2023-07-16 11:24:00	ga_ls8c_ard_3-2-1_110085_2023-07-16_final
2023-08-08 09:51:27	ga_ls8c_ard_3-2-1_095085_2023-08-08_final
2023-08-08 09:51:51	ga_ls8c_ard_3-2-1_095086_2023-08-08_final
2023-08-12 09:26:44	ga_ls8c_ard_3-2-1_091085_2023-08-11_final
2023-08-12 09:27:08	ga_ls8c_ard_3-2-1_091086_2023-08-11_final
2023-08-13 10:10:01	ga_ls8c_ard_3-2-1_098085_2023-08-13_final
2023-08-14 09:14:25	ga_ls8c_ard_3-2-1_089085_2023-08-13_final
2023-08-21 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-08-20_final
2023-08-22 10:03:56	ga_ls8c_ard_3-2-1_097085_2023-08-22_final
2023-08-24 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-08-24_final
2023-08-24 09:51:59	ga_ls8c_ard_3-2-1_095086_2023-08-24_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-02 09:45:48	ga_ls8c_ard_3-2-1_094086_2023-09-02_final
2023-09-09 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-09-09_final
2023-09-09 09:51:59	ga_ls8c_ard_3-2-1_095086_2023-09-09_final
2023-09-11 09:39:15	ga_ls8c_ard_3-2-1_093085_2023-09-11_final
2023-09-18 11:24:22	ga_ls8c_ard_3-2-1_110085_2023-09-18_final
2023-09-20 09:33:07	ga_ls8c_ard_3-2-1_092085_2023-09-20_final
2023-10-06 09:33:10	ga_ls8c_ard_3-2-1_092085_2023-10-06_final
2023-10-07 10:16:26	ga_ls8c_ard_3-2-1_099085_2023-10-07_final
2023-10-08 09:20:50	ga_ls8c_ard_3-2-1_090085_2023-10-07_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