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
2018-04-17 09:21:11	ga_ls8c_ard_3-0-0_090088_2018-04-16_final
2018-04-20 09:52:03	ga_ls8c_ard_3-0-0_095088_2018-04-20_final
2018-06-07 09:51:35	ga_ls8c_ard_3-0-0_095088_2018-06-07_final
2019-12-14 09:34:33	ga_ls8c_ard_3-2-0_092088_2019-12-14_final
2020-01-10 09:15:54	ga_ls8c_ard_3-1-0_089088_2020-01-09_final
2020-01-15 09:34:25	ga_ls8c_ard_3-1-0_092088_2020-01-15_final
2020-01-26 09:15:50	ga_ls8c_ard_3-1-0_089088_2020-01-25_final
2020-03-19 09:34:04	ga_ls8c_ard_3-1-0_092088_2020-03-19_final
2020-03-21 09:21:42	ga_ls8c_ard_3-1-0_090088_2020-03-20_final
2020-03-26 09:40:11	ga_ls8c_ard_3-1-0_093088_2020-03-26_final
2020-03-28 09:27:48	ga_ls8c_ard_3-1-0_091088_2020-03-27_final
2020-04-11 09:40:03	ga_ls8c_ard_3-1-0_093088_2020-04-11_final
2020-04-13 09:27:41	ga_ls8c_ard_3-1-0_091088_2020-04-12_final
2020-04-15 09:15:18	ga_ls8c_ard_3-1-0_089088_2020-04-14_final
2020-05-22 09:33:41	ga_ls8c_ard_3-1-0_092088_2020-05-22_final
2020-05-22 09:34:05	ga_ls8c_ard_3-1-0_092089_2020-05-22_final
2020-05-24 09:21:20	ga_ls8c_ard_3-1-0_090088_2020-05-23_final
2020-05-24 09:21:44	ga_ls8c_ard_3-1-0_090089_2020-05-23_final
2021-04-14 09:40:08	ga_ls8c_ard_3-2-0_093088_2021-04-14_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-05 09:27:54	ga_ls8c_ard_3-2-1_091088_2022-05-04_final
2022-08-02 09:22:19	ga_ls8c_ard_3-2-1_090088_2022-08-01_final
2022-08-02 09:22:43	ga_ls8c_ard_3-2-1_090089_2022-08-01_final
2022-08-07 09:40:54	ga_ls8c_ard_3-2-1_093088_2022-08-07_final
2022-08-09 09:28:34	ga_ls8c_ard_3-2-1_091088_2022-08-08_final
2022-08-09 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-08-08_final
2022-08-11 09:16:13	ga_ls8c_ard_3-2-1_089088_2022-08-10_final
2022-08-11 09:16:37	ga_ls8c_ard_3-2-1_089089_2022-08-10_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-08-16 09:35:10	ga_ls8c_ard_3-2-1_092089_2022-08-16_final
2022-08-18 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-08-17_final
2022-08-18 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-08-17_final
2022-08-23 09:40:58	ga_ls8c_ard_3-2-1_093088_2022-08-23_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-08-25 09:29:00	ga_ls8c_ard_3-2-1_091089_2022-08-24_final
2022-09-01 09:34:47	ga_ls8c_ard_3-2-1_092088_2022-09-01_final
2022-09-03 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-09-02_final
2022-09-03 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-09-02_final
2022-09-08 09:41:00	ga_ls8c_ard_3-2-1_093088_2022-09-08_final
2022-09-10 09:28:40	ga_ls8c_ard_3-2-1_091088_2022-09-09_final
2022-09-10 09:29:04	ga_ls8c_ard_3-2-1_091089_2022-09-09_final
2022-09-12 09:16:19	ga_ls8c_ard_3-2-1_089088_2022-09-11_final
2022-09-17 09:34:53	ga_ls8c_ard_3-2-1_092088_2022-09-17_final
2022-09-17 09:35:17	ga_ls8c_ard_3-2-1_092089_2022-09-17_final
2022-09-19 09:22:32	ga_ls8c_ard_3-2-1_090088_2022-09-18_final
2022-09-24 09:41:05	ga_ls8c_ard_3-2-1_093088_2022-09-24_final
2022-09-26 09:28:43	ga_ls8c_ard_3-2-1_091088_2022-09-25_final
2022-09-26 09:29:07	ga_ls8c_ard_3-2-1_091089_2022-09-25_final
2022-09-28 09:16:21	ga_ls8c_ard_3-2-1_089088_2022-09-27_final
2022-10-03 09:34:52	ga_ls8c_ard_3-2-1_092088_2022-10-03_final
2022-10-03 09:35:16	ga_ls8c_ard_3-2-1_092089_2022-10-03_final
2022-10-05 09:22:30	ga_ls8c_ard_3-2-1_090088_2022-10-04_final
2022-10-05 09:22:54	ga_ls8c_ard_3-2-1_090089_2022-10-04_final
2022-10-10 09:40:59	ga_ls8c_ard_3-2-1_093088_2022-10-10_final
2022-10-12 09:28:35	ga_ls8c_ard_3-2-1_091088_2022-10-11_final
2022-10-14 09:16:12	ga_ls8c_ard_3-2-1_089088_2022-10-13_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-21 09:22:28	ga_ls8c_ard_3-2-1_090088_2022-10-20_final
2022-10-26 09:41:03	ga_ls8c_ard_3-2-1_093088_2022-10-26_final
2022-10-28 09:28:42	ga_ls8c_ard_3-2-1_091088_2022-10-27_final
2022-11-04 09:34:54	ga_ls8c_ard_3-2-1_092088_2022-11-04_final
2022-11-06 09:22:31	ga_ls8c_ard_3-2-1_090088_2022-11-05_final
2022-11-11 09:41:02	ga_ls8c_ard_3-2-1_093088_2022-11-11_final
2022-11-13 09:28:39	ga_ls8c_ard_3-2-1_091088_2022-11-12_final
2022-11-20 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-11-20_final
2022-11-22 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-11-21_final
2022-11-27 09:40:59	ga_ls8c_ard_3-2-1_093088_2022-11-27_final
2022-12-06 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-12-06_final
2022-12-17 09:16:10	ga_ls8c_ard_3-2-1_089088_2022-12-16_final
2022-12-22 09:34:38	ga_ls8c_ard_3-2-1_092088_2022-12-22_final
2022-12-24 09:22:16	ga_ls8c_ard_3-2-1_090088_2022-12-23_final
2023-01-23 09:34:36	ga_ls8c_ard_3-2-1_092088_2023-01-23_final
2023-01-25 09:22:15	ga_ls8c_ard_3-2-1_090088_2023-01-24_final
2023-05-26 09:15:01	ga_ls8c_ard_3-2-1_089088_2023-05-25_final
2023-05-26 09:15:25	ga_ls8c_ard_3-2-1_089089_2023-05-25_final
2023-05-31 09:33:34	ga_ls8c_ard_3-2-1_092088_2023-05-31_final
2023-05-31 09:33:57	ga_ls8c_ard_3-2-1_092089_2023-05-31_final
2023-06-02 09:21:12	ga_ls8c_ard_3-2-1_090088_2023-06-01_final
2023-06-07 09:39:49	ga_ls8c_ard_3-2-1_093088_2023-06-07_final
2023-06-09 09:27:29	ga_ls8c_ard_3-2-1_091088_2023-06-08_final
2023-06-09 09:27:53	ga_ls8c_ard_3-2-1_091089_2023-06-08_final
2023-06-11 09:15:08	ga_ls8c_ard_3-2-1_089088_2023-06-10_final
2023-06-11 09:15:32	ga_ls8c_ard_3-2-1_089089_2023-06-10_final
2023-06-16 09:33:43	ga_ls8c_ard_3-2-1_092088_2023-06-16_final
2023-06-16 09:34:07	ga_ls8c_ard_3-2-1_092089_2023-06-16_final
2023-06-18 09:21:21	ga_ls8c_ard_3-2-1_090088_2023-06-17_final
2023-06-18 09:21:45	ga_ls8c_ard_3-2-1_090089_2023-06-17_final
2023-06-23 09:39:54	ga_ls8c_ard_3-2-1_093088_2023-06-23_final
2023-06-25 09:27:35	ga_ls8c_ard_3-2-1_091088_2023-06-24_final
2023-06-25 09:27:59	ga_ls8c_ard_3-2-1_091089_2023-06-24_final
2023-06-27 09:15:15	ga_ls8c_ard_3-2-1_089088_2023-06-26_final
2023-06-27 09:15:39	ga_ls8c_ard_3-2-1_089089_2023-06-26_final
2023-07-02 09:33:52	ga_ls8c_ard_3-2-1_092088_2023-07-02_final
2023-07-02 09:34:16	ga_ls8c_ard_3-2-1_092089_2023-07-02_final
2023-07-04 09:21:32	ga_ls8c_ard_3-2-1_090088_2023-07-03_final
2023-07-04 09:21:56	ga_ls8c_ard_3-2-1_090089_2023-07-03_final
2023-07-09 09:40:07	ga_ls8c_ard_3-2-1_093088_2023-07-09_final
2023-07-27 09:27:52	ga_ls8c_ard_3-2-1_091088_2023-07-26_final
2023-07-27 09:28:16	ga_ls8c_ard_3-2-1_091089_2023-07-26_final
2023-07-29 09:15:31	ga_ls8c_ard_3-2-1_089088_2023-07-28_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