Search ga_ls9c_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
2021-11-07 09:23:03	ga_ls9c_ard_3-2-1_090089_2021-11-06_final.stac-item
2021-12-06 09:16:30	ga_ls9c_ard_3-2-1_089089_2021-12-05_final.stac-item
2021-12-06 09:16:54	ga_ls9c_ard_3-2-1_089090_2021-12-05_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2021-12-13 09:23:00	ga_ls9c_ard_3-2-1_090090_2021-12-12_final.stac-item
2021-12-22 09:16:24	ga_ls9c_ard_3-2-1_089089_2021-12-21_final.stac-item
2021-12-22 09:16:48	ga_ls9c_ard_3-2-1_089090_2021-12-21_final.stac-item
2021-12-29 09:22:35	ga_ls9c_ard_3-2-1_090089_2021-12-28_final.stac-item
2021-12-29 09:22:59	ga_ls9c_ard_3-2-1_090090_2021-12-28_final.stac-item
2022-01-07 09:16:22	ga_ls9c_ard_3-2-1_089089_2022-01-06_final.stac-item
2022-01-23 09:16:23	ga_ls9c_ard_3-2-1_089089_2022-01-22_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-02-08 09:16:22	ga_ls9c_ard_3-2-1_089089_2022-02-07_final.stac-item
2022-02-15 09:22:29	ga_ls9c_ard_3-2-1_090089_2022-02-14_final.stac-item
2022-02-24 09:16:12	ga_ls9c_ard_3-2-1_089089_2022-02-23_final.stac-item
2022-02-24 09:16:36	ga_ls9c_ard_3-2-1_089090_2022-02-23_final.stac-item
2022-03-12 09:16:08	ga_ls9c_ard_3-2-1_089089_2022-03-11_final.stac-item
2022-03-12 09:16:32	ga_ls9c_ard_3-2-1_089090_2022-03-11_final.stac-item
2022-03-28 09:16:03	ga_ls9c_ard_3-2-1_089089_2022-03-27_final.stac-item
2022-04-04 09:22:14	ga_ls9c_ard_3-2-1_090089_2022-04-03_final.stac-item
2022-04-13 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-04-12_final.stac-item
2022-04-20 09:22:04	ga_ls9c_ard_3-2-1_090089_2022-04-19_final.stac-item
2022-04-29 09:15:51	ga_ls9c_ard_3-2-1_089089_2022-04-28_final.stac-item
2022-05-06 09:21:59	ga_ls9c_ard_3-2-1_090089_2022-05-05_final.stac-item
2022-05-15 09:15:42	ga_ls9c_ard_3-2-1_089089_2022-05-14_final.stac-item
2022-05-22 09:21:48	ga_ls9c_ard_3-2-1_090089_2022-05-21_final.stac-item
2022-05-31 09:15:38	ga_ls9c_ard_3-2-1_089089_2022-05-30_final.stac-item
2022-05-31 09:16:02	ga_ls9c_ard_3-2-1_089090_2022-05-30_final.stac-item
2022-06-07 09:21:49	ga_ls9c_ard_3-2-1_090089_2022-06-06_final.stac-item
2022-06-07 09:22:13	ga_ls9c_ard_3-2-1_090090_2022-06-06_final.stac-item
2022-06-16 09:15:44	ga_ls9c_ard_3-2-1_089089_2022-06-15_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-06-23 09:22:07	ga_ls9c_ard_3-2-1_090089_2022-06-22_final.stac-item
2022-06-23 09:22:31	ga_ls9c_ard_3-2-1_090090_2022-06-22_final.stac-item
2022-07-02 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-07-01_final.stac-item
2022-07-02 09:16:23	ga_ls9c_ard_3-2-1_089090_2022-07-01_final.stac-item
2022-07-09 09:22:07	ga_ls9c_ard_3-2-1_090089_2022-07-08_final.stac-item
2022-07-09 09:22:31	ga_ls9c_ard_3-2-1_090090_2022-07-08_final.stac-item
2022-07-18 09:15:58	ga_ls9c_ard_3-2-1_089089_2022-07-17_final.stac-item
2022-07-25 09:22:15	ga_ls9c_ard_3-2-1_090089_2022-07-24_final.stac-item
2022-07-25 09:22:39	ga_ls9c_ard_3-2-1_090090_2022-07-24_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-10 09:22:51	ga_ls9c_ard_3-2-1_090090_2022-08-09_final.stac-item
2022-08-19 09:16:43	ga_ls9c_ard_3-2-1_089090_2022-08-18_final.stac-item
2022-08-26 09:22:55	ga_ls9c_ard_3-2-1_090090_2022-08-25_final.stac-item
2022-09-04 09:16:20	ga_ls9c_ard_3-2-1_089089_2022-09-03_final.stac-item
2022-09-04 09:16:44	ga_ls9c_ard_3-2-1_089090_2022-09-03_final.stac-item
2022-09-11 09:22:32	ga_ls9c_ard_3-2-1_090089_2022-09-10_final.stac-item
2022-09-20 09:16:26	ga_ls9c_ard_3-2-1_089089_2022-09-19_final.stac-item
2022-10-06 09:16:27	ga_ls9c_ard_3-2-1_089089_2022-10-05_final.stac-item
2022-10-06 09:16:51	ga_ls9c_ard_3-2-1_089090_2022-10-05_final.stac-item
2022-10-13 09:23:06	ga_ls9c_ard_3-2-1_090090_2022-10-12_final.stac-item
2022-10-22 09:16:34	ga_ls9c_ard_3-2-1_089089_2022-10-21_final.stac-item
2022-10-22 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-10-21_final.stac-item
2022-10-29 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-10-28_final.stac-item
2022-11-07 09:16:32	ga_ls9c_ard_3-2-1_089089_2022-11-06_final.stac-item
2022-11-07 09:16:56	ga_ls9c_ard_3-2-1_089090_2022-11-06_final.stac-item
2022-11-14 09:22:45	ga_ls9c_ard_3-2-1_090089_2022-11-13_final.stac-item
2022-11-23 09:16:34	ga_ls9c_ard_3-2-1_089089_2022-11-22_final.stac-item
2022-11-23 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-11-22_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-09 09:16:33	ga_ls9c_ard_3-2-1_089089_2022-12-08_final.stac-item
2022-12-25 09:16:30	ga_ls9c_ard_3-2-1_089089_2022-12-24_final.stac-item
2023-01-10 09:16:33	ga_ls9c_ard_3-2-1_089089_2023-01-09_final.stac-item
2023-01-17 09:22:38	ga_ls9c_ard_3-2-1_090089_2023-01-16_final.stac-item
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final.stac-item
2023-01-26 09:16:54	ga_ls9c_ard_3-2-1_089090_2023-01-25_final.stac-item
2023-02-02 09:22:46	ga_ls9c_ard_3-2-1_090089_2023-02-01_final.stac-item
2023-02-11 09:16:37	ga_ls9c_ard_3-2-1_089089_2023-02-10_final.stac-item
2023-02-27 09:16:23	ga_ls9c_ard_3-2-1_089089_2023-02-26_final.stac-item
2023-03-06 09:22:30	ga_ls9c_ard_3-2-1_090089_2023-03-05_final.stac-item
2023-03-15 09:16:16	ga_ls9c_ard_3-2-1_089089_2023-03-14_final.stac-item
2023-03-22 09:22:23	ga_ls9c_ard_3-2-1_090089_2023-03-21_final.stac-item
2023-03-31 09:16:04	ga_ls9c_ard_3-2-1_089089_2023-03-30_final.stac-item
2023-04-07 09:22:14	ga_ls9c_ard_3-2-1_090089_2023-04-06_final.stac-item
2023-04-16 09:15:57	ga_ls9c_ard_3-2-1_089089_2023-04-15_final.stac-item
2023-04-23 09:22:07	ga_ls9c_ard_3-2-1_090089_2023-04-22_final.stac-item
2023-05-02 09:15:48	ga_ls9c_ard_3-2-1_089089_2023-05-01_final.stac-item
2023-05-18 09:15:41	ga_ls9c_ard_3-2-1_089089_2023-05-17_final.stac-item
2023-06-03 09:15:34	ga_ls9c_ard_3-2-1_089089_2023-06-02_final.stac-item
2023-06-10 09:21:41	ga_ls9c_ard_3-2-1_090089_2023-06-09_final.stac-item
2023-06-19 09:15:50	ga_ls9c_ard_3-2-1_089090_2023-06-18_final.stac-item
2023-06-26 09:21:37	ga_ls9c_ard_3-2-1_090089_2023-06-25_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-07-05 09:16:02	ga_ls9c_ard_3-2-1_089090_2023-07-04_final.stac-item
2023-07-12 09:21:53	ga_ls9c_ard_3-2-1_090089_2023-07-11_final.stac-item
2023-07-12 09:22:17	ga_ls9c_ard_3-2-1_090090_2023-07-11_final.stac-item
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final.stac-item
2023-08-22 09:15:57	ga_ls9c_ard_3-2-1_089089_2023-08-21_final.stac-item
2023-09-07 09:16:07	ga_ls9c_ard_3-2-1_089089_2023-09-06_final.stac-item
2023-09-07 09:16:31	ga_ls9c_ard_3-2-1_089090_2023-09-06_final.stac-item
2023-09-14 09:22:22	ga_ls9c_ard_3-2-1_090089_2023-09-13_final.stac-item
2023-09-23 09:16:10	ga_ls9c_ard_3-2-1_089089_2023-09-22_final.stac-item
2023-09-30 09:22:19	ga_ls9c_ard_3-2-1_090089_2023-09-29_final.stac-item
2023-09-30 09:22:43	ga_ls9c_ard_3-2-1_090090_2023-09-29_final.stac-item
2023-10-09 09:16:15	ga_ls9c_ard_3-2-1_089089_2023-10-08_final.stac-item
2023-10-09 09:16:39	ga_ls9c_ard_3-2-1_089090_2023-10-08_final.stac-item
2023-10-16 09:22:31	ga_ls9c_ard_3-2-1_090089_2023-10-15_final.stac-item
2023-11-01 09:22:50	ga_ls9c_ard_3-2-1_090090_2023-10-31_final.stac-item
2023-11-17 09:22:53	ga_ls9c_ard_3-2-1_090090_2023-11-16_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 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