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
2021-12-06 09:12:30	ga_ls9c_ard_3-2-1_089079_2021-12-05_final.stac-item
2021-12-06 09:13:18	ga_ls9c_ard_3-2-1_089081_2021-12-05_final.stac-item
2021-12-22 09:12:24	ga_ls9c_ard_3-2-1_089079_2021-12-21_final.stac-item
2021-12-22 09:13:12	ga_ls9c_ard_3-2-1_089081_2021-12-21_final.stac-item
2021-12-31 09:07:01	ga_ls9c_ard_3-2-1_088081_2021-12-30_final.stac-item
2022-01-07 09:12:23	ga_ls9c_ard_3-2-1_089079_2022-01-06_final.stac-item
2022-01-07 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-06_final.stac-item
2022-01-23 09:12:23	ga_ls9c_ard_3-2-1_089079_2022-01-22_final.stac-item
2022-01-23 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-22_final.stac-item
2022-02-01 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-01-31_final.stac-item
2022-02-08 09:12:22	ga_ls9c_ard_3-2-1_089079_2022-02-07_final.stac-item
2022-02-08 09:13:10	ga_ls9c_ard_3-2-1_089081_2022-02-07_final.stac-item
2022-02-17 09:06:55	ga_ls9c_ard_3-2-1_088081_2022-02-16_final.stac-item
2022-02-24 09:12:13	ga_ls9c_ard_3-2-1_089079_2022-02-23_final.stac-item
2022-02-24 09:13:01	ga_ls9c_ard_3-2-1_089081_2022-02-23_final.stac-item
2022-03-05 09:06:45	ga_ls9c_ard_3-2-1_088081_2022-03-04_final.stac-item
2022-03-12 09:12:09	ga_ls9c_ard_3-2-1_089079_2022-03-11_final.stac-item
2022-03-12 09:12:56	ga_ls9c_ard_3-2-1_089081_2022-03-11_final.stac-item
2022-03-21 09:06:43	ga_ls9c_ard_3-2-1_088081_2022-03-20_final.stac-item
2022-03-28 09:12:03	ga_ls9c_ard_3-2-1_089079_2022-03-27_final.stac-item
2022-03-28 09:12:51	ga_ls9c_ard_3-2-1_089081_2022-03-27_final.stac-item
2022-04-06 09:06:40	ga_ls9c_ard_3-2-1_088081_2022-04-05_final.stac-item
2022-04-13 09:11:59	ga_ls9c_ard_3-2-1_089079_2022-04-12_final.stac-item
2022-04-13 09:12:47	ga_ls9c_ard_3-2-1_089081_2022-04-12_final.stac-item
2022-04-22 09:06:29	ga_ls9c_ard_3-2-1_088081_2022-04-21_final.stac-item
2022-04-29 09:11:52	ga_ls9c_ard_3-2-1_089079_2022-04-28_final.stac-item
2022-05-08 09:06:25	ga_ls9c_ard_3-2-1_088081_2022-05-07_final.stac-item
2022-05-15 09:11:43	ga_ls9c_ard_3-2-1_089079_2022-05-14_final.stac-item
2022-05-15 09:12:30	ga_ls9c_ard_3-2-1_089081_2022-05-14_final.stac-item
2022-05-24 09:06:15	ga_ls9c_ard_3-2-1_088081_2022-05-23_final.stac-item
2022-05-31 09:11:38	ga_ls9c_ard_3-2-1_089079_2022-05-30_final.stac-item
2022-05-31 09:12:26	ga_ls9c_ard_3-2-1_089081_2022-05-30_final.stac-item
2022-06-09 09:06:16	ga_ls9c_ard_3-2-1_088081_2022-06-08_final.stac-item
2022-06-16 09:11:45	ga_ls9c_ard_3-2-1_089079_2022-06-15_final.stac-item
2022-06-16 09:12:33	ga_ls9c_ard_3-2-1_089081_2022-06-15_final.stac-item
2022-06-25 09:06:37	ga_ls9c_ard_3-2-1_088081_2022-06-24_final.stac-item
2022-07-02 09:11:59	ga_ls9c_ard_3-2-1_089079_2022-07-01_final.stac-item
2022-07-02 09:12:47	ga_ls9c_ard_3-2-1_089081_2022-07-01_final.stac-item
2022-07-11 09:06:33	ga_ls9c_ard_3-2-1_088081_2022-07-10_final.stac-item
2022-07-18 09:11:58	ga_ls9c_ard_3-2-1_089079_2022-07-17_final.stac-item
2022-07-18 09:12:46	ga_ls9c_ard_3-2-1_089081_2022-07-17_final.stac-item
2022-07-27 09:06:44	ga_ls9c_ard_3-2-1_088081_2022-07-26_final.stac-item
2022-08-03 09:12:12	ga_ls9c_ard_3-2-1_089079_2022-08-02_final.stac-item
2022-08-03 09:13:00	ga_ls9c_ard_3-2-1_089081_2022-08-02_final.stac-item
2022-08-12 09:06:54	ga_ls9c_ard_3-2-1_088081_2022-08-11_final.stac-item
2022-08-19 09:13:08	ga_ls9c_ard_3-2-1_089081_2022-08-18_final.stac-item
2022-08-28 09:06:58	ga_ls9c_ard_3-2-1_088081_2022-08-27_final.stac-item
2022-09-04 09:12:21	ga_ls9c_ard_3-2-1_089079_2022-09-03_final.stac-item
2022-09-04 09:13:09	ga_ls9c_ard_3-2-1_089081_2022-09-03_final.stac-item
2022-09-13 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-09-12_final.stac-item
2022-09-20 09:12:27	ga_ls9c_ard_3-2-1_089079_2022-09-19_final.stac-item
2022-09-20 09:13:14	ga_ls9c_ard_3-2-1_089081_2022-09-19_final.stac-item
2022-09-29 09:07:06	ga_ls9c_ard_3-2-1_088081_2022-09-28_final.stac-item
2022-10-06 09:12:28	ga_ls9c_ard_3-2-1_089079_2022-10-05_final.stac-item
2022-10-06 09:13:15	ga_ls9c_ard_3-2-1_089081_2022-10-05_final.stac-item
2022-10-15 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-14_final.stac-item
2022-10-22 09:12:34	ga_ls9c_ard_3-2-1_089079_2022-10-21_final.stac-item
2022-10-22 09:13:22	ga_ls9c_ard_3-2-1_089081_2022-10-21_final.stac-item
2022-10-31 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-30_final.stac-item
2022-11-07 09:12:33	ga_ls9c_ard_3-2-1_089079_2022-11-06_final.stac-item
2022-11-07 09:13:21	ga_ls9c_ard_3-2-1_089081_2022-11-06_final.stac-item
2022-11-16 09:07:12	ga_ls9c_ard_3-2-1_088081_2022-11-15_final.stac-item
2022-11-23 09:12:35	ga_ls9c_ard_3-2-1_089079_2022-11-22_final.stac-item
2022-11-23 09:13:22	ga_ls9c_ard_3-2-1_089081_2022-11-22_final.stac-item
2022-12-02 09:07:08	ga_ls9c_ard_3-2-1_088081_2022-12-01_final.stac-item
2022-12-09 09:12:34	ga_ls9c_ard_3-2-1_089079_2022-12-08_final.stac-item
2022-12-09 09:13:22	ga_ls9c_ard_3-2-1_089081_2022-12-08_final.stac-item
2022-12-18 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-12-17_final.stac-item
2022-12-25 09:12:31	ga_ls9c_ard_3-2-1_089079_2022-12-24_final.stac-item
2022-12-25 09:13:19	ga_ls9c_ard_3-2-1_089081_2022-12-24_final.stac-item
2023-01-10 09:12:33	ga_ls9c_ard_3-2-1_089079_2023-01-09_final.stac-item
2023-01-10 09:13:21	ga_ls9c_ard_3-2-1_089081_2023-01-09_final.stac-item
2023-01-19 09:07:03	ga_ls9c_ard_3-2-1_088081_2023-01-18_final.stac-item
2023-01-26 09:12:30	ga_ls9c_ard_3-2-1_089079_2023-01-25_final.stac-item
2023-01-26 09:13:18	ga_ls9c_ard_3-2-1_089081_2023-01-25_final.stac-item
2023-02-04 09:07:14	ga_ls9c_ard_3-2-1_088081_2023-02-03_final.stac-item
2023-02-11 09:12:37	ga_ls9c_ard_3-2-1_089079_2023-02-10_final.stac-item
2023-02-11 09:13:25	ga_ls9c_ard_3-2-1_089081_2023-02-10_final.stac-item
2023-02-20 09:07:06	ga_ls9c_ard_3-2-1_088081_2023-02-19_final.stac-item
2023-02-27 09:13:11	ga_ls9c_ard_3-2-1_089081_2023-02-26_final.stac-item
2023-03-15 09:13:04	ga_ls9c_ard_3-2-1_089081_2023-03-14_final.stac-item
2023-03-24 09:06:48	ga_ls9c_ard_3-2-1_088081_2023-03-23_final.stac-item
2023-03-31 09:12:52	ga_ls9c_ard_3-2-1_089081_2023-03-30_final.stac-item
2023-04-09 09:06:39	ga_ls9c_ard_3-2-1_088081_2023-04-08_final.stac-item
2023-04-16 09:11:58	ga_ls9c_ard_3-2-1_089079_2023-04-15_final.stac-item
2023-04-16 09:12:46	ga_ls9c_ard_3-2-1_089081_2023-04-15_final.stac-item
2023-04-25 09:06:33	ga_ls9c_ard_3-2-1_088081_2023-04-24_final.stac-item
2023-05-02 09:11:49	ga_ls9c_ard_3-2-1_089079_2023-05-01_final.stac-item
2023-05-02 09:12:37	ga_ls9c_ard_3-2-1_089081_2023-05-01_final.stac-item
2023-05-11 09:06:23	ga_ls9c_ard_3-2-1_088081_2023-05-10_final.stac-item
2023-05-18 09:11:42	ga_ls9c_ard_3-2-1_089079_2023-05-17_final.stac-item
2023-05-18 09:12:30	ga_ls9c_ard_3-2-1_089081_2023-05-17_final.stac-item
2023-05-27 09:06:13	ga_ls9c_ard_3-2-1_088081_2023-05-26_final.stac-item
2023-06-03 09:11:35	ga_ls9c_ard_3-2-1_089079_2023-06-02_final.stac-item
2023-06-03 09:12:23	ga_ls9c_ard_3-2-1_089081_2023-06-02_final.stac-item
2023-06-12 09:06:06	ga_ls9c_ard_3-2-1_088081_2023-06-11_final.stac-item
2023-06-19 09:11:26	ga_ls9c_ard_3-2-1_089079_2023-06-18_final.stac-item
2023-06-19 09:12:14	ga_ls9c_ard_3-2-1_089081_2023-06-18_final.stac-item
2023-06-28 09:06:07	ga_ls9c_ard_3-2-1_088081_2023-06-27_final.stac-item
2023-07-05 09:11:38	ga_ls9c_ard_3-2-1_089079_2023-07-04_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years