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
2021-11-08 11:36:54	ga_ls9c_ard_3-2-1_113077_2021-11-08_final.stac-item
2021-12-06 10:50:59	ga_ls9c_ard_3-2-1_105078_2021-12-06_final.stac-item
2021-12-07 11:33:51	ga_ls9c_ard_3-2-1_112077_2021-12-07_final.stac-item
2021-12-09 11:21:28	ga_ls9c_ard_3-2-1_110077_2021-12-09_final.stac-item
2021-12-16 11:27:33	ga_ls9c_ard_3-2-1_111077_2021-12-16_final.stac-item
2021-12-22 10:50:53	ga_ls9c_ard_3-2-1_105078_2021-12-22_final.stac-item
2021-12-29 10:57:04	ga_ls9c_ard_3-2-1_106078_2021-12-29_final.stac-item
2022-01-01 11:27:34	ga_ls9c_ard_3-2-1_111077_2022-01-01_final.stac-item
2022-01-07 10:50:52	ga_ls9c_ard_3-2-1_105078_2022-01-07_final.stac-item
2022-01-10 11:21:45	ga_ls9c_ard_3-2-1_110078_2022-01-10_final.stac-item
2022-01-17 11:27:56	ga_ls9c_ard_3-2-1_111078_2022-01-17_final.stac-item
2022-01-24 11:33:44	ga_ls9c_ard_3-2-1_112077_2022-01-24_final.stac-item
2022-01-30 10:57:03	ga_ls9c_ard_3-2-1_106078_2022-01-30_final.stac-item
2022-02-08 10:50:51	ga_ls9c_ard_3-2-1_105078_2022-02-08_final.stac-item
2022-02-11 11:21:44	ga_ls9c_ard_3-2-1_110078_2022-02-11_final.stac-item
2022-02-15 10:56:59	ga_ls9c_ard_3-2-1_106078_2022-02-15_final.stac-item
2022-03-03 10:56:48	ga_ls9c_ard_3-2-1_106078_2022-03-03_final.stac-item
2022-03-12 10:50:38	ga_ls9c_ard_3-2-1_105078_2022-03-12_final.stac-item
2022-03-22 11:27:40	ga_ls9c_ard_3-2-1_111078_2022-03-22_final.stac-item
2022-03-28 10:50:32	ga_ls9c_ard_3-2-1_105078_2022-03-28_final.stac-item
2022-04-07 11:27:36	ga_ls9c_ard_3-2-1_111078_2022-04-07_final.stac-item
2022-04-13 10:50:28	ga_ls9c_ard_3-2-1_105078_2022-04-13_final.stac-item
2022-04-16 11:21:20	ga_ls9c_ard_3-2-1_110078_2022-04-16_final.stac-item
2022-05-06 10:56:29	ga_ls9c_ard_3-2-1_106078_2022-05-06_final.stac-item
2022-05-09 11:27:21	ga_ls9c_ard_3-2-1_111078_2022-05-09_final.stac-item
2022-05-15 10:50:12	ga_ls9c_ard_3-2-1_105078_2022-05-15_final.stac-item
2022-05-18 11:21:03	ga_ls9c_ard_3-2-1_110078_2022-05-18_final.stac-item
2022-05-22 10:56:17	ga_ls9c_ard_3-2-1_106078_2022-05-22_final.stac-item
2022-05-25 11:27:11	ga_ls9c_ard_3-2-1_111078_2022-05-25_final.stac-item
2022-06-01 11:32:59	ga_ls9c_ard_3-2-1_112077_2022-06-01_final.stac-item
2022-06-10 11:26:50	ga_ls9c_ard_3-2-1_111077_2022-06-10_final.stac-item
2022-06-17 11:33:06	ga_ls9c_ard_3-2-1_112077_2022-06-17_final.stac-item
2022-06-26 11:27:34	ga_ls9c_ard_3-2-1_111078_2022-06-26_final.stac-item
2022-07-02 10:50:28	ga_ls9c_ard_3-2-1_105078_2022-07-02_final.stac-item
2022-07-03 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-03_final.stac-item
2022-07-12 11:27:06	ga_ls9c_ard_3-2-1_111077_2022-07-12_final.stac-item
2022-07-19 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-19_final.stac-item
2022-07-21 11:21:01	ga_ls9c_ard_3-2-1_110077_2022-07-21_final.stac-item
2022-07-25 10:56:45	ga_ls9c_ard_3-2-1_106078_2022-07-25_final.stac-item
2022-07-28 11:27:18	ga_ls9c_ard_3-2-1_111077_2022-07-28_final.stac-item
2022-08-04 11:33:34	ga_ls9c_ard_3-2-1_112077_2022-08-04_final.stac-item
2022-08-06 11:21:13	ga_ls9c_ard_3-2-1_110077_2022-08-06_final.stac-item
2022-08-06 11:21:37	ga_ls9c_ard_3-2-1_110078_2022-08-06_final.stac-item
2022-08-13 11:27:52	ga_ls9c_ard_3-2-1_111078_2022-08-13_final.stac-item
2022-08-19 10:50:49	ga_ls9c_ard_3-2-1_105078_2022-08-19_final.stac-item
2022-08-20 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-08-20_final.stac-item
2022-08-22 11:21:20	ga_ls9c_ard_3-2-1_110077_2022-08-22_final.stac-item
2022-08-26 10:57:01	ga_ls9c_ard_3-2-1_106078_2022-08-26_final.stac-item
2022-09-05 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-09-05_final.stac-item
2022-09-21 11:33:48	ga_ls9c_ard_3-2-1_112077_2022-09-21_final.stac-item
2022-09-23 11:21:27	ga_ls9c_ard_3-2-1_110077_2022-09-23_final.stac-item
2022-09-27 10:57:08	ga_ls9c_ard_3-2-1_106078_2022-09-27_final.stac-item
2022-09-30 11:27:39	ga_ls9c_ard_3-2-1_111077_2022-09-30_final.stac-item
2022-10-06 10:50:57	ga_ls9c_ard_3-2-1_105078_2022-10-06_final.stac-item
2022-10-07 11:33:49	ga_ls9c_ard_3-2-1_112077_2022-10-07_final.stac-item
2022-10-09 11:21:29	ga_ls9c_ard_3-2-1_110077_2022-10-09_final.stac-item
2022-10-09 11:21:53	ga_ls9c_ard_3-2-1_110078_2022-10-09_final.stac-item
2022-10-23 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-10-23_final.stac-item
2022-11-01 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-11-01_final.stac-item
2022-11-01 11:28:06	ga_ls9c_ard_3-2-1_111078_2022-11-01_final.stac-item
2022-11-08 11:33:54	ga_ls9c_ard_3-2-1_112077_2022-11-08_final.stac-item
2022-11-10 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-11-10_final.stac-item
2022-11-17 11:27:45	ga_ls9c_ard_3-2-1_111077_2022-11-17_final.stac-item
2022-11-17 11:28:09	ga_ls9c_ard_3-2-1_111078_2022-11-17_final.stac-item
2022-11-24 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-11-24_final.stac-item
2022-11-26 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-11-26_final.stac-item
2022-12-03 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-12-03_final.stac-item
2022-12-10 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-12-10_final.stac-item
2023-01-13 11:21:55	ga_ls9c_ard_3-2-1_110078_2023-01-13_final.stac-item
2023-01-29 11:21:56	ga_ls9c_ard_3-2-1_110078_2023-01-29_final.stac-item
2023-02-05 11:28:11	ga_ls9c_ard_3-2-1_111078_2023-02-05_final.stac-item
2023-02-21 11:28:01	ga_ls9c_ard_3-2-1_111078_2023-02-21_final.stac-item
2023-04-10 11:27:35	ga_ls9c_ard_3-2-1_111078_2023-04-10_final.stac-item
2023-05-12 11:27:19	ga_ls9c_ard_3-2-1_111078_2023-05-12_final.stac-item
2023-05-28 11:27:09	ga_ls9c_ard_3-2-1_111078_2023-05-28_final.stac-item
2023-06-06 11:20:57	ga_ls9c_ard_3-2-1_110078_2023-06-06_final.stac-item
2023-06-20 11:32:47	ga_ls9c_ard_3-2-1_112077_2023-06-20_final.stac-item
2023-06-29 11:26:42	ga_ls9c_ard_3-2-1_111077_2023-06-29_final.stac-item
2023-06-29 11:27:06	ga_ls9c_ard_3-2-1_111078_2023-06-29_final.stac-item
2023-07-08 11:20:40	ga_ls9c_ard_3-2-1_110077_2023-07-08_final.stac-item
2023-07-15 11:26:53	ga_ls9c_ard_3-2-1_111077_2023-07-15_final.stac-item
2023-07-22 11:33:03	ga_ls9c_ard_3-2-1_112077_2023-07-22_final.stac-item
2023-07-24 11:20:41	ga_ls9c_ard_3-2-1_110077_2023-07-24_final.stac-item
2023-07-31 11:26:58	ga_ls9c_ard_3-2-1_111077_2023-07-31_final.stac-item
2023-08-16 11:27:03	ga_ls9c_ard_3-2-1_111077_2023-08-16_final.stac-item
2023-08-25 11:20:59	ga_ls9c_ard_3-2-1_110077_2023-08-25_final.stac-item
2023-09-08 11:33:29	ga_ls9c_ard_3-2-1_112077_2023-09-08_final.stac-item
2023-09-17 11:27:22	ga_ls9c_ard_3-2-1_111077_2023-09-17_final.stac-item
2023-10-03 11:27:22	ga_ls9c_ard_3-2-1_111077_2023-10-03_final.stac-item
2023-10-19 11:27:32	ga_ls9c_ard_3-2-1_111077_2023-10-19_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-28 11:21:18	ga_ls9c_ard_3-2-1_110077_2023-10-28_final.stac-item
2023-11-04 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-11-04_final.stac-item
2023-11-20 11:27:31	ga_ls9c_ard_3-2-1_111077_2023-11-20_final.stac-item
2023-12-22 11:27:38	ga_ls9c_ard_3-2-1_111077_2023-12-22_final.stac-item
2023-12-31 11:21:24	ga_ls9c_ard_3-2-1_110077_2023-12-31_final.stac-item
2024-02-08 11:27:36	ga_ls9c_ard_3-2-1_111077_2024-02-08_final.stac-item
2024-02-17 11:21:19	ga_ls9c_ard_3-2-1_110077_2024-02-17_final.stac-item
2024-02-24 11:27:22	ga_ls9c_ard_3-2-1_111077_2024-02-24_final.stac-item
2024-03-11 11:27:27	ga_ls9c_ard_3-2-1_111077_2024-03-11_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