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
2021-11-03 09:57:21	ga_ls9c_ard_3-2-1_096081_2021-11-03_final.stac-item
2021-11-08 09:59:50	ga_ls9c_ard_3-2-1_097081_2021-11-08_final.stac-item
2021-12-05 11:47:49	ga_ls9c_ard_3-2-1_114081_2021-12-05_final.stac-item
2021-12-07 09:56:33	ga_ls9c_ard_3-2-1_096081_2021-12-07_final.stac-item
2021-12-16 09:50:16	ga_ls9c_ard_3-2-1_095081_2021-12-16_final.stac-item
2021-12-21 11:47:42	ga_ls9c_ard_3-2-1_114081_2021-12-21_final.stac-item
2021-12-23 09:56:28	ga_ls9c_ard_3-2-1_096081_2021-12-23_final.stac-item
2021-12-27 11:10:38	ga_ls9c_ard_3-2-1_108081_2021-12-27_final.stac-item
2022-01-06 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-06_final.stac-item
2022-01-08 09:56:26	ga_ls9c_ard_3-2-1_096081_2022-01-08_final.stac-item
2022-01-12 11:10:35	ga_ls9c_ard_3-2-1_108081_2022-01-12_final.stac-item
2022-01-15 10:02:35	ga_ls9c_ard_3-2-1_097081_2022-01-15_final.stac-item
2022-01-22 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-22_final.stac-item
2022-01-24 09:56:27	ga_ls9c_ard_3-2-1_096081_2022-01-24_final.stac-item
2022-01-31 10:02:38	ga_ls9c_ard_3-2-1_097081_2022-01-31_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-07 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-02-07_final.stac-item
2022-02-18 09:50:10	ga_ls9c_ard_3-2-1_095081_2022-02-18_final.stac-item
2022-02-23 11:47:32	ga_ls9c_ard_3-2-1_114081_2022-02-23_final.stac-item
2022-02-25 09:56:16	ga_ls9c_ard_3-2-1_096081_2022-02-25_final.stac-item
2022-03-01 11:10:22	ga_ls9c_ard_3-2-1_108081_2022-03-01_final.stac-item
2022-03-11 11:47:27	ga_ls9c_ard_3-2-1_114081_2022-03-11_final.stac-item
2022-03-20 10:02:21	ga_ls9c_ard_3-2-1_097081_2022-03-20_final.stac-item
2022-03-22 09:49:59	ga_ls9c_ard_3-2-1_095081_2022-03-22_final.stac-item
2022-03-27 11:47:22	ga_ls9c_ard_3-2-1_114081_2022-03-27_final.stac-item
2022-03-29 09:56:07	ga_ls9c_ard_3-2-1_096081_2022-03-29_final.stac-item
2022-04-02 11:10:17	ga_ls9c_ard_3-2-1_108081_2022-04-02_final.stac-item
2022-04-07 09:49:55	ga_ls9c_ard_3-2-1_095081_2022-04-07_final.stac-item
2022-04-12 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-04-12_final.stac-item
2022-04-28 11:47:10	ga_ls9c_ard_3-2-1_114081_2022-04-28_final.stac-item
2022-05-07 10:02:03	ga_ls9c_ard_3-2-1_097081_2022-05-07_final.stac-item
2022-05-09 09:49:40	ga_ls9c_ard_3-2-1_095081_2022-05-09_final.stac-item
2022-05-14 11:47:02	ga_ls9c_ard_3-2-1_114081_2022-05-14_final.stac-item
2022-05-16 09:55:45	ga_ls9c_ard_3-2-1_096081_2022-05-16_final.stac-item
2022-05-30 11:46:56	ga_ls9c_ard_3-2-1_114081_2022-05-30_final.stac-item
2022-06-08 10:01:53	ga_ls9c_ard_3-2-1_097081_2022-06-08_final.stac-item
2022-06-10 09:49:32	ga_ls9c_ard_3-2-1_095081_2022-06-10_final.stac-item
2022-06-15 11:47:02	ga_ls9c_ard_3-2-1_114081_2022-06-15_final.stac-item
2022-06-20 08:48:19	ga_ls9c_ard_3-2-1_085082_2022-06-19_final.stac-item
2022-06-26 09:49:53	ga_ls9c_ard_3-2-1_095081_2022-06-26_final.stac-item
2022-07-01 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-07-01_final.stac-item
2022-07-03 09:56:03	ga_ls9c_ard_3-2-1_096081_2022-07-03_final.stac-item
2022-07-12 09:49:49	ga_ls9c_ard_3-2-1_095081_2022-07-12_final.stac-item
2022-07-17 11:47:15	ga_ls9c_ard_3-2-1_114081_2022-07-17_final.stac-item
2022-07-25 10:58:21	ga_ls9c_ard_3-2-1_106082_2022-07-25_final.stac-item
2022-07-28 09:50:00	ga_ls9c_ard_3-2-1_095081_2022-07-28_final.stac-item
2022-08-02 11:47:30	ga_ls9c_ard_3-2-1_114081_2022-08-02_final.stac-item
2022-08-18 11:47:38	ga_ls9c_ard_3-2-1_114081_2022-08-18_final.stac-item
2022-08-20 09:56:24	ga_ls9c_ard_3-2-1_096081_2022-08-20_final.stac-item
2022-09-03 11:47:39	ga_ls9c_ard_3-2-1_114081_2022-09-03_final.stac-item
2022-09-05 09:56:24	ga_ls9c_ard_3-2-1_096081_2022-09-05_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-09-19 11:47:44	ga_ls9c_ard_3-2-1_114081_2022-09-19_final.stac-item
2022-09-28 10:02:43	ga_ls9c_ard_3-2-1_097081_2022-09-28_final.stac-item
2022-09-30 09:50:21	ga_ls9c_ard_3-2-1_095081_2022-09-30_final.stac-item
2022-10-05 11:47:46	ga_ls9c_ard_3-2-1_114081_2022-10-05_final.stac-item
2022-10-07 09:56:31	ga_ls9c_ard_3-2-1_096081_2022-10-07_final.stac-item
2022-10-10 08:48:59	ga_ls9c_ard_3-2-1_085082_2022-10-09_final.stac-item
2022-10-11 11:10:44	ga_ls9c_ard_3-2-1_108081_2022-10-11_final.stac-item
2022-10-14 10:02:47	ga_ls9c_ard_3-2-1_097081_2022-10-14_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-10-27 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-10-27_final.stac-item
2022-11-06 11:47:51	ga_ls9c_ard_3-2-1_114081_2022-11-06_final.stac-item
2022-11-12 11:10:48	ga_ls9c_ard_3-2-1_108081_2022-11-12_final.stac-item
2022-11-22 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-11-22_final.stac-item
2022-11-28 11:10:46	ga_ls9c_ard_3-2-1_108081_2022-11-28_final.stac-item
2022-12-08 11:47:52	ga_ls9c_ard_3-2-1_114081_2022-12-08_final.stac-item
2022-12-14 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-12-14_final.stac-item
2022-12-24 11:47:49	ga_ls9c_ard_3-2-1_114081_2022-12-24_final.stac-item
2022-12-30 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-12-30_final.stac-item
2023-01-09 11:47:52	ga_ls9c_ard_3-2-1_114081_2023-01-09_final.stac-item
2023-01-15 11:10:43	ga_ls9c_ard_3-2-1_108081_2023-01-15_final.stac-item
2023-01-25 11:47:47	ga_ls9c_ard_3-2-1_114081_2023-01-25_final.stac-item
2023-01-31 11:10:48	ga_ls9c_ard_3-2-1_108081_2023-01-31_final.stac-item
2023-02-10 11:47:56	ga_ls9c_ard_3-2-1_114081_2023-02-10_final.stac-item
2023-02-26 11:47:41	ga_ls9c_ard_3-2-1_114081_2023-02-26_final.stac-item
2023-03-14 11:47:34	ga_ls9c_ard_3-2-1_114081_2023-03-14_final.stac-item
2023-03-20 11:10:28	ga_ls9c_ard_3-2-1_108081_2023-03-20_final.stac-item
2023-03-30 11:47:22	ga_ls9c_ard_3-2-1_114081_2023-03-30_final.stac-item
2023-04-15 11:47:16	ga_ls9c_ard_3-2-1_114081_2023-04-15_final.stac-item
2023-04-21 11:10:11	ga_ls9c_ard_3-2-1_108081_2023-04-21_final.stac-item
2023-05-01 11:47:08	ga_ls9c_ard_3-2-1_114081_2023-05-01_final.stac-item
2023-05-07 11:09:59	ga_ls9c_ard_3-2-1_108081_2023-05-07_final.stac-item
2023-05-17 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-05-17_final.stac-item
2023-05-23 11:09:50	ga_ls9c_ard_3-2-1_108081_2023-05-23_final.stac-item
2023-06-02 11:46:53	ga_ls9c_ard_3-2-1_114081_2023-06-02_final.stac-item
2023-06-16 08:41:44	ga_ls9c_ard_3-2-1_084082_2023-06-15_final.stac-item
2023-06-18 11:46:45	ga_ls9c_ard_3-2-1_114081_2023-06-18_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-24 11:09:39	ga_ls9c_ard_3-2-1_108081_2023-06-24_final.stac-item
2023-07-04 11:46:56	ga_ls9c_ard_3-2-1_114081_2023-07-04_final.stac-item
2023-07-10 11:09:55	ga_ls9c_ard_3-2-1_108081_2023-07-10_final.stac-item
2023-07-18 08:42:01	ga_ls9c_ard_3-2-1_084082_2023-07-17_final.stac-item
2023-07-20 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-07-20_final.stac-item
2023-07-25 08:48:10	ga_ls9c_ard_3-2-1_085082_2023-07-24_final.stac-item
2023-09-06 11:47:25	ga_ls9c_ard_3-2-1_114081_2023-09-06_final.stac-item
2023-10-06 08:42:32	ga_ls9c_ard_3-2-1_084082_2023-10-05_final.stac-item
2023-10-22 08:42:40	ga_ls9c_ard_3-2-1_084082_2023-10-21_final.stac-item
2023-10-24 11:47:39	ga_ls9c_ard_3-2-1_114081_2023-10-24_final.stac-item
2024-02-13 11:47:42	ga_ls9c_ard_3-2-1_114081_2024-02-13_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