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
2021-12-13 10:53:06	ga_ls9c_ard_3-2-1_106068_2021-12-13_final.stac-item
2021-12-13 10:53:30	ga_ls9c_ard_3-2-1_106069_2021-12-13_final.stac-item
2021-12-22 10:47:18	ga_ls9c_ard_3-2-1_105069_2021-12-22_final.stac-item
2021-12-22 10:47:42	ga_ls9c_ard_3-2-1_105070_2021-12-22_final.stac-item
2021-12-29 10:53:29	ga_ls9c_ard_3-2-1_106069_2021-12-29_final.stac-item
2022-01-07 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-01-07_final.stac-item
2022-01-07 10:47:40	ga_ls9c_ard_3-2-1_105070_2022-01-07_final.stac-item
2022-01-14 10:53:25	ga_ls9c_ard_3-2-1_106069_2022-01-14_final.stac-item
2022-01-23 10:47:17	ga_ls9c_ard_3-2-1_105069_2022-01-23_final.stac-item
2022-01-23 10:47:41	ga_ls9c_ard_3-2-1_105070_2022-01-23_final.stac-item
2022-01-23 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-23_final.stac-item
2022-01-30 10:53:04	ga_ls9c_ard_3-2-1_106068_2022-01-30_final.stac-item
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final.stac-item
2022-02-08 10:47:16	ga_ls9c_ard_3-2-1_105069_2022-02-08_final.stac-item
2022-02-15 10:53:23	ga_ls9c_ard_3-2-1_106069_2022-02-15_final.stac-item
2022-03-03 10:52:48	ga_ls9c_ard_3-2-1_106068_2022-03-03_final.stac-item
2022-03-03 10:53:12	ga_ls9c_ard_3-2-1_106069_2022-03-03_final.stac-item
2022-03-12 10:46:38	ga_ls9c_ard_3-2-1_105068_2022-03-12_final.stac-item
2022-03-19 10:52:47	ga_ls9c_ard_3-2-1_106068_2022-03-19_final.stac-item
2022-03-19 10:53:11	ga_ls9c_ard_3-2-1_106069_2022-03-19_final.stac-item
2022-03-28 10:46:33	ga_ls9c_ard_3-2-1_105068_2022-03-28_final.stac-item
2022-03-28 10:46:57	ga_ls9c_ard_3-2-1_105069_2022-03-28_final.stac-item
2022-04-04 10:52:44	ga_ls9c_ard_3-2-1_106068_2022-04-04_final.stac-item
2022-04-13 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-04-13_final.stac-item
2022-04-13 10:47:41	ga_ls9c_ard_3-2-1_105071_2022-04-13_final.stac-item
2022-04-20 10:52:34	ga_ls9c_ard_3-2-1_106068_2022-04-20_final.stac-item
2022-04-20 10:52:58	ga_ls9c_ard_3-2-1_106069_2022-04-20_final.stac-item
2022-04-29 10:46:45	ga_ls9c_ard_3-2-1_105069_2022-04-29_final.stac-item
2022-04-29 10:47:09	ga_ls9c_ard_3-2-1_105070_2022-04-29_final.stac-item
2022-05-06 10:52:53	ga_ls9c_ard_3-2-1_106069_2022-05-06_final.stac-item
2022-05-22 10:52:42	ga_ls9c_ard_3-2-1_106069_2022-05-22_final.stac-item
2022-05-31 10:46:08	ga_ls9c_ard_3-2-1_105068_2022-05-31_final.stac-item
2022-05-31 10:46:56	ga_ls9c_ard_3-2-1_105070_2022-05-31_final.stac-item
2022-06-07 10:52:43	ga_ls9c_ard_3-2-1_106069_2022-06-07_final.stac-item
2022-06-16 10:46:38	ga_ls9c_ard_3-2-1_105069_2022-06-16_final.stac-item
2022-07-02 10:46:29	ga_ls9c_ard_3-2-1_105068_2022-07-02_final.stac-item
2022-07-02 10:46:53	ga_ls9c_ard_3-2-1_105069_2022-07-02_final.stac-item
2022-07-02 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-07-02_final.stac-item
2022-07-09 10:53:02	ga_ls9c_ard_3-2-1_106069_2022-07-09_final.stac-item
2022-07-18 10:46:52	ga_ls9c_ard_3-2-1_105069_2022-07-18_final.stac-item
2022-07-25 10:52:46	ga_ls9c_ard_3-2-1_106068_2022-07-25_final.stac-item
2022-07-25 10:53:10	ga_ls9c_ard_3-2-1_106069_2022-07-25_final.stac-item
2022-08-03 10:47:30	ga_ls9c_ard_3-2-1_105070_2022-08-03_final.stac-item
2022-08-10 10:53:21	ga_ls9c_ard_3-2-1_106069_2022-08-10_final.stac-item
2022-08-19 10:47:37	ga_ls9c_ard_3-2-1_105070_2022-08-19_final.stac-item
2022-09-04 10:47:14	ga_ls9c_ard_3-2-1_105069_2022-09-04_final.stac-item
2022-09-04 10:47:38	ga_ls9c_ard_3-2-1_105070_2022-09-04_final.stac-item
2022-09-11 10:53:02	ga_ls9c_ard_3-2-1_106068_2022-09-11_final.stac-item
2022-09-11 10:53:26	ga_ls9c_ard_3-2-1_106069_2022-09-11_final.stac-item
2022-09-20 10:46:56	ga_ls9c_ard_3-2-1_105068_2022-09-20_final.stac-item
2022-09-20 10:47:44	ga_ls9c_ard_3-2-1_105070_2022-09-20_final.stac-item
2022-09-27 10:53:33	ga_ls9c_ard_3-2-1_106069_2022-09-27_final.stac-item
2022-10-06 10:46:57	ga_ls9c_ard_3-2-1_105068_2022-10-06_final.stac-item
2022-10-06 10:47:45	ga_ls9c_ard_3-2-1_105070_2022-10-06_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-22 10:47:28	ga_ls9c_ard_3-2-1_105069_2022-10-22_final.stac-item
2022-10-22 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-10-22_final.stac-item
2022-11-07 10:47:50	ga_ls9c_ard_3-2-1_105070_2022-11-07_final.stac-item
2022-11-23 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-11-23_final.stac-item
2022-12-09 10:47:03	ga_ls9c_ard_3-2-1_105068_2022-12-09_final.stac-item
2022-12-09 10:47:27	ga_ls9c_ard_3-2-1_105069_2022-12-09_final.stac-item
2022-12-09 10:47:51	ga_ls9c_ard_3-2-1_105070_2022-12-09_final.stac-item
2022-12-16 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-12-16_final.stac-item
2022-12-16 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-12-16_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2022-12-25 10:47:48	ga_ls9c_ard_3-2-1_105070_2022-12-25_final.stac-item
2023-01-01 10:53:38	ga_ls9c_ard_3-2-1_106069_2023-01-01_final.stac-item
2023-01-10 10:47:51	ga_ls9c_ard_3-2-1_105070_2023-01-10_final.stac-item
2023-01-26 10:47:24	ga_ls9c_ard_3-2-1_105069_2023-01-26_final.stac-item
2023-02-11 10:47:07	ga_ls9c_ard_3-2-1_105068_2023-02-11_final.stac-item
2023-02-11 10:47:31	ga_ls9c_ard_3-2-1_105069_2023-02-11_final.stac-item
2023-02-11 10:47:55	ga_ls9c_ard_3-2-1_105070_2023-02-11_final.stac-item
2023-02-18 10:53:36	ga_ls9c_ard_3-2-1_106069_2023-02-18_final.stac-item
2023-02-27 10:47:41	ga_ls9c_ard_3-2-1_105070_2023-02-27_final.stac-item
2023-03-06 10:53:00	ga_ls9c_ard_3-2-1_106068_2023-03-06_final.stac-item
2023-03-15 10:47:10	ga_ls9c_ard_3-2-1_105069_2023-03-15_final.stac-item
2023-03-15 10:47:34	ga_ls9c_ard_3-2-1_105070_2023-03-15_final.stac-item
2023-03-15 10:47:57	ga_ls9c_ard_3-2-1_105071_2023-03-15_final.stac-item
2023-03-22 10:52:54	ga_ls9c_ard_3-2-1_106068_2023-03-22_final.stac-item
2023-03-22 10:53:17	ga_ls9c_ard_3-2-1_106069_2023-03-22_final.stac-item
2023-03-31 10:46:34	ga_ls9c_ard_3-2-1_105068_2023-03-31_final.stac-item
2023-03-31 10:47:22	ga_ls9c_ard_3-2-1_105070_2023-03-31_final.stac-item
2023-04-16 10:46:27	ga_ls9c_ard_3-2-1_105068_2023-04-16_final.stac-item
2023-04-16 10:46:51	ga_ls9c_ard_3-2-1_105069_2023-04-16_final.stac-item
2023-04-16 10:47:15	ga_ls9c_ard_3-2-1_105070_2023-04-16_final.stac-item
2023-04-16 10:47:39	ga_ls9c_ard_3-2-1_105071_2023-04-16_final.stac-item
2023-04-23 10:52:38	ga_ls9c_ard_3-2-1_106068_2023-04-23_final.stac-item
2023-05-02 10:47:06	ga_ls9c_ard_3-2-1_105070_2023-05-02_final.stac-item
2023-05-09 10:52:26	ga_ls9c_ard_3-2-1_106068_2023-05-09_final.stac-item
2023-05-18 10:46:11	ga_ls9c_ard_3-2-1_105068_2023-05-18_final.stac-item
2023-05-18 10:46:59	ga_ls9c_ard_3-2-1_105070_2023-05-18_final.stac-item
2023-05-25 10:52:16	ga_ls9c_ard_3-2-1_106068_2023-05-25_final.stac-item
2023-06-19 10:46:44	ga_ls9c_ard_3-2-1_105070_2023-06-19_final.stac-item
2023-06-26 10:52:07	ga_ls9c_ard_3-2-1_106068_2023-06-26_final.stac-item
2023-07-05 10:46:56	ga_ls9c_ard_3-2-1_105070_2023-07-05_final.stac-item
2023-07-12 10:52:47	ga_ls9c_ard_3-2-1_106069_2023-07-12_final.stac-item
2023-08-06 10:46:46	ga_ls9c_ard_3-2-1_105069_2023-08-06_final.stac-item
2023-08-29 10:53:07	ga_ls9c_ard_3-2-1_106069_2023-08-29_final.stac-item
2024-03-17 10:46:46	ga_ls9c_ard_3-2-1_105068_2024-03-17_final.stac-item
2024-04-25 10:52:25	ga_ls9c_ard_3-2-1_106068_2024-04-25_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