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
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-08 09:57:50	ga_ls9c_ard_3-2-1_097076_2021-11-08_final.stac-item
2021-11-10 09:39:05	ga_ls9c_ard_3-2-1_094076_2021-11-10_final.stac-item
2021-11-12 09:20:21	ga_ls9c_ard_3-2-1_091076_2021-11-11_final.stac-item
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-07 09:54:34	ga_ls9c_ard_3-2-1_096076_2021-12-07_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2021-12-20 09:23:34	ga_ls9c_ard_3-2-1_091076_2021-12-19_final.stac-item
2021-12-30 10:00:39	ga_ls9c_ard_3-2-1_097076_2021-12-30_final.stac-item
2022-01-08 09:54:26	ga_ls9c_ard_3-2-1_096076_2022-01-08_final.stac-item
2022-01-19 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-01-19_final.stac-item
2022-01-24 09:54:27	ga_ls9c_ard_3-2-1_096076_2022-01-24_final.stac-item
2022-02-04 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-02-04_final.stac-item
2022-02-06 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-02-05_final.stac-item
2022-02-09 09:54:25	ga_ls9c_ard_3-2-1_096076_2022-02-09_final.stac-item
2022-02-20 09:35:47	ga_ls9c_ard_3-2-1_093076_2022-02-20_final.stac-item
2022-02-22 09:23:24	ga_ls9c_ard_3-2-1_091076_2022-02-21_final.stac-item
2022-02-25 09:54:16	ga_ls9c_ard_3-2-1_096076_2022-02-25_final.stac-item
2022-03-08 09:35:40	ga_ls9c_ard_3-2-1_093076_2022-03-08_final.stac-item
2022-03-10 09:23:18	ga_ls9c_ard_3-2-1_091076_2022-03-09_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-03-26 09:23:14	ga_ls9c_ard_3-2-1_091076_2022-03-25_final.stac-item
2022-04-11 09:23:10	ga_ls9c_ard_3-2-1_091076_2022-04-10_final.stac-item
2022-04-25 09:35:24	ga_ls9c_ard_3-2-1_093076_2022-04-25_final.stac-item
2022-04-27 09:23:02	ga_ls9c_ard_3-2-1_091076_2022-04-26_final.stac-item
2022-04-30 09:53:55	ga_ls9c_ard_3-2-1_096076_2022-04-30_final.stac-item
2022-05-07 10:00:03	ga_ls9c_ard_3-2-1_097076_2022-05-07_final.stac-item
2022-05-13 09:22:54	ga_ls9c_ard_3-2-1_091076_2022-05-12_final.stac-item
2022-05-16 09:53:45	ga_ls9c_ard_3-2-1_096076_2022-05-16_final.stac-item
2022-05-23 09:59:52	ga_ls9c_ard_3-2-1_097076_2022-05-23_final.stac-item
2022-05-27 09:35:09	ga_ls9c_ard_3-2-1_093076_2022-05-27_final.stac-item
2022-05-29 09:22:48	ga_ls9c_ard_3-2-1_091076_2022-05-28_final.stac-item
2022-06-01 09:53:42	ga_ls9c_ard_3-2-1_096076_2022-06-01_final.stac-item
2022-06-12 09:35:13	ga_ls9c_ard_3-2-1_093076_2022-06-12_final.stac-item
2022-06-28 09:35:31	ga_ls9c_ard_3-2-1_093076_2022-06-28_final.stac-item
2022-06-30 09:23:09	ga_ls9c_ard_3-2-1_091076_2022-06-29_final.stac-item
2022-07-03 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-03_final.stac-item
2022-07-10 10:00:11	ga_ls9c_ard_3-2-1_097076_2022-07-10_final.stac-item
2022-07-16 09:23:06	ga_ls9c_ard_3-2-1_091076_2022-07-15_final.stac-item
2022-07-19 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-19_final.stac-item
2022-07-30 09:35:41	ga_ls9c_ard_3-2-1_093076_2022-07-30_final.stac-item
2022-08-01 09:23:20	ga_ls9c_ard_3-2-1_091076_2022-07-31_final.stac-item
2022-08-04 09:54:17	ga_ls9c_ard_3-2-1_096076_2022-08-04_final.stac-item
2022-08-11 10:00:32	ga_ls9c_ard_3-2-1_097076_2022-08-11_final.stac-item
2022-08-15 09:35:50	ga_ls9c_ard_3-2-1_093076_2022-08-15_final.stac-item
2022-08-17 09:23:29	ga_ls9c_ard_3-2-1_091076_2022-08-16_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-08-27 10:00:36	ga_ls9c_ard_3-2-1_097076_2022-08-27_final.stac-item
2022-08-31 09:35:53	ga_ls9c_ard_3-2-1_093076_2022-08-31_final.stac-item
2022-09-02 09:23:31	ga_ls9c_ard_3-2-1_091076_2022-09-01_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-18 09:23:36	ga_ls9c_ard_3-2-1_091076_2022-09-17_final.stac-item
2022-09-21 09:54:31	ga_ls9c_ard_3-2-1_096076_2022-09-21_final.stac-item
2022-09-28 10:00:43	ga_ls9c_ard_3-2-1_097076_2022-09-28_final.stac-item
2022-10-02 09:36:00	ga_ls9c_ard_3-2-1_093076_2022-10-02_final.stac-item
2022-10-04 09:23:38	ga_ls9c_ard_3-2-1_091076_2022-10-03_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-20 09:23:44	ga_ls9c_ard_3-2-1_091076_2022-10-19_final.stac-item
2022-10-30 10:00:48	ga_ls9c_ard_3-2-1_097076_2022-10-30_final.stac-item
2022-11-03 09:36:03	ga_ls9c_ard_3-2-1_093076_2022-11-03_final.stac-item
2022-11-05 09:23:41	ga_ls9c_ard_3-2-1_091076_2022-11-04_final.stac-item
2022-11-05 09:23:41	ga_ls9c_ard_3-2-1_091076_2022-11-04_interim.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-11-21 09:23:45	ga_ls9c_ard_3-2-1_091076_2022-11-20_final.stac-item
2022-11-24 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-11-24_final.stac-item
2022-12-01 10:00:46	ga_ls9c_ard_3-2-1_097076_2022-12-01_final.stac-item
2022-12-05 09:36:04	ga_ls9c_ard_3-2-1_093076_2022-12-05_final.stac-item
2022-12-07 09:23:43	ga_ls9c_ard_3-2-1_091076_2022-12-06_final.stac-item
2022-12-07 09:23:43	ga_ls9c_ard_3-2-1_091076_2022-12-06_nrt.stac-item
2022-12-10 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-12-10_final.stac-item
2022-12-17 10:00:48	ga_ls9c_ard_3-2-1_097076_2022-12-17_final.stac-item
2022-12-21 09:36:03	ga_ls9c_ard_3-2-1_093076_2022-12-21_final.stac-item
2022-12-23 09:23:40	ga_ls9c_ard_3-2-1_091076_2022-12-22_final.stac-item
2022-12-26 09:54:35	ga_ls9c_ard_3-2-1_096076_2022-12-26_final.stac-item
2023-01-02 10:00:49	ga_ls9c_ard_3-2-1_097076_2023-01-02_final.stac-item
2023-01-06 09:36:06	ga_ls9c_ard_3-2-1_093076_2023-01-06_final.stac-item
2023-01-08 09:23:44	ga_ls9c_ard_3-2-1_091076_2023-01-07_final.stac-item
2023-01-22 09:35:57	ga_ls9c_ard_3-2-1_093076_2023-01-22_final.stac-item
2023-01-24 09:23:38	ga_ls9c_ard_3-2-1_091076_2023-01-23_final.stac-item
2023-01-27 09:54:35	ga_ls9c_ard_3-2-1_096076_2023-01-27_final.stac-item
2023-02-07 09:36:09	ga_ls9c_ard_3-2-1_093076_2023-02-07_final.stac-item
2023-02-09 09:23:47	ga_ls9c_ard_3-2-1_091076_2023-02-08_final.stac-item
2023-02-12 09:54:41	ga_ls9c_ard_3-2-1_096076_2023-02-12_final.stac-item
2023-02-23 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-02-23_final.stac-item
2023-03-07 10:00:33	ga_ls9c_ard_3-2-1_097076_2023-03-07_final.stac-item
2023-03-11 09:35:47	ga_ls9c_ard_3-2-1_093076_2023-03-11_final.stac-item
2023-03-23 10:00:27	ga_ls9c_ard_3-2-1_097076_2023-03-23_final.stac-item
2023-04-12 09:35:31	ga_ls9c_ard_3-2-1_093076_2023-04-12_final.stac-item
2023-04-14 09:23:08	ga_ls9c_ard_3-2-1_091076_2023-04-13_final.stac-item
2023-04-17 09:54:02	ga_ls9c_ard_3-2-1_096076_2023-04-17_final.stac-item
2023-04-28 09:35:25	ga_ls9c_ard_3-2-1_093076_2023-04-28_final.stac-item
2023-04-30 09:23:01	ga_ls9c_ard_3-2-1_091076_2023-04-29_final.stac-item
2023-05-14 09:35:16	ga_ls9c_ard_3-2-1_093076_2023-05-14_final.stac-item
2023-05-16 09:22:53	ga_ls9c_ard_3-2-1_091076_2023-05-15_final.stac-item
2023-05-30 09:35:07	ga_ls9c_ard_3-2-1_093076_2023-05-30_final.stac-item
2023-06-01 09:22:45	ga_ls9c_ard_3-2-1_091076_2023-05-31_final.stac-item
2023-06-15 09:34:58	ga_ls9c_ard_3-2-1_093076_2023-06-15_final.stac-item
2023-06-17 09:22:36	ga_ls9c_ard_3-2-1_091076_2023-06-16_final.stac-item
2023-07-01 09:35:07	ga_ls9c_ard_3-2-1_093076_2023-07-01_final.stac-item
2023-07-03 09:22:47	ga_ls9c_ard_3-2-1_091076_2023-07-02_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