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
2021-11-07 09:21:28	ga_ls9c_ard_3-2-1_090085_2021-11-06_final.stac-item
2021-11-08 10:01:01	ga_ls9c_ard_3-2-1_097084_2021-11-08_final.stac-item
2021-11-12 09:23:56	ga_ls9c_ard_3-2-1_091085_2021-11-11_final.stac-item
2021-12-06 09:14:30	ga_ls9c_ard_3-2-1_089084_2021-12-05_final.stac-item
2021-12-06 09:14:54	ga_ls9c_ard_3-2-1_089085_2021-12-05_final.stac-item
2021-12-29 09:20:59	ga_ls9c_ard_3-2-1_090085_2021-12-28_final.stac-item
2022-01-14 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-01-13_final.stac-item
2022-01-23 09:14:47	ga_ls9c_ard_3-2-1_089085_2022-01-22_final.stac-item
2022-01-30 09:20:58	ga_ls9c_ard_3-2-1_090085_2022-01-29_final.stac-item
2022-02-15 09:20:53	ga_ls9c_ard_3-2-1_090085_2022-02-14_final.stac-item
2022-03-03 09:20:42	ga_ls9c_ard_3-2-1_090085_2022-03-02_final.stac-item
2022-04-04 09:20:38	ga_ls9c_ard_3-2-1_090085_2022-04-03_final.stac-item
2022-04-20 09:20:28	ga_ls9c_ard_3-2-1_090085_2022-04-19_final.stac-item
2022-05-02 11:24:02	ga_ls9c_ard_3-2-1_110085_2022-05-02_final.stac-item
2022-05-14 10:09:44	ga_ls9c_ard_3-2-1_098085_2022-05-14_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-05-31 09:13:38	ga_ls9c_ard_3-2-1_089084_2022-05-30_final.stac-item
2022-06-07 09:20:14	ga_ls9c_ard_3-2-1_090085_2022-06-06_final.stac-item
2022-06-13 10:21:41	ga_ls9c_ard_3-2-1_100084_2022-06-13_final.stac-item
2022-06-15 10:09:21	ga_ls9c_ard_3-2-1_098084_2022-06-15_final.stac-item
2022-06-16 09:14:08	ga_ls9c_ard_3-2-1_089085_2022-06-15_final.stac-item
2022-06-23 09:20:31	ga_ls9c_ard_3-2-1_090085_2022-06-22_final.stac-item
2022-07-02 09:14:23	ga_ls9c_ard_3-2-1_089085_2022-07-01_final.stac-item
2022-07-03 09:57:14	ga_ls9c_ard_3-2-1_096084_2022-07-03_final.stac-item
2022-07-08 10:15:45	ga_ls9c_ard_3-2-1_099084_2022-07-08_final.stac-item
2022-07-09 09:20:32	ga_ls9c_ard_3-2-1_090085_2022-07-08_final.stac-item
2022-07-18 09:13:58	ga_ls9c_ard_3-2-1_089084_2022-07-17_final.stac-item
2022-07-25 09:20:40	ga_ls9c_ard_3-2-1_090085_2022-07-24_final.stac-item
2022-07-31 10:22:09	ga_ls9c_ard_3-2-1_100084_2022-07-31_final.stac-item
2022-08-03 09:14:36	ga_ls9c_ard_3-2-1_089085_2022-08-02_final.stac-item
2022-08-10 09:20:51	ga_ls9c_ard_3-2-1_090085_2022-08-09_final.stac-item
2022-08-19 09:14:20	ga_ls9c_ard_3-2-1_089084_2022-08-18_final.stac-item
2022-08-19 09:14:44	ga_ls9c_ard_3-2-1_089085_2022-08-18_final.stac-item
2022-08-25 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-08-25_final.stac-item
2022-08-26 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-08-25_final.stac-item
2022-09-03 10:09:58	ga_ls9c_ard_3-2-1_098084_2022-09-03_final.stac-item
2022-09-04 09:14:45	ga_ls9c_ard_3-2-1_089085_2022-09-03_final.stac-item
2022-09-11 09:20:56	ga_ls9c_ard_3-2-1_090085_2022-09-10_final.stac-item
2022-09-19 10:10:03	ga_ls9c_ard_3-2-1_098084_2022-09-19_final.stac-item
2022-09-20 09:14:50	ga_ls9c_ard_3-2-1_089085_2022-09-19_final.stac-item
2022-09-26 10:16:16	ga_ls9c_ard_3-2-1_099084_2022-09-26_final.stac-item
2022-09-26 10:16:40	ga_ls9c_ard_3-2-1_099085_2022-09-26_final.stac-item
2022-09-27 09:21:03	ga_ls9c_ard_3-2-1_090085_2022-09-26_final.stac-item
2022-10-06 09:14:51	ga_ls9c_ard_3-2-1_089085_2022-10-05_final.stac-item
2022-10-13 09:21:07	ga_ls9c_ard_3-2-1_090085_2022-10-12_final.stac-item
2022-10-29 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-10-28_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_final.stac-item
2022-11-07 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-11-06_final.stac-item
2022-11-14 09:21:10	ga_ls9c_ard_3-2-1_090085_2022-11-13_final.stac-item
2022-11-23 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-11-22_final.stac-item
2022-11-30 09:21:06	ga_ls9c_ard_3-2-1_090085_2022-11-29_final.stac-item
2022-12-08 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-12-08_final.stac-item
2022-12-16 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-12-15_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2023-01-01 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-12-31_final.stac-item
2023-01-17 09:21:03	ga_ls9c_ard_3-2-1_090085_2023-01-16_final.stac-item
2023-02-02 09:21:10	ga_ls9c_ard_3-2-1_090085_2023-02-01_final.stac-item
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final.stac-item
2023-03-06 09:20:54	ga_ls9c_ard_3-2-1_090085_2023-03-05_final.stac-item
2023-03-22 09:20:48	ga_ls9c_ard_3-2-1_090085_2023-03-21_final.stac-item
2023-04-07 09:20:38	ga_ls9c_ard_3-2-1_090085_2023-04-06_final.stac-item
2023-04-23 09:20:32	ga_ls9c_ard_3-2-1_090085_2023-04-22_final.stac-item
2023-05-09 09:20:20	ga_ls9c_ard_3-2-1_090085_2023-05-08_final.stac-item
2023-05-25 09:20:10	ga_ls9c_ard_3-2-1_090085_2023-05-24_final.stac-item
2023-06-03 09:13:58	ga_ls9c_ard_3-2-1_089085_2023-06-02_final.stac-item
2023-06-10 09:20:05	ga_ls9c_ard_3-2-1_090085_2023-06-09_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-06-26 09:20:01	ga_ls9c_ard_3-2-1_090085_2023-06-25_final.stac-item
2023-06-27 10:02:55	ga_ls9c_ard_3-2-1_097084_2023-06-27_final.stac-item
2023-07-05 09:14:02	ga_ls9c_ard_3-2-1_089085_2023-07-04_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-07-21 09:14:07	ga_ls9c_ard_3-2-1_089085_2023-07-20_final.stac-item
2023-07-28 09:20:19	ga_ls9c_ard_3-2-1_090085_2023-07-27_final.stac-item
2023-08-06 09:14:16	ga_ls9c_ard_3-2-1_089085_2023-08-05_final.stac-item
2023-08-13 09:20:28	ga_ls9c_ard_3-2-1_090085_2023-08-12_final.stac-item
2023-08-22 09:14:21	ga_ls9c_ard_3-2-1_089085_2023-08-21_final.stac-item
2023-08-29 09:20:37	ga_ls9c_ard_3-2-1_090085_2023-08-28_final.stac-item
2023-09-07 09:14:31	ga_ls9c_ard_3-2-1_089085_2023-09-06_final.stac-item
2023-09-14 09:20:46	ga_ls9c_ard_3-2-1_090085_2023-09-13_final.stac-item
2023-09-23 09:14:34	ga_ls9c_ard_3-2-1_089085_2023-09-22_final.stac-item
2023-09-30 09:20:43	ga_ls9c_ard_3-2-1_090085_2023-09-29_final.stac-item
2023-10-09 09:14:39	ga_ls9c_ard_3-2-1_089085_2023-10-08_final.stac-item
2023-10-16 09:20:56	ga_ls9c_ard_3-2-1_090085_2023-10-15_final.stac-item
2023-10-25 09:14:45	ga_ls9c_ard_3-2-1_089085_2023-10-24_final.stac-item
2023-11-01 09:20:50	ga_ls9c_ard_3-2-1_090085_2023-10-31_final.stac-item
2023-11-10 09:14:41	ga_ls9c_ard_3-2-1_089085_2023-11-09_final.stac-item
2023-11-17 09:20:53	ga_ls9c_ard_3-2-1_090085_2023-11-16_final.stac-item
2023-11-26 09:14:49	ga_ls9c_ard_3-2-1_089085_2023-11-25_final.stac-item
2023-12-03 09:20:59	ga_ls9c_ard_3-2-1_090085_2023-12-02_final.stac-item
2023-12-12 09:14:47	ga_ls9c_ard_3-2-1_089085_2023-12-11_final.stac-item
2023-12-19 09:21:02	ga_ls9c_ard_3-2-1_090085_2023-12-18_final.stac-item
2023-12-28 09:14:50	ga_ls9c_ard_3-2-1_089085_2023-12-27_final.stac-item
2024-01-04 09:20:56	ga_ls9c_ard_3-2-1_090085_2024-01-03_final.stac-item
2024-01-13 09:14:47	ga_ls9c_ard_3-2-1_089085_2024-01-12_final.stac-item
2024-01-20 09:20:57	ga_ls9c_ard_3-2-1_090085_2024-01-19_final.stac-item
2024-01-29 09:14:47	ga_ls9c_ard_3-2-1_089085_2024-01-28_final.stac-item
2024-02-05 09:21:00	ga_ls9c_ard_3-2-1_090085_2024-02-04_final.stac-item
2024-02-14 09:14:46	ga_ls9c_ard_3-2-1_089085_2024-02-13_final.stac-item
2024-02-21 09:20:48	ga_ls9c_ard_3-2-1_090085_2024-02-20_final.stac-item
2024-03-01 09:14:40	ga_ls9c_ard_3-2-1_089085_2024-02-29_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