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 10:01:01	ga_ls9c_ard_3-2-1_097084_2021-11-08_final.stac-item
2021-12-06 09:14:30	ga_ls9c_ard_3-2-1_089084_2021-12-05_final.stac-item
2021-12-19 10:22:22	ga_ls9c_ard_3-2-1_100084_2021-12-19_final.stac-item
2021-12-22 09:14:24	ga_ls9c_ard_3-2-1_089084_2021-12-21_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2021-12-30 10:03:50	ga_ls9c_ard_3-2-1_097084_2021-12-30_final.stac-item
2022-01-06 10:10:00	ga_ls9c_ard_3-2-1_098084_2022-01-06_final.stac-item
2022-01-07 09:14:22	ga_ls9c_ard_3-2-1_089084_2022-01-06_final.stac-item
2022-01-13 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-01-13_final.stac-item
2022-01-23 09:14:23	ga_ls9c_ard_3-2-1_089084_2022-01-22_final.stac-item
2022-01-29 10:16:11	ga_ls9c_ard_3-2-1_099084_2022-01-29_final.stac-item
2022-02-07 10:09:59	ga_ls9c_ard_3-2-1_098084_2022-02-07_final.stac-item
2022-02-16 10:03:45	ga_ls9c_ard_3-2-1_097084_2022-02-16_final.stac-item
2022-02-21 10:22:14	ga_ls9c_ard_3-2-1_100084_2022-02-21_final.stac-item
2022-02-23 10:09:51	ga_ls9c_ard_3-2-1_098084_2022-02-23_final.stac-item
2022-02-24 09:14:13	ga_ls9c_ard_3-2-1_089084_2022-02-23_final.stac-item
2022-03-02 10:15:56	ga_ls9c_ard_3-2-1_099084_2022-03-02_final.stac-item
2022-03-12 09:14:08	ga_ls9c_ard_3-2-1_089084_2022-03-11_final.stac-item
2022-03-20 10:03:33	ga_ls9c_ard_3-2-1_097084_2022-03-20_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-04-05 10:03:29	ga_ls9c_ard_3-2-1_097084_2022-04-05_final.stac-item
2022-04-12 10:09:37	ga_ls9c_ard_3-2-1_098084_2022-04-12_final.stac-item
2022-04-13 09:13:59	ga_ls9c_ard_3-2-1_089084_2022-04-12_final.stac-item
2022-04-26 10:21:51	ga_ls9c_ard_3-2-1_100084_2022-04-26_final.stac-item
2022-04-29 09:13:52	ga_ls9c_ard_3-2-1_089084_2022-04-28_final.stac-item
2022-05-12 10:21:44	ga_ls9c_ard_3-2-1_100084_2022-05-12_final.stac-item
2022-05-14 10:09:20	ga_ls9c_ard_3-2-1_098084_2022-05-14_final.stac-item
2022-05-15 09:13:42	ga_ls9c_ard_3-2-1_089084_2022-05-14_final.stac-item
2022-05-23 10:03:04	ga_ls9c_ard_3-2-1_097084_2022-05-23_final.stac-item
2022-05-28 10:21:36	ga_ls9c_ard_3-2-1_100084_2022-05-28_final.stac-item
2022-05-30 10:09:15	ga_ls9c_ard_3-2-1_098084_2022-05-30_final.stac-item
2022-05-31 09:13:38	ga_ls9c_ard_3-2-1_089084_2022-05-30_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 09:13:45	ga_ls9c_ard_3-2-1_089084_2022-06-15_final.stac-item
2022-06-22 10:15:43	ga_ls9c_ard_3-2-1_099084_2022-06-22_final.stac-item
2022-07-01 10:09:36	ga_ls9c_ard_3-2-1_098084_2022-07-01_final.stac-item
2022-07-08 10:15:45	ga_ls9c_ard_3-2-1_099084_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
2022-07-31 10:22:09	ga_ls9c_ard_3-2-1_100084_2022-07-31_final.stac-item
2022-08-03 09:14:12	ga_ls9c_ard_3-2-1_089084_2022-08-02_final.stac-item
2022-08-19 09:14:20	ga_ls9c_ard_3-2-1_089084_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
2022-09-01 10:22:20	ga_ls9c_ard_3-2-1_100084_2022-09-01_final.stac-item
2022-09-03 10:09:58	ga_ls9c_ard_3-2-1_098084_2022-09-03_final.stac-item
2022-09-10 10:16:09	ga_ls9c_ard_3-2-1_099084_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
2022-09-26 10:16:16	ga_ls9c_ard_3-2-1_099084_2022-09-26_final.stac-item
2022-10-12 10:16:19	ga_ls9c_ard_3-2-1_099084_2022-10-12_final.stac-item
2022-10-19 10:22:33	ga_ls9c_ard_3-2-1_100084_2022-10-19_final.stac-item
2022-10-22 09:14:34	ga_ls9c_ard_3-2-1_089084_2022-10-21_final.stac-item
2022-11-04 10:22:30	ga_ls9c_ard_3-2-1_100084_2022-11-04_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_nrt.stac-item
2022-11-07 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-11-06_final.stac-item
2022-11-23 09:14:34	ga_ls9c_ard_3-2-1_089084_2022-11-22_final.stac-item
2022-12-06 10:22:32	ga_ls9c_ard_3-2-1_100084_2022-12-06_final.stac-item
2022-12-06 10:22:32	ga_ls9c_ard_3-2-1_100084_2022-12-06_nrt.stac-item
2022-12-08 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-12-08_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-15 10:16:22	ga_ls9c_ard_3-2-1_099084_2022-12-15_final.stac-item
2022-12-25 09:14:31	ga_ls9c_ard_3-2-1_089084_2022-12-24_final.stac-item
2023-01-09 10:10:11	ga_ls9c_ard_3-2-1_098084_2023-01-09_final.stac-item
2023-01-10 09:14:33	ga_ls9c_ard_3-2-1_089084_2023-01-09_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_final.stac-item
2023-01-26 09:14:30	ga_ls9c_ard_3-2-1_089084_2023-01-25_final.stac-item
2023-02-01 10:16:23	ga_ls9c_ard_3-2-1_099084_2023-02-01_final.stac-item
2023-02-10 10:10:15	ga_ls9c_ard_3-2-1_098084_2023-02-10_final.stac-item
2023-02-11 09:14:37	ga_ls9c_ard_3-2-1_089084_2023-02-10_final.stac-item
2023-02-26 10:10:00	ga_ls9c_ard_3-2-1_098084_2023-02-26_final.stac-item
2023-02-27 09:14:23	ga_ls9c_ard_3-2-1_089084_2023-02-26_final.stac-item
2023-03-05 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-03-05_final.stac-item
2023-03-12 10:22:14	ga_ls9c_ard_3-2-1_100084_2023-03-12_final.stac-item
2023-03-14 10:09:53	ga_ls9c_ard_3-2-1_098084_2023-03-14_final.stac-item
2023-03-15 09:14:16	ga_ls9c_ard_3-2-1_089084_2023-03-14_final.stac-item
2023-03-16 09:57:31	ga_ls9c_ard_3-2-1_096084_2023-03-16_final.stac-item
2023-03-21 10:16:02	ga_ls9c_ard_3-2-1_099084_2023-03-21_final.stac-item
2023-03-23 10:03:38	ga_ls9c_ard_3-2-1_097084_2023-03-23_final.stac-item
2023-03-31 09:14:04	ga_ls9c_ard_3-2-1_089084_2023-03-30_final.stac-item
2023-04-13 10:21:58	ga_ls9c_ard_3-2-1_100084_2023-04-13_final.stac-item
2023-04-16 09:13:57	ga_ls9c_ard_3-2-1_089084_2023-04-15_final.stac-item
2023-04-17 09:57:13	ga_ls9c_ard_3-2-1_096084_2023-04-17_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-05-02 09:13:49	ga_ls9c_ard_3-2-1_089084_2023-05-01_final.stac-item
2023-05-08 10:15:34	ga_ls9c_ard_3-2-1_099084_2023-05-08_final.stac-item
2023-05-10 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-05-10_final.stac-item
2023-05-12 09:50:50	ga_ls9c_ard_3-2-1_095084_2023-05-12_final.stac-item
2023-05-15 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-05-15_final.stac-item
2023-05-18 09:13:41	ga_ls9c_ard_3-2-1_089084_2023-05-17_final.stac-item
2023-05-31 10:21:34	ga_ls9c_ard_3-2-1_100084_2023-05-31_final.stac-item
2023-06-02 10:09:12	ga_ls9c_ard_3-2-1_098084_2023-06-02_final.stac-item
2023-06-03 09:13:34	ga_ls9c_ard_3-2-1_089084_2023-06-02_final.stac-item
2023-06-19 09:13:26	ga_ls9c_ard_3-2-1_089084_2023-06-18_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_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
2023-11-10 09:14:17	ga_ls9c_ard_3-2-1_089084_2023-11-09_final.stac-item
2024-04-24 10:15:32	ga_ls9c_ard_3-2-1_099084_2024-04-24_final.stac-item
2024-05-01 10:21:42	ga_ls9c_ard_3-2-1_100084_2024-05-01_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