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

61 results

Time (local)	Label
2021-11-07 09:23:27	ga_ls9c_ard_3-2-1_090090_2021-11-06_final.stac-item
2021-11-22 09:30:50	ga_ls9c_ard_3-2-1_091090_2021-11-22_final.stac-item
2021-12-04 09:29:17	ga_ls9c_ard_3-2-1_091090_2021-12-03_final.stac-item
2021-12-20 09:29:09	ga_ls9c_ard_3-2-1_091090_2021-12-19_final.stac-item
2021-12-27 09:35:20	ga_ls9c_ard_3-2-1_092090_2021-12-27_final.stac-item
2022-05-29 09:28:23	ga_ls9c_ard_3-2-1_091090_2022-05-28_final.stac-item
2022-05-31 09:16:02	ga_ls9c_ard_3-2-1_089090_2022-05-30_final.stac-item
2022-06-05 09:34:35	ga_ls9c_ard_3-2-1_092090_2022-06-05_final.stac-item
2022-06-14 09:28:28	ga_ls9c_ard_3-2-1_091090_2022-06-13_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-06-21 09:34:49	ga_ls9c_ard_3-2-1_092090_2022-06-21_final.stac-item
2022-06-23 09:22:31	ga_ls9c_ard_3-2-1_090090_2022-06-22_final.stac-item
2022-07-02 09:16:23	ga_ls9c_ard_3-2-1_089090_2022-07-01_final.stac-item
2022-07-16 09:28:41	ga_ls9c_ard_3-2-1_091090_2022-07-15_final.stac-item
2022-07-18 09:16:22	ga_ls9c_ard_3-2-1_089090_2022-07-17_final.stac-item
2022-07-23 09:34:59	ga_ls9c_ard_3-2-1_092090_2022-07-23_final.stac-item
2022-08-03 09:16:36	ga_ls9c_ard_3-2-1_089090_2022-08-02_final.stac-item
2022-08-24 09:35:17	ga_ls9c_ard_3-2-1_092090_2022-08-24_final.stac-item
2022-09-02 09:29:06	ga_ls9c_ard_3-2-1_091090_2022-09-01_final.stac-item
2022-09-18 09:29:11	ga_ls9c_ard_3-2-1_091090_2022-09-17_final.stac-item
2022-09-20 09:16:50	ga_ls9c_ard_3-2-1_089090_2022-09-19_final.stac-item
2022-09-27 09:23:03	ga_ls9c_ard_3-2-1_090090_2022-09-26_final.stac-item
2022-10-04 09:29:13	ga_ls9c_ard_3-2-1_091090_2022-10-03_final.stac-item
2022-10-27 09:35:30	ga_ls9c_ard_3-2-1_092090_2022-10-27_final.stac-item
2023-01-08 09:29:19	ga_ls9c_ard_3-2-1_091090_2023-01-07_final.stac-item
2023-02-02 09:23:34	ga_ls9c_ard_3-2-1_090091_2023-02-01_interim.stac-item
2023-02-18 09:23:30	ga_ls9c_ard_3-2-1_090091_2023-02-17_interim.stac-item
2023-03-06 09:23:18	ga_ls9c_ard_3-2-1_090091_2023-03-05_interim.stac-item
2023-06-17 09:28:11	ga_ls9c_ard_3-2-1_091090_2023-06-16_final.stac-item
2023-06-19 09:15:50	ga_ls9c_ard_3-2-1_089090_2023-06-18_final.stac-item
2023-06-24 09:34:22	ga_ls9c_ard_3-2-1_092090_2023-06-24_final.stac-item
2023-07-03 09:28:22	ga_ls9c_ard_3-2-1_091090_2023-07-02_final.stac-item
2023-07-05 09:16:02	ga_ls9c_ard_3-2-1_089090_2023-07-04_final.stac-item
2023-07-10 09:34:37	ga_ls9c_ard_3-2-1_092090_2023-07-10_final.stac-item
2023-07-12 09:22:17	ga_ls9c_ard_3-2-1_090090_2023-07-11_final.stac-item
2023-07-19 09:28:28	ga_ls9c_ard_3-2-1_091090_2023-07-18_final.stac-item
2023-07-26 09:34:39	ga_ls9c_ard_3-2-1_092090_2023-07-26_final.stac-item
2023-07-28 09:22:19	ga_ls9c_ard_3-2-1_090090_2023-07-27_final.stac-item
2023-08-04 09:28:36	ga_ls9c_ard_3-2-1_091090_2023-08-03_final.stac-item
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final.stac-item
2023-08-11 09:34:49	ga_ls9c_ard_3-2-1_092090_2023-08-11_final.stac-item
2023-08-13 09:22:28	ga_ls9c_ard_3-2-1_090090_2023-08-12_final.stac-item
2023-08-22 09:16:20	ga_ls9c_ard_3-2-1_089090_2023-08-21_final.stac-item
2023-08-27 09:34:57	ga_ls9c_ard_3-2-1_092090_2023-08-27_final.stac-item
2023-08-29 09:22:37	ga_ls9c_ard_3-2-1_090090_2023-08-28_final.stac-item
2023-09-05 09:28:51	ga_ls9c_ard_3-2-1_091090_2023-09-04_final.stac-item
2023-09-12 09:35:07	ga_ls9c_ard_3-2-1_092090_2023-09-12_final.stac-item
2023-09-14 09:22:46	ga_ls9c_ard_3-2-1_090090_2023-09-13_final.stac-item
2023-09-23 09:16:34	ga_ls9c_ard_3-2-1_089090_2023-09-22_final.stac-item
2023-09-28 09:35:02	ga_ls9c_ard_3-2-1_092090_2023-09-28_final.stac-item
2023-10-16 09:22:55	ga_ls9c_ard_3-2-1_090090_2023-10-15_final.stac-item
2023-10-25 09:16:44	ga_ls9c_ard_3-2-1_089090_2023-10-24_final.stac-item
2023-11-08 09:29:02	ga_ls9c_ard_3-2-1_091090_2023-11-07_final.stac-item
2023-11-15 09:35:13	ga_ls9c_ard_3-2-1_092090_2023-11-15_final.stac-item
2023-12-01 09:35:21	ga_ls9c_ard_3-2-1_092090_2023-12-01_final.stac-item
2023-12-03 09:22:58	ga_ls9c_ard_3-2-1_090090_2023-12-02_final.stac-item
2023-12-12 09:16:47	ga_ls9c_ard_3-2-1_089090_2023-12-11_final.stac-item
2023-12-17 09:35:22	ga_ls9c_ard_3-2-1_092090_2023-12-17_final.stac-item
2023-12-28 09:16:50	ga_ls9c_ard_3-2-1_089090_2023-12-27_final.stac-item
2024-01-13 09:16:47	ga_ls9c_ard_3-2-1_089090_2024-01-12_final.stac-item
2024-04-09 09:23:03	ga_ls9c_ard_3-2-1_090091_2024-04-08_interim.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