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

59 results

Time (local)	Label
2021-11-22 11:04:43	ga_ls9c_ard_3-2-1_107078_2021-11-22_final.stac-item
2021-12-04 11:03:22	ga_ls9c_ard_3-2-1_107078_2021-12-04_final.stac-item
2021-12-20 11:03:14	ga_ls9c_ard_3-2-1_107078_2021-12-20_final.stac-item
2022-01-05 11:03:14	ga_ls9c_ard_3-2-1_107078_2022-01-05_final.stac-item
2022-01-21 11:03:13	ga_ls9c_ard_3-2-1_107078_2022-01-21_final.stac-item
2022-02-06 11:03:13	ga_ls9c_ard_3-2-1_107078_2022-02-06_final.stac-item
2022-02-22 11:03:05	ga_ls9c_ard_3-2-1_107078_2022-02-22_final.stac-item
2022-03-10 11:02:59	ga_ls9c_ard_3-2-1_107078_2022-03-10_final.stac-item
2022-03-26 11:02:55	ga_ls9c_ard_3-2-1_107078_2022-03-26_final.stac-item
2022-04-11 11:02:51	ga_ls9c_ard_3-2-1_107078_2022-04-11_final.stac-item
2022-04-27 11:02:43	ga_ls9c_ard_3-2-1_107078_2022-04-27_final.stac-item
2022-05-13 11:02:35	ga_ls9c_ard_3-2-1_107078_2022-05-13_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-30 11:02:50	ga_ls9c_ard_3-2-1_107078_2022-06-30_final.stac-item
2022-07-16 11:02:47	ga_ls9c_ard_3-2-1_107078_2022-07-16_final.stac-item
2022-08-01 11:03:01	ga_ls9c_ard_3-2-1_107078_2022-08-01_final.stac-item
2022-08-17 11:03:10	ga_ls9c_ard_3-2-1_107078_2022-08-17_final.stac-item
2022-09-02 11:03:12	ga_ls9c_ard_3-2-1_107078_2022-09-02_final.stac-item
2022-09-18 11:03:16	ga_ls9c_ard_3-2-1_107078_2022-09-18_final.stac-item
2022-10-04 11:03:19	ga_ls9c_ard_3-2-1_107078_2022-10-04_final.stac-item
2022-10-20 11:03:25	ga_ls9c_ard_3-2-1_107078_2022-10-20_final.stac-item
2022-11-05 11:03:22	ga_ls9c_ard_3-2-1_107078_2022-11-05_final.stac-item
2022-11-21 11:03:26	ga_ls9c_ard_3-2-1_107078_2022-11-21_final.stac-item
2022-12-07 11:03:24	ga_ls9c_ard_3-2-1_107078_2022-12-07_final.stac-item
2022-12-23 11:03:21	ga_ls9c_ard_3-2-1_107078_2022-12-23_final.stac-item
2023-01-08 11:03:24	ga_ls9c_ard_3-2-1_107078_2023-01-08_final.stac-item
2023-01-24 11:03:19	ga_ls9c_ard_3-2-1_107078_2023-01-24_final.stac-item
2023-02-09 11:03:28	ga_ls9c_ard_3-2-1_107078_2023-02-09_final.stac-item
2023-02-25 11:03:14	ga_ls9c_ard_3-2-1_107078_2023-02-25_final.stac-item
2023-03-13 11:03:07	ga_ls9c_ard_3-2-1_107078_2023-03-13_final.stac-item
2023-03-29 11:02:55	ga_ls9c_ard_3-2-1_107078_2023-03-29_final.stac-item
2023-04-14 11:02:49	ga_ls9c_ard_3-2-1_107078_2023-04-14_final.stac-item
2023-04-30 11:02:42	ga_ls9c_ard_3-2-1_107078_2023-04-30_final.stac-item
2023-05-16 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-05-16_final.stac-item
2023-06-01 11:02:26	ga_ls9c_ard_3-2-1_107078_2023-06-01_final.stac-item
2023-06-17 11:02:17	ga_ls9c_ard_3-2-1_107078_2023-06-17_final.stac-item
2023-07-03 11:02:28	ga_ls9c_ard_3-2-1_107078_2023-07-03_final.stac-item
2023-07-19 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-07-19_final.stac-item
2023-08-04 11:02:42	ga_ls9c_ard_3-2-1_107078_2023-08-04_final.stac-item
2023-08-20 11:02:46	ga_ls9c_ard_3-2-1_107078_2023-08-20_final.stac-item
2023-09-05 11:02:57	ga_ls9c_ard_3-2-1_107078_2023-09-05_final.stac-item
2023-09-21 11:03:02	ga_ls9c_ard_3-2-1_107078_2023-09-21_final.stac-item
2023-10-07 11:03:05	ga_ls9c_ard_3-2-1_107078_2023-10-07_final.stac-item
2023-10-23 11:03:12	ga_ls9c_ard_3-2-1_107078_2023-10-23_final.stac-item
2023-11-08 11:03:08	ga_ls9c_ard_3-2-1_107078_2023-11-08_final.stac-item
2023-11-24 11:03:15	ga_ls9c_ard_3-2-1_107078_2023-11-24_final.stac-item
2023-12-10 11:03:13	ga_ls9c_ard_3-2-1_107078_2023-12-10_final.stac-item
2023-12-26 11:03:18	ga_ls9c_ard_3-2-1_107078_2023-12-26_final.stac-item
2024-01-11 11:03:14	ga_ls9c_ard_3-2-1_107078_2024-01-11_final.stac-item
2024-01-27 11:03:12	ga_ls9c_ard_3-2-1_107078_2024-01-27_final.stac-item
2024-02-12 11:03:15	ga_ls9c_ard_3-2-1_107078_2024-02-12_final.stac-item
2024-02-28 11:03:06	ga_ls9c_ard_3-2-1_107078_2024-02-28_final.stac-item
2024-03-15 11:03:07	ga_ls9c_ard_3-2-1_107078_2024-03-15_final.stac-item
2024-03-31 11:02:58	ga_ls9c_ard_3-2-1_107078_2024-03-31_final.stac-item
2024-04-16 11:02:50	ga_ls9c_ard_3-2-1_107078_2024-04-16_final.stac-item
2024-05-02 11:02:34	ga_ls9c_ard_3-2-1_107078_2024-05-02_final.stac-item
2024-05-18 11:02:26	ga_ls9c_ard_3-2-1_107078_2024-05-18_nrt.stac-item
2024-06-03 11:02:20	ga_ls9c_ard_3-2-1_107078_2024-06-03_nrt.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