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

47 results

Time (local)	Label
2021-12-20 09:28:45	ga_ls9c_ard_3-2-1_091089_2021-12-19_final.stac-item
2021-12-29 10:55:52	ga_ls9c_ard_3-2-1_106075_2021-12-29_final.stac-item
2022-01-12 09:34:05	ga_ls9c_ard_3-2-1_092087_2022-01-12_final.stac-item
2022-02-05 10:21:58	ga_ls9c_ard_3-2-1_100083_2022-02-05_final.stac-item
2022-02-06 09:23:08	ga_ls9c_ard_3-2-1_091075_2022-02-05_final.stac-item
2022-02-22 09:23:00	ga_ls9c_ard_3-2-1_091075_2022-02-21_final.stac-item
2022-03-10 09:24:06	ga_ls9c_ard_3-2-1_091078_2022-03-09_final.stac-item
2022-04-13 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-04-13_final.stac-item
2022-04-27 09:24:14	ga_ls9c_ard_3-2-1_091079_2022-04-26_final.stac-item
2022-05-04 09:28:47	ga_ls9c_ard_3-2-1_092075_2022-05-03_final.stac-item
2022-05-21 11:50:19	ga_ls9c_ard_3-2-1_115074_2022-05-21_final.stac-item
2022-05-26 10:28:46	ga_ls9c_ard_3-2-1_102071_2022-05-26_final.stac-item
2022-08-04 11:31:34	ga_ls9c_ard_3-2-1_112072_2022-08-04_final.stac-item
2022-08-07 10:25:37	ga_ls9c_ard_3-2-1_101077_2022-08-07_final.stac-item
2022-08-25 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-08-25_final.stac-item
2022-09-01 10:20:20	ga_ls9c_ard_3-2-1_100079_2022-09-01_final.stac-item
2022-10-02 11:12:53	ga_ls9c_ard_3-2-1_109071_2022-10-02_final.stac-item
2022-10-04 09:22:26	ga_ls9c_ard_3-2-1_091073_2022-10-03_final.stac-item
2022-10-12 10:13:32	ga_ls9c_ard_3-2-1_099077_2022-10-12_final.stac-item
2022-10-20 11:00:13	ga_ls9c_ard_3-2-1_107070_2022-10-20_final.stac-item
2022-10-27 11:07:36	ga_ls9c_ard_3-2-1_108073_2022-10-27_final.stac-item
2022-10-28 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-10-28_final.stac-item
2023-03-13 09:23:50	ga_ls9c_ard_3-2-1_091077_2023-03-12_final.stac-item
2023-04-14 09:27:31	ga_ls9c_ard_3-2-1_091087_2023-04-13_final.stac-item
2023-05-06 10:27:31	ga_ls9c_ard_3-2-1_101083_2023-05-06_final.stac-item
2023-05-18 10:46:35	ga_ls9c_ard_3-2-1_105069_2023-05-18_final.stac-item
2023-05-31 10:20:46	ga_ls9c_ard_3-2-1_100082_2023-05-31_final.stac-item
2023-07-01 09:39:30	ga_ls9c_ard_3-2-1_093087_2023-07-01_final.stac-item
2023-07-15 11:26:05	ga_ls9c_ard_3-2-1_111075_2023-07-15_final.stac-item
2023-08-25 11:20:11	ga_ls9c_ard_3-2-1_110075_2023-08-25_final.stac-item
2023-09-23 10:49:03	ga_ls9c_ard_3-2-1_105074_2023-09-23_final.stac-item
2023-09-28 11:07:32	ga_ls9c_ard_3-2-1_108074_2023-09-28_final.stac-item
2023-10-27 10:36:04	ga_ls9c_ard_3-2-1_103072_2023-10-27_final.stac-item
2023-11-13 09:40:48	ga_ls9c_ard_3-2-1_094073_2023-11-13_final.stac-item
2023-11-29 11:24:12	ga_ls9c_ard_3-2-1_110084_2023-11-29_final.stac-item
2023-12-04 11:42:42	ga_ls9c_ard_3-2-1_113084_2023-12-04_final.stac-item
2023-12-05 09:07:23	ga_ls9c_ard_3-2-1_088082_2023-12-04_final.stac-item
2023-12-14 10:34:33	ga_ls9c_ard_3-2-1_103068_2023-12-14_final.stac-item
2023-12-18 10:11:03	ga_ls9c_ard_3-2-1_099071_2023-12-18_final.stac-item
2024-02-05 10:55:30	ga_ls9c_ard_3-2-1_106074_2024-02-05_final.stac-item
2024-02-20 10:13:40	ga_ls9c_ard_3-2-1_099078_2024-02-20_final.stac-item
2024-03-11 11:26:40	ga_ls9c_ard_3-2-1_111075_2024-03-11_final.stac-item
2024-03-12 10:29:02	ga_ls9c_ard_3-2-1_102070_2024-03-12_final.stac-item
2024-03-14 10:17:52	ga_ls9c_ard_3-2-1_100073_2024-03-14_final.stac-item
2024-03-31 11:01:22	ga_ls9c_ard_3-2-1_107074_2024-03-31_final.stac-item
2024-04-18 10:49:14	ga_ls9c_ard_3-2-1_105075_2024-04-18_final.stac-item
2024-04-19 09:52:47	ga_ls9c_ard_3-2-1_096073_2024-04-19_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years