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

42 results

Time (local)	Label
2021-12-12 11:53:07	ga_ls9c_ard_3-2-1_115079_2021-12-12_final.stac-item
2021-12-21 10:10:01	ga_ls9c_ard_3-2-1_098084_2021-12-21_final.stac-item
2022-01-01 11:25:58	ga_ls9c_ard_3-2-1_111073_2022-01-01_final.stac-item
2022-01-21 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-21_final.stac-item
2022-01-25 10:40:06	ga_ls9c_ard_3-2-1_103082_2022-01-25_final.stac-item
2022-01-26 11:18:59	ga_ls9c_ard_3-2-1_110071_2022-01-26_final.stac-item
2022-02-08 09:10:22	ga_ls9c_ard_3-2-1_089074_2022-02-07_final.stac-item
2022-03-10 09:28:54	ga_ls9c_ard_3-2-1_091090_2022-03-09_final.stac-item
2022-04-09 11:14:02	ga_ls9c_ard_3-2-1_109075_2022-04-09_final.stac-item
2022-05-08 09:06:49	ga_ls9c_ard_3-2-1_088082_2022-05-07_final.stac-item
2022-05-16 11:31:03	ga_ls9c_ard_3-2-1_112072_2022-05-16_final.stac-item
2022-05-31 09:11:14	ga_ls9c_ard_3-2-1_089078_2022-05-30_final.stac-item
2022-06-22 10:10:31	ga_ls9c_ard_3-2-1_099071_2022-06-22_final.stac-item
2022-06-26 09:51:53	ga_ls9c_ard_3-2-1_095086_2022-06-26_final.stac-item
2022-07-12 09:51:48	ga_ls9c_ard_3-2-1_095086_2022-07-12_final.stac-item
2022-07-12 11:23:30	ga_ls9c_ard_3-2-1_111068_2022-07-12_final.stac-item
2022-07-16 09:21:54	ga_ls9c_ard_3-2-1_091073_2022-07-15_final.stac-item
2022-08-22 09:46:26	ga_ls9c_ard_3-2-1_094087_2022-08-22_final.stac-item
2022-08-25 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-08-25_final.stac-item
2022-10-07 09:57:43	ga_ls9c_ard_3-2-1_096084_2022-10-07_final.stac-item
2022-10-21 10:05:00	ga_ls9c_ard_3-2-1_098071_2022-10-21_final.stac-item
2022-11-05 09:24:05	ga_ls9c_ard_3-2-1_091077_2022-11-04_final.stac-item
2022-11-21 11:00:38	ga_ls9c_ard_3-2-1_107071_2022-11-21_final.stac-item
2022-12-08 10:03:00	ga_ls9c_ard_3-2-1_098066_2022-12-08_final.stac-item
2022-12-24 10:04:08	ga_ls9c_ard_3-2-1_098069_2022-12-24_final.stac-item
2023-01-18 11:38:47	ga_ls9c_ard_3-2-1_113074_2023-01-18_final.stac-item
2023-01-31 11:08:24	ga_ls9c_ard_3-2-1_108075_2023-01-31_final.stac-item
2023-02-17 10:09:10	ga_ls9c_ard_3-2-1_099066_2023-02-17_final.stac-item
2023-03-06 09:17:42	ga_ls9c_ard_3-2-1_090077_2023-03-05_final.stac-item
2023-04-03 11:23:51	ga_ls9c_ard_3-2-1_110084_2023-04-03_final.stac-item
2023-04-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2023-04-23_final.stac-item
2023-05-23 09:28:10	ga_ls9c_ard_3-2-1_092074_2023-05-22_final.stac-item
2023-05-28 11:23:58	ga_ls9c_ard_3-2-1_111070_2023-05-28_final.stac-item
2023-05-28 11:24:22	ga_ls9c_ard_3-2-1_111071_2023-05-28_final.stac-item
2023-07-08 11:17:52	ga_ls9c_ard_3-2-1_110070_2023-07-08_final.stac-item
2023-08-27 09:34:09	ga_ls9c_ard_3-2-1_092088_2023-08-27_final.stac-item
2023-09-01 11:25:38	ga_ls9c_ard_3-2-1_111073_2023-09-01_final.stac-item
2023-10-10 11:32:26	ga_ls9c_ard_3-2-1_112074_2023-10-10_final.stac-item
2023-10-14 11:06:10	ga_ls9c_ard_3-2-1_108070_2023-10-14_final.stac-item
2023-12-02 10:10:13	ga_ls9c_ard_3-2-1_099069_2023-12-02_final.stac-item
2024-02-05 10:55:30	ga_ls9c_ard_3-2-1_106074_2024-02-05_final.stac-item
2024-05-01 10:16:31	ga_ls9c_ard_3-2-1_100071_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years