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

44 results

Time (local)	Label
2021-12-04 09:22:06	ga_ls9c_ard_3-2-1_091072_2021-12-03_final.stac-item
2021-12-23 11:31:45	ga_ls9c_ard_3-2-1_112072_2021-12-23_final.stac-item
2022-01-10 11:18:33	ga_ls9c_ard_3-2-1_110070_2022-01-10_final.stac-item
2022-02-22 09:23:00	ga_ls9c_ard_3-2-1_091075_2022-02-21_final.stac-item
2022-03-09 10:19:20	ga_ls9c_ard_3-2-1_100077_2022-03-09_final.stac-item
2022-03-19 10:55:35	ga_ls9c_ard_3-2-1_106075_2022-03-19_final.stac-item
2022-04-03 10:08:40	ga_ls9c_ard_3-2-1_099066_2022-04-03_final.stac-item
2022-04-06 09:07:28	ga_ls9c_ard_3-2-1_088083_2022-04-05_final.stac-item
2022-06-01 09:56:54	ga_ls9c_ard_3-2-1_096084_2022-06-01_final.stac-item
2022-06-16 10:49:02	ga_ls9c_ard_3-2-1_105075_2022-06-16_final.stac-item
2022-07-09 09:21:20	ga_ls9c_ard_3-2-1_090087_2022-07-08_final.stac-item
2022-08-03 10:49:05	ga_ls9c_ard_3-2-1_105074_2022-08-03_final.stac-item
2022-08-06 11:18:26	ga_ls9c_ard_3-2-1_110070_2022-08-06_final.stac-item
2022-08-16 10:22:18	ga_ls9c_ard_3-2-1_100084_2022-08-16_final.stac-item
2022-09-18 09:27:59	ga_ls9c_ard_3-2-1_091087_2022-09-17_final.stac-item
2022-10-14 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-14_final.stac-item
2022-10-18 11:14:34	ga_ls9c_ard_3-2-1_109075_2022-10-18_final.stac-item
2022-11-12 09:29:08	ga_ls9c_ard_3-2-1_092074_2022-11-11_final.stac-item
2022-11-21 09:26:56	ga_ls9c_ard_3-2-1_091084_2022-11-20_final.stac-item
2022-12-28 09:41:03	ga_ls9c_ard_3-2-1_094073_2022-12-28_final.stac-item
2023-01-19 10:40:44	ga_ls9c_ard_3-2-1_104068_2023-01-19_final.stac-item
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final.stac-item
2023-03-06 09:17:18	ga_ls9c_ard_3-2-1_090076_2023-03-05_final.stac-item
2023-03-20 09:28:47	ga_ls9c_ard_3-2-1_092074_2023-03-19_final.stac-item
2023-04-22 10:10:34	ga_ls9c_ard_3-2-1_099071_2023-04-22_final.stac-item
2023-05-07 09:28:19	ga_ls9c_ard_3-2-1_092074_2023-05-06_final.stac-item
2023-05-25 09:16:10	ga_ls9c_ard_3-2-1_090075_2023-05-24_final.stac-item
2023-06-06 09:43:39	ga_ls9c_ard_3-2-1_094082_2023-06-06_final.stac-item
2023-07-11 10:13:06	ga_ls9c_ard_3-2-1_099078_2023-07-11_final.stac-item
2023-09-08 09:57:24	ga_ls9c_ard_3-2-1_096084_2023-09-08_final.stac-item
2023-09-19 11:17:48	ga_ls9c_ard_3-2-1_109084_2023-09-19_final.stac-item
2023-10-31 10:13:17	ga_ls9c_ard_3-2-1_099077_2023-10-31_final.stac-item
2023-11-08 11:01:32	ga_ls9c_ard_3-2-1_107074_2023-11-08_final.stac-item
2023-11-10 10:46:47	ga_ls9c_ard_3-2-1_105068_2023-11-10_final.stac-item
2023-12-02 10:10:13	ga_ls9c_ard_3-2-1_099069_2023-12-02_final.stac-item
2024-01-21 09:59:48	ga_ls9c_ard_3-2-1_097074_2024-01-21_final.stac-item
2024-02-13 10:09:37	ga_ls9c_ard_3-2-1_098083_2024-02-13_final.stac-item
2024-02-14 09:10:23	ga_ls9c_ard_3-2-1_089074_2024-02-13_final.stac-item
2024-02-20 10:10:04	ga_ls9c_ard_3-2-1_099069_2024-02-20_final.stac-item
2024-03-09 09:58:57	ga_ls9c_ard_3-2-1_097072_2024-03-09_final.stac-item
2024-03-17 10:46:46	ga_ls9c_ard_3-2-1_105068_2024-03-17_final.stac-item
2024-04-03 09:57:47	ga_ls9c_ard_3-2-1_096085_2024-04-03_final.stac-item
2024-04-19 09:52:23	ga_ls9c_ard_3-2-1_096072_2024-04-19_final.stac-item
2024-04-24 10:12:44	ga_ls9c_ard_3-2-1_099077_2024-04-24_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