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

50 results

Time (local)	Label
2021-11-13 09:57:07	ga_ls9c_ard_3-2-1_097068_2021-11-13_final.stac-item
2021-12-16 11:23:58	ga_ls9c_ard_3-2-1_111068_2021-12-16_final.stac-item
2022-01-05 09:23:09	ga_ls9c_ard_3-2-1_091075_2022-01-04_final.stac-item
2022-01-23 09:11:35	ga_ls9c_ard_3-2-1_089077_2022-01-22_final.stac-item
2022-01-25 10:39:43	ga_ls9c_ard_3-2-1_103081_2022-01-25_final.stac-item
2022-01-30 09:22:10	ga_ls9c_ard_3-2-1_090088_2022-01-29_final.stac-item
2022-02-14 10:09:44	ga_ls9c_ard_3-2-1_099068_2022-02-14_final.stac-item
2022-02-15 09:21:41	ga_ls9c_ard_3-2-1_090087_2022-02-14_final.stac-item
2022-03-08 11:13:45	ga_ls9c_ard_3-2-1_109074_2022-03-08_final.stac-item
2022-03-28 09:14:51	ga_ls9c_ard_3-2-1_089086_2022-03-27_final.stac-item
2022-05-05 10:10:26	ga_ls9c_ard_3-2-1_099071_2022-05-05_final.stac-item
2022-05-25 09:48:42	ga_ls9c_ard_3-2-1_095079_2022-05-25_final.stac-item
2022-06-11 10:32:49	ga_ls9c_ard_3-2-1_102081_2022-06-11_final.stac-item
2022-06-13 11:57:47	ga_ls9c_ard_3-2-1_116077_2022-06-13_final.stac-item
2022-06-15 10:02:34	ga_ls9c_ard_3-2-1_098067_2022-06-15_final.stac-item
2022-07-09 09:21:44	ga_ls9c_ard_3-2-1_090088_2022-07-08_final.stac-item
2022-07-14 11:13:55	ga_ls9c_ard_3-2-1_109075_2022-07-14_final.stac-item
2022-07-15 10:19:06	ga_ls9c_ard_3-2-1_100077_2022-07-15_final.stac-item
2022-07-22 10:22:37	ga_ls9c_ard_3-2-1_101070_2022-07-22_final.stac-item
2022-08-09 10:09:17	ga_ls9c_ard_3-2-1_099067_2022-08-09_final.stac-item
2022-08-13 11:23:52	ga_ls9c_ard_3-2-1_111068_2022-08-13_final.stac-item
2022-08-16 10:19:30	ga_ls9c_ard_3-2-1_100077_2022-08-16_final.stac-item
2022-08-22 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-08-22_final.stac-item
2022-09-09 09:35:16	ga_ls9c_ard_3-2-1_092090_2022-09-09_final.stac-item
2022-09-13 10:45:53	ga_ls9c_ard_3-2-1_104081_2022-09-13_final.stac-item
2022-09-24 10:27:49	ga_ls9c_ard_3-2-1_101082_2022-09-24_final.stac-item
2022-09-30 11:27:39	ga_ls9c_ard_3-2-1_111077_2022-09-30_final.stac-item
2022-10-25 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-10-25_final.stac-item
2022-12-03 11:24:06	ga_ls9c_ard_3-2-1_111068_2022-12-03_final.stac-item
2022-12-06 11:59:01	ga_ls9c_ard_3-2-1_116078_2022-12-06_final.stac-item
2022-12-22 11:58:59	ga_ls9c_ard_3-2-1_116078_2022-12-22_final.stac-item
2023-01-16 10:11:06	ga_ls9c_ard_3-2-1_099071_2023-01-16_final.stac-item
2023-01-17 10:53:08	ga_ls9c_ard_3-2-1_106068_2023-01-17_final.stac-item
2023-01-23 11:58:55	ga_ls9c_ard_3-2-1_116078_2023-01-23_final.stac-item
2023-02-21 11:25:37	ga_ls9c_ard_3-2-1_111072_2023-02-21_final.stac-item
2023-04-24 09:57:48	ga_ls9c_ard_3-2-1_097070_2023-04-24_final.stac-item
2023-04-29 10:19:03	ga_ls9c_ard_3-2-1_100077_2023-04-29_final.stac-item
2023-05-02 09:11:01	ga_ls9c_ard_3-2-1_089077_2023-05-01_final.stac-item
2023-05-22 10:26:36	ga_ls9c_ard_3-2-1_101081_2023-05-22_final.stac-item
2023-06-15 09:38:33	ga_ls9c_ard_3-2-1_093085_2023-06-15_final.stac-item
2023-07-17 11:13:44	ga_ls9c_ard_3-2-1_109075_2023-07-17_final.stac-item
2023-07-31 11:23:23	ga_ls9c_ard_3-2-1_111068_2023-07-31_final.stac-item
2023-11-03 09:07:15	ga_ls9c_ard_3-2-1_088082_2023-11-02_final.stac-item
2023-11-07 08:42:35	ga_ls9c_ard_3-2-1_084082_2023-11-06_final.stac-item
2024-03-06 11:07:20	ga_ls9c_ard_3-2-1_108073_2024-03-06_final.stac-item
2024-03-14 10:19:27	ga_ls9c_ard_3-2-1_100077_2024-03-14_final.stac-item
2024-03-21 10:27:37	ga_ls9c_ard_3-2-1_101082_2024-03-21_final.stac-item
2024-04-07 11:07:56	ga_ls9c_ard_3-2-1_108075_2024-04-07_final.stac-item
2024-04-07 11:07:56	ga_ls9c_ard_3-2-1_108075_2024-04-07_interim.stac-item
2024-04-22 10:27:10	ga_ls9c_ard_3-2-1_101082_2024-04-22_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years