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

61 results

Time (local)	Label
2021-11-10 09:37:54	ga_ls9c_ard_3-2-1_094073_2021-11-10_final.stac-item
2021-11-12 09:19:57	ga_ls9c_ard_3-2-1_091075_2021-11-11_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2022-01-20 10:19:34	ga_ls9c_ard_3-2-1_100077_2022-01-20_final.stac-item
2022-01-22 10:03:13	ga_ls9c_ard_3-2-1_098067_2022-01-22_final.stac-item
2022-01-25 10:34:55	ga_ls9c_ard_3-2-1_103069_2022-01-25_final.stac-item
2022-02-22 09:21:48	ga_ls9c_ard_3-2-1_091072_2022-02-21_final.stac-item
2022-03-10 09:22:07	ga_ls9c_ard_3-2-1_091073_2022-03-09_final.stac-item
2022-04-03 11:52:45	ga_ls9c_ard_3-2-1_115079_2022-04-03_final.stac-item
2022-04-07 11:24:49	ga_ls9c_ard_3-2-1_111071_2022-04-07_final.stac-item
2022-04-09 09:35:09	ga_ls9c_ard_3-2-1_093075_2022-04-09_final.stac-item
2022-05-15 09:10:55	ga_ls9c_ard_3-2-1_089077_2022-05-14_final.stac-item
2022-05-21 11:52:43	ga_ls9c_ard_3-2-1_115080_2022-05-21_final.stac-item
2022-05-22 09:16:13	ga_ls9c_ard_3-2-1_090075_2022-05-21_final.stac-item
2022-06-03 09:39:21	ga_ls9c_ard_3-2-1_094071_2022-06-03_final.stac-item
2022-06-16 10:49:26	ga_ls9c_ard_3-2-1_105076_2022-06-16_final.stac-item
2022-06-22 10:08:56	ga_ls9c_ard_3-2-1_099067_2022-06-22_final.stac-item
2022-06-30 09:22:45	ga_ls9c_ard_3-2-1_091075_2022-06-29_final.stac-item
2022-07-02 10:52:28	ga_ls9c_ard_3-2-1_105083_2022-07-02_final.stac-item
2022-08-09 10:10:05	ga_ls9c_ard_3-2-1_099069_2022-08-09_final.stac-item
2022-08-09 10:13:40	ga_ls9c_ard_3-2-1_099078_2022-08-09_final.stac-item
2022-08-29 11:24:20	ga_ls9c_ard_3-2-1_111069_2022-08-29_final.stac-item
2022-09-02 11:05:35	ga_ls9c_ard_3-2-1_107084_2022-09-02_final.stac-item
2022-09-10 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-09-10_final.stac-item
2022-11-19 09:34:55	ga_ls9c_ard_3-2-1_093073_2022-11-19_final.stac-item
2022-11-29 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-11-29_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_final.stac-item
2023-01-10 09:15:21	ga_ls9c_ard_3-2-1_089086_2023-01-09_final.stac-item
2023-01-31 09:29:55	ga_ls9c_ard_3-2-1_092076_2023-01-30_final.stac-item
2023-02-11 09:16:37	ga_ls9c_ard_3-2-1_089089_2023-02-10_final.stac-item
2023-02-22 10:33:34	ga_ls9c_ard_3-2-1_102081_2023-02-22_final.stac-item
2023-03-09 09:46:09	ga_ls9c_ard_3-2-1_095071_2023-03-09_final.stac-item
2023-03-29 09:22:02	ga_ls9c_ard_3-2-1_091073_2023-03-28_final.stac-item
2023-04-06 11:53:09	ga_ls9c_ard_3-2-1_115080_2023-04-06_final.stac-item
2023-05-05 11:17:33	ga_ls9c_ard_3-2-1_110069_2023-05-05_final.stac-item
2023-05-16 09:22:05	ga_ls9c_ard_3-2-1_091074_2023-05-15_final.stac-item
2023-05-21 09:45:45	ga_ls9c_ard_3-2-1_094087_2023-05-21_final.stac-item
2023-05-25 10:55:03	ga_ls9c_ard_3-2-1_106075_2023-05-25_final.stac-item
2023-06-09 11:52:37	ga_ls9c_ard_3-2-1_115080_2023-06-09_final.stac-item
2023-07-05 10:50:55	ga_ls9c_ard_3-2-1_105080_2023-07-05_final.stac-item
2023-07-12 09:16:17	ga_ls9c_ard_3-2-1_090075_2023-07-11_final.stac-item
2023-07-28 10:55:13	ga_ls9c_ard_3-2-1_106075_2023-07-28_final.stac-item
2023-08-13 09:16:28	ga_ls9c_ard_3-2-1_090075_2023-08-12_final.stac-item
2023-08-16 09:45:46	ga_ls9c_ard_3-2-1_095071_2023-08-16_final.stac-item
2023-10-03 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-10-03_final.stac-item
2023-10-15 10:10:09	ga_ls9c_ard_3-2-1_099069_2023-10-15_final.stac-item
2023-10-23 09:23:07	ga_ls9c_ard_3-2-1_091075_2023-10-22_final.stac-item
2023-11-08 09:28:14	ga_ls9c_ard_3-2-1_091088_2023-11-07_final.stac-item
2023-11-17 10:58:58	ga_ls9c_ard_3-2-1_106083_2023-11-17_final.stac-item
2023-12-18 10:09:28	ga_ls9c_ard_3-2-1_099067_2023-12-18_final.stac-item
2023-12-27 10:03:17	ga_ls9c_ard_3-2-1_098067_2023-12-27_final.stac-item
2024-01-03 10:10:59	ga_ls9c_ard_3-2-1_099071_2024-01-03_final.stac-item
2024-01-16 09:40:30	ga_ls9c_ard_3-2-1_094072_2024-01-16_final.stac-item
2024-02-13 10:03:14	ga_ls9c_ard_3-2-1_098067_2024-02-13_final.stac-item
2024-02-20 10:09:40	ga_ls9c_ard_3-2-1_099068_2024-02-20_final.stac-item
2024-02-26 09:34:33	ga_ls9c_ard_3-2-1_093073_2024-02-26_final.stac-item
2024-02-27 11:58:19	ga_ls9c_ard_3-2-1_116077_2024-02-27_final.stac-item
2024-02-29 10:05:29	ga_ls9c_ard_3-2-1_098073_2024-02-29_final.stac-item
2024-03-13 09:34:12	ga_ls9c_ard_3-2-1_093072_2024-03-13_final.stac-item
2024-04-08 10:09:07	ga_ls9c_ard_3-2-1_099067_2024-04-08_final.stac-item
2024-04-08 10:09:07	ga_ls9c_ard_3-2-1_099067_2024-04-08_interim.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