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

58 results

Time (local)	Label
2021-11-12 10:56:37	ga_ls9c_ard_3-2-1_106070_2021-11-12_final.stac-item
2021-12-22 10:52:29	ga_ls9c_ard_3-2-1_105082_2021-12-22_final.stac-item
2022-01-23 10:47:41	ga_ls9c_ard_3-2-1_105070_2022-01-23_final.stac-item
2022-01-30 09:17:46	ga_ls9c_ard_3-2-1_090077_2022-01-29_final.stac-item
2022-01-31 10:02:38	ga_ls9c_ard_3-2-1_097081_2022-01-31_final.stac-item
2022-03-21 09:06:19	ga_ls9c_ard_3-2-1_088080_2022-03-20_final.stac-item
2022-04-06 10:45:57	ga_ls9c_ard_3-2-1_104082_2022-04-06_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-09 11:14:26	ga_ls9c_ard_3-2-1_109076_2022-04-09_final.stac-item
2022-04-10 10:19:12	ga_ls9c_ard_3-2-1_100077_2022-04-10_final.stac-item
2022-04-25 11:13:53	ga_ls9c_ard_3-2-1_109075_2022-04-25_final.stac-item
2022-04-25 11:14:17	ga_ls9c_ard_3-2-1_109076_2022-04-25_final.stac-item
2022-05-06 10:52:29	ga_ls9c_ard_3-2-1_106068_2022-05-06_final.stac-item
2022-05-12 10:18:56	ga_ls9c_ard_3-2-1_100077_2022-05-12_final.stac-item
2022-05-27 11:14:02	ga_ls9c_ard_3-2-1_109076_2022-05-27_final.stac-item
2022-05-28 10:18:49	ga_ls9c_ard_3-2-1_100077_2022-05-28_final.stac-item
2022-07-07 11:07:47	ga_ls9c_ard_3-2-1_108075_2022-07-07_final.stac-item
2022-08-15 11:14:43	ga_ls9c_ard_3-2-1_109076_2022-08-15_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-16 11:24:08	ga_ls9c_ard_3-2-1_111068_2022-10-16_final.stac-item
2022-10-19 10:17:21	ga_ls9c_ard_3-2-1_100071_2022-10-19_final.stac-item
2022-10-29 10:59:13	ga_ls9c_ard_3-2-1_106083_2022-10-29_final.stac-item
2022-11-03 11:14:32	ga_ls9c_ard_3-2-1_109075_2022-11-03_final.stac-item
2022-11-20 10:17:22	ga_ls9c_ard_3-2-1_100071_2022-11-20_final.stac-item
2022-11-29 10:10:21	ga_ls9c_ard_3-2-1_099069_2022-11-29_final.stac-item
2022-12-07 09:26:55	ga_ls9c_ard_3-2-1_091084_2022-12-06_final.stac-item
2023-01-20 09:52:17	ga_ls9c_ard_3-2-1_095086_2023-01-20_final.stac-item
2023-01-31 11:08:00	ga_ls9c_ard_3-2-1_108074_2023-01-31_final.stac-item
2023-02-10 10:10:15	ga_ls9c_ard_3-2-1_098084_2023-02-10_final.stac-item
2023-02-25 11:05:13	ga_ls9c_ard_3-2-1_107083_2023-02-25_final.stac-item
2023-06-29 11:23:07	ga_ls9c_ard_3-2-1_111068_2023-06-29_final.stac-item
2023-07-18 10:18:54	ga_ls9c_ard_3-2-1_100077_2023-07-18_final.stac-item
2023-07-21 09:10:55	ga_ls9c_ard_3-2-1_089077_2023-07-20_final.stac-item
2023-08-10 10:22:27	ga_ls9c_ard_3-2-1_101070_2023-08-10_final.stac-item
2023-08-19 10:19:05	ga_ls9c_ard_3-2-1_100077_2023-08-19_final.stac-item
2023-09-17 11:23:46	ga_ls9c_ard_3-2-1_111068_2023-09-17_final.stac-item
2023-09-23 09:11:22	ga_ls9c_ard_3-2-1_089077_2023-09-22_final.stac-item
2023-10-02 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-10-01_final.stac-item
2023-10-06 10:19:25	ga_ls9c_ard_3-2-1_100077_2023-10-06_final.stac-item
2023-10-23 09:23:07	ga_ls9c_ard_3-2-1_091075_2023-10-22_final.stac-item
2023-11-10 10:52:22	ga_ls9c_ard_3-2-1_105082_2023-11-10_final.stac-item
2023-11-26 09:12:49	ga_ls9c_ard_3-2-1_089080_2023-11-25_final.stac-item
2024-01-19 10:09:24	ga_ls9c_ard_3-2-1_099067_2024-01-19_final.stac-item
2024-01-29 09:10:23	ga_ls9c_ard_3-2-1_089074_2024-01-28_final.stac-item
2024-02-06 09:59:53	ga_ls9c_ard_3-2-1_097074_2024-02-06_final.stac-item
2024-02-07 10:42:44	ga_ls9c_ard_3-2-1_104073_2024-02-07_final.stac-item
2024-02-11 10:20:00	ga_ls9c_ard_3-2-1_100078_2024-02-11_final.stac-item
2024-02-18 10:23:16	ga_ls9c_ard_3-2-1_101071_2024-02-18_final.stac-item
2024-02-19 11:05:43	ga_ls9c_ard_3-2-1_108069_2024-02-19_final.stac-item
2024-02-19 11:07:43	ga_ls9c_ard_3-2-1_108074_2024-02-19_final.stac-item
2024-02-19 11:08:06	ga_ls9c_ard_3-2-1_108075_2024-02-19_final.stac-item
2024-02-26 09:35:21	ga_ls9c_ard_3-2-1_093075_2024-02-26_final.stac-item
2024-03-11 11:27:03	ga_ls9c_ard_3-2-1_111076_2024-03-11_final.stac-item
2024-03-26 09:07:12	ga_ls9c_ard_3-2-1_088082_2024-03-25_final.stac-item
2024-03-29 09:40:26	ga_ls9c_ard_3-2-1_093088_2024-03-29_final.stac-item
2024-04-02 09:11:20	ga_ls9c_ard_3-2-1_089077_2024-04-01_final.stac-item
2024-04-14 09:33:57	ga_ls9c_ard_3-2-1_093072_2024-04-14_final.stac-item
2024-04-18 10:46:26	ga_ls9c_ard_3-2-1_105068_2024-04-18_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