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

43 results

Time (local)	Label
2021-11-22 11:03:55	ga_ls9c_ard_3-2-1_107076_2021-11-22_final.stac-item
2021-11-23 11:43:05	ga_ls9c_ard_3-2-1_114074_2021-11-23_final.stac-item
2021-12-08 10:34:37	ga_ls9c_ard_3-2-1_103068_2021-12-08_final.stac-item
2022-01-05 09:23:33	ga_ls9c_ard_3-2-1_091076_2022-01-04_final.stac-item
2022-01-13 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-01-13_final.stac-item
2022-02-20 11:11:53	ga_ls9c_ard_3-2-1_109069_2022-02-20_final.stac-item
2022-03-01 09:27:53	ga_ls9c_ard_3-2-1_092072_2022-02-28_final.stac-item
2022-03-02 10:09:09	ga_ls9c_ard_3-2-1_099067_2022-03-02_final.stac-item
2022-03-06 11:24:07	ga_ls9c_ard_3-2-1_111069_2022-03-06_final.stac-item
2022-04-23 11:23:51	ga_ls9c_ard_3-2-1_111069_2022-04-23_final.stac-item
2022-04-28 10:09:29	ga_ls9c_ard_3-2-1_098084_2022-04-28_final.stac-item
2022-04-30 11:32:01	ga_ls9c_ard_3-2-1_112074_2022-04-30_final.stac-item
2022-05-05 10:08:26	ga_ls9c_ard_3-2-1_099066_2022-05-05_final.stac-item
2022-06-15 10:06:57	ga_ls9c_ard_3-2-1_098078_2022-06-15_final.stac-item
2022-07-25 09:16:40	ga_ls9c_ard_3-2-1_090075_2022-07-24_final.stac-item
2022-08-04 11:31:34	ga_ls9c_ard_3-2-1_112072_2022-08-04_final.stac-item
2022-09-08 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-09-08_final.stac-item
2022-10-03 10:19:39	ga_ls9c_ard_3-2-1_100077_2022-10-03_final.stac-item
2022-12-07 11:02:12	ga_ls9c_ard_3-2-1_107075_2022-12-07_nrt.stac-item
2022-12-11 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-12-11_final.stac-item
2022-12-19 09:51:13	ga_ls9c_ard_3-2-1_095083_2022-12-19_final.stac-item
2023-01-23 10:22:25	ga_ls9c_ard_3-2-1_100084_2023-01-23_final.stac-item
2023-04-10 11:25:36	ga_ls9c_ard_3-2-1_111073_2023-04-10_final.stac-item
2023-04-22 10:13:22	ga_ls9c_ard_3-2-1_099078_2023-04-22_final.stac-item
2023-06-09 10:12:32	ga_ls9c_ard_3-2-1_099077_2023-06-09_final.stac-item
2023-06-19 10:49:08	ga_ls9c_ard_3-2-1_105076_2023-06-19_final.stac-item
2023-10-15 11:51:26	ga_ls9c_ard_3-2-1_115075_2023-10-15_final.stac-item
2023-12-03 09:22:10	ga_ls9c_ard_3-2-1_090088_2023-12-02_final.stac-item
2023-12-11 10:02:49	ga_ls9c_ard_3-2-1_098066_2023-12-11_final.stac-item
2023-12-28 10:50:08	ga_ls9c_ard_3-2-1_105076_2023-12-28_final.stac-item
2024-01-12 10:05:13	ga_ls9c_ard_3-2-1_098072_2024-01-12_final.stac-item
2024-01-16 11:19:23	ga_ls9c_ard_3-2-1_110072_2024-01-16_final.stac-item
2024-01-17 10:28:09	ga_ls9c_ard_3-2-1_101083_2024-01-17_final.stac-item
2024-01-25 09:35:27	ga_ls9c_ard_3-2-1_093075_2024-01-25_final.stac-item
2024-01-26 10:19:56	ga_ls9c_ard_3-2-1_100078_2024-01-26_final.stac-item
2024-02-04 10:14:14	ga_ls9c_ard_3-2-1_099079_2024-02-04_final.stac-item
2024-02-10 09:40:44	ga_ls9c_ard_3-2-1_093088_2024-02-10_final.stac-item
2024-03-04 09:40:48	ga_ls9c_ard_3-2-1_094073_2024-03-04_final.stac-item
2024-03-04 09:40:48	ga_ls9c_ard_3-2-1_094073_2024-03-04_interim.stac-item
2024-03-29 11:14:32	ga_ls9c_ard_3-2-1_109076_2024-03-29_final.stac-item
2024-04-04 10:34:15	ga_ls9c_ard_3-2-1_103068_2024-04-04_final.stac-item
2024-04-08 10:11:06	ga_ls9c_ard_3-2-1_099072_2024-04-08_final.stac-item
2024-04-25 10:55:12	ga_ls9c_ard_3-2-1_106075_2024-04-25_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