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
2021-12-05 10:10:32	ga_ls9c_ard_3-2-1_098085_2021-12-05_final.stac-item
2021-12-11 09:28:12	ga_ls9c_ard_3-2-1_092072_2021-12-10_final.stac-item
2021-12-16 09:52:16	ga_ls9c_ard_3-2-1_095086_2021-12-16_final.stac-item
2022-01-12 11:11:22	ga_ls9c_ard_3-2-1_108083_2022-01-12_final.stac-item
2022-01-28 11:07:25	ga_ls9c_ard_3-2-1_108073_2022-01-28_final.stac-item
2022-02-09 09:52:50	ga_ls9c_ard_3-2-1_096072_2022-02-09_final.stac-item
2022-02-22 11:03:53	ga_ls9c_ard_3-2-1_107080_2022-02-22_final.stac-item
2022-03-01 09:27:53	ga_ls9c_ard_3-2-1_092072_2022-02-28_final.stac-item
2022-03-23 10:29:14	ga_ls9c_ard_3-2-1_102071_2022-03-23_final.stac-item
2022-04-07 09:51:55	ga_ls9c_ard_3-2-1_095086_2022-04-07_final.stac-item
2022-05-07 10:03:15	ga_ls9c_ard_3-2-1_097084_2022-05-07_final.stac-item
2022-05-24 10:40:20	ga_ls9c_ard_3-2-1_104069_2022-05-24_final.stac-item
2022-06-15 10:04:10	ga_ls9c_ard_3-2-1_098071_2022-06-15_final.stac-item
2022-07-08 10:15:45	ga_ls9c_ard_3-2-1_099084_2022-07-08_final.stac-item
2022-08-03 09:14:36	ga_ls9c_ard_3-2-1_089085_2022-08-02_final.stac-item
2022-09-03 10:05:11	ga_ls9c_ard_3-2-1_098072_2022-09-03_final.stac-item
2022-10-10 10:26:16	ga_ls9c_ard_3-2-1_101078_2022-10-10_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-29 10:55:14	ga_ls9c_ard_3-2-1_106073_2022-10-29_final.stac-item
2022-11-16 09:08:00	ga_ls9c_ard_3-2-1_088083_2022-11-15_final.stac-item
2022-12-16 10:54:26	ga_ls9c_ard_3-2-1_106071_2022-12-16_final.stac-item
2022-12-24 11:47:01	ga_ls9c_ard_3-2-1_114079_2022-12-24_final.stac-item
2022-12-25 09:12:07	ga_ls9c_ard_3-2-1_089078_2022-12-24_final.stac-item
2023-01-03 10:40:53	ga_ls9c_ard_3-2-1_104068_2023-01-03_final.stac-item
2023-02-14 11:23:34	ga_ls9c_ard_3-2-1_110082_2023-02-14_final.stac-item
2023-03-05 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-03-05_final.stac-item
2023-03-15 09:16:16	ga_ls9c_ard_3-2-1_089089_2023-03-14_final.stac-item
2023-04-02 10:38:12	ga_ls9c_ard_3-2-1_103078_2023-04-02_final.stac-item
2023-08-03 10:18:37	ga_ls9c_ard_3-2-1_100076_2023-08-03_final.stac-item
2023-08-23 11:36:06	ga_ls9c_ard_3-2-1_112084_2023-08-23_final.stac-item
2023-09-29 10:09:08	ga_ls9c_ard_3-2-1_099067_2023-09-29_final.stac-item
2023-10-01 10:03:36	ga_ls9c_ard_3-2-1_097084_2023-10-01_final.stac-item
2023-10-17 09:59:00	ga_ls9c_ard_3-2-1_097072_2023-10-17_final.stac-item
2023-12-19 09:21:02	ga_ls9c_ard_3-2-1_090085_2023-12-18_final.stac-item
2023-12-31 11:21:24	ga_ls9c_ard_3-2-1_110077_2023-12-31_final.stac-item
2024-01-10 10:18:22	ga_ls9c_ard_3-2-1_100074_2024-01-10_final.stac-item
2024-01-11 11:01:38	ga_ls9c_ard_3-2-1_107074_2024-01-11_final.stac-item
2024-01-29 09:14:47	ga_ls9c_ard_3-2-1_089085_2024-01-28_final.stac-item
2024-02-05 09:18:13	ga_ls9c_ard_3-2-1_090078_2024-02-04_final.stac-item
2024-02-23 09:06:24	ga_ls9c_ard_3-2-1_088080_2024-02-22_final.stac-item
2024-03-15 09:27:02	ga_ls9c_ard_3-2-1_091085_2024-03-14_final.stac-item
2024-03-17 09:16:16	ga_ls9c_ard_3-2-1_089089_2024-03-16_final.stac-item
2024-03-20 11:18:27	ga_ls9c_ard_3-2-1_110070_2024-03-20_final.stac-item
2024-04-16 09:22:45	ga_ls9c_ard_3-2-1_091075_2024-04-15_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