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

45 results

Time (local)	Label
2021-12-05 10:09:44	ga_ls9c_ard_3-2-1_098083_2021-12-05_final.stac-item
2022-01-05 09:22:45	ga_ls9c_ard_3-2-1_091074_2022-01-04_final.stac-item
2022-01-24 09:57:39	ga_ls9c_ard_3-2-1_096084_2022-01-24_final.stac-item
2022-03-03 09:20:42	ga_ls9c_ard_3-2-1_090085_2022-03-02_final.stac-item
2022-03-30 10:35:47	ga_ls9c_ard_3-2-1_103072_2022-03-30_final.stac-item
2022-04-13 09:12:23	ga_ls9c_ard_3-2-1_089080_2022-04-12_final.stac-item
2022-04-24 10:28:13	ga_ls9c_ard_3-2-1_102069_2022-04-24_final.stac-item
2022-06-06 10:09:28	ga_ls9c_ard_3-2-1_099069_2022-06-06_final.stac-item
2022-07-16 09:22:18	ga_ls9c_ard_3-2-1_091074_2022-07-15_final.stac-item
2022-08-01 10:59:50	ga_ls9c_ard_3-2-1_107070_2022-08-01_final.stac-item
2022-09-05 11:36:05	ga_ls9c_ard_3-2-1_112083_2022-09-05_final.stac-item
2022-10-12 10:09:32	ga_ls9c_ard_3-2-1_099067_2022-10-12_final.stac-item
2022-10-12 10:10:44	ga_ls9c_ard_3-2-1_099070_2022-10-12_final.stac-item
2022-11-01 09:46:50	ga_ls9c_ard_3-2-1_095072_2022-11-01_final.stac-item
2022-11-29 10:16:20	ga_ls9c_ard_3-2-1_099084_2022-11-29_final.stac-item
2022-12-19 11:26:07	ga_ls9c_ard_3-2-1_111073_2022-12-19_final.stac-item
2022-12-21 11:18:08	ga_ls9c_ard_3-2-1_109084_2022-12-21_final.stac-item
2022-12-24 10:04:08	ga_ls9c_ard_3-2-1_098069_2022-12-24_final.stac-item
2023-01-24 09:24:02	ga_ls9c_ard_3-2-1_091077_2023-01-23_final.stac-item
2023-02-07 11:14:38	ga_ls9c_ard_3-2-1_109075_2023-02-07_final.stac-item
2023-03-06 10:58:35	ga_ls9c_ard_3-2-1_106082_2023-03-06_final.stac-item
2023-04-09 09:07:27	ga_ls9c_ard_3-2-1_088083_2023-04-08_final.stac-item
2023-06-25 10:08:51	ga_ls9c_ard_3-2-1_099068_2023-06-25_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-07-28 10:55:37	ga_ls9c_ard_3-2-1_106076_2023-07-28_final.stac-item
2023-08-02 11:14:14	ga_ls9c_ard_3-2-1_109076_2023-08-02_final.stac-item
2023-08-05 10:02:42	ga_ls9c_ard_3-2-1_098067_2023-08-05_final.stac-item
2023-08-19 10:18:41	ga_ls9c_ard_3-2-1_100076_2023-08-19_final.stac-item
2023-08-29 09:16:37	ga_ls9c_ard_3-2-1_090075_2023-08-28_final.stac-item
2023-09-08 11:32:17	ga_ls9c_ard_3-2-1_112074_2023-09-08_final.stac-item
2023-09-25 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-25_final.stac-item
2023-10-06 11:57:30	ga_ls9c_ard_3-2-1_116075_2023-10-06_final.stac-item
2023-10-06 11:57:54	ga_ls9c_ard_3-2-1_116076_2023-10-06_final.stac-item
2023-10-16 09:16:56	ga_ls9c_ard_3-2-1_090075_2023-10-15_final.stac-item
2023-11-01 09:17:39	ga_ls9c_ard_3-2-1_090077_2023-10-31_final.stac-item
2023-11-21 10:33:31	ga_ls9c_ard_3-2-1_102081_2023-11-21_final.stac-item
2023-11-26 09:11:38	ga_ls9c_ard_3-2-1_089077_2023-11-25_final.stac-item
2023-12-05 09:06:36	ga_ls9c_ard_3-2-1_088080_2023-12-04_final.stac-item
2023-12-06 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-12-06_final.stac-item
2024-02-21 10:55:18	ga_ls9c_ard_3-2-1_106074_2024-02-21_final.stac-item
2024-03-03 10:39:37	ga_ls9c_ard_3-2-1_103081_2024-03-03_final.stac-item
2024-03-24 10:53:18	ga_ls9c_ard_3-2-1_106069_2024-03-24_final.stac-item
2024-03-27 09:52:02	ga_ls9c_ard_3-2-1_095086_2024-03-27_final.stac-item
2024-04-10 09:57:56	ga_ls9c_ard_3-2-1_097070_2024-04-10_final.stac-item
2024-04-30 09:34:03	ga_ls9c_ard_3-2-1_093073_2024-04-30_nrt.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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years