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

53 results

Time (local)	Label
2023-11-27 09:52:30	ga_ls9c_ard_3-2-1_096071_2023-11-27_final.stac-item
2023-11-27 09:53:42	ga_ls9c_ard_3-2-1_096074_2023-11-27_final.stac-item
2023-11-27 09:54:05	ga_ls9c_ard_3-2-1_096075_2023-11-27_final.stac-item
2023-11-27 09:54:29	ga_ls9c_ard_3-2-1_096076_2023-11-27_final.stac-item
2023-11-27 09:55:17	ga_ls9c_ard_3-2-1_096078_2023-11-27_final.stac-item
2023-11-27 09:56:05	ga_ls9c_ard_3-2-1_096080_2023-11-27_final.stac-item
2023-11-27 09:57:17	ga_ls9c_ard_3-2-1_096083_2023-11-27_final.stac-item
2023-11-27 09:58:05	ga_ls9c_ard_3-2-1_096085_2023-11-27_final.stac-item
2023-11-27 09:58:29	ga_ls9c_ard_3-2-1_096086_2023-11-27_final.stac-item
2023-11-27 11:31:47	ga_ls9c_ard_3-2-1_112072_2023-11-27_final.stac-item
2023-11-27 11:32:11	ga_ls9c_ard_3-2-1_112073_2023-11-27_final.stac-item
2023-11-27 11:33:22	ga_ls9c_ard_3-2-1_112076_2023-11-27_final.stac-item
2023-11-27 11:33:46	ga_ls9c_ard_3-2-1_112077_2023-11-27_final.stac-item
2023-11-27 11:35:22	ga_ls9c_ard_3-2-1_112081_2023-11-27_final.stac-item
2023-11-27 11:35:46	ga_ls9c_ard_3-2-1_112082_2023-11-27_final.stac-item
2023-11-27 11:36:34	ga_ls9c_ard_3-2-1_112084_2023-11-27_final.stac-item
2023-11-28 10:34:34	ga_ls9c_ard_3-2-1_103068_2023-11-28_final.stac-item
2023-11-28 10:35:22	ga_ls9c_ard_3-2-1_103070_2023-11-28_final.stac-item
2023-11-28 10:36:33	ga_ls9c_ard_3-2-1_103073_2023-11-28_final.stac-item
2023-11-28 10:37:45	ga_ls9c_ard_3-2-1_103076_2023-11-28_final.stac-item
2023-11-28 10:38:09	ga_ls9c_ard_3-2-1_103077_2023-11-28_final.stac-item
2023-11-28 10:39:21	ga_ls9c_ard_3-2-1_103080_2023-11-28_final.stac-item
2023-11-28 10:40:09	ga_ls9c_ard_3-2-1_103082_2023-11-28_final.stac-item
2023-11-29 09:40:08	ga_ls9c_ard_3-2-1_094071_2023-11-29_final.stac-item
2023-11-29 09:40:32	ga_ls9c_ard_3-2-1_094072_2023-11-29_final.stac-item
2023-11-29 09:41:20	ga_ls9c_ard_3-2-1_094074_2023-11-29_final.stac-item
2023-11-29 09:41:44	ga_ls9c_ard_3-2-1_094075_2023-11-29_final.stac-item
2023-11-29 09:42:08	ga_ls9c_ard_3-2-1_094076_2023-11-29_final.stac-item
2023-11-29 09:42:32	ga_ls9c_ard_3-2-1_094077_2023-11-29_final.stac-item
2023-11-29 09:42:56	ga_ls9c_ard_3-2-1_094078_2023-11-29_final.stac-item
2023-11-29 09:44:08	ga_ls9c_ard_3-2-1_094081_2023-11-29_final.stac-item
2023-11-29 09:45:43	ga_ls9c_ard_3-2-1_094085_2023-11-29_final.stac-item
2023-11-29 09:46:07	ga_ls9c_ard_3-2-1_094086_2023-11-29_final.stac-item
2023-11-29 09:46:31	ga_ls9c_ard_3-2-1_094087_2023-11-29_final.stac-item
2023-11-29 11:18:13	ga_ls9c_ard_3-2-1_110069_2023-11-29_final.stac-item
2023-11-29 11:20:37	ga_ls9c_ard_3-2-1_110075_2023-11-29_final.stac-item
2023-11-29 11:23:48	ga_ls9c_ard_3-2-1_110083_2023-11-29_final.stac-item
2023-11-29 11:24:12	ga_ls9c_ard_3-2-1_110084_2023-11-29_final.stac-item
2023-11-30 10:23:48	ga_ls9c_ard_3-2-1_101072_2023-11-30_final.stac-item
2023-11-30 10:24:12	ga_ls9c_ard_3-2-1_101073_2023-11-30_final.stac-item
2023-11-30 10:24:35	ga_ls9c_ard_3-2-1_101074_2023-11-30_final.stac-item
2023-11-30 10:24:59	ga_ls9c_ard_3-2-1_101075_2023-11-30_final.stac-item
2023-11-30 10:25:23	ga_ls9c_ard_3-2-1_101076_2023-11-30_final.stac-item
2023-11-30 10:26:11	ga_ls9c_ard_3-2-1_101078_2023-11-30_final.stac-item
2023-11-30 10:26:35	ga_ls9c_ard_3-2-1_101079_2023-11-30_final.stac-item
2023-11-30 10:26:59	ga_ls9c_ard_3-2-1_101080_2023-11-30_final.stac-item
2023-11-30 10:27:23	ga_ls9c_ard_3-2-1_101081_2023-11-30_final.stac-item
2023-11-30 10:27:47	ga_ls9c_ard_3-2-1_101082_2023-11-30_final.stac-item
2023-12-01 09:27:46	ga_ls9c_ard_3-2-1_092071_2023-11-30_final.stac-item
2023-12-01 09:28:10	ga_ls9c_ard_3-2-1_092072_2023-11-30_final.stac-item
2023-12-01 09:28:34	ga_ls9c_ard_3-2-1_092073_2023-11-30_final.stac-item
2023-12-01 09:29:22	ga_ls9c_ard_3-2-1_092075_2023-11-30_final.stac-item
2023-12-01 09:29:46	ga_ls9c_ard_3-2-1_092076_2023-11-30_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