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

54 results

Time (local)	Label
2023-02-23 09:34:20	ga_ls9c_ard_3-2-1_093072_2023-02-23_final.stac-item
2023-02-23 09:36:19	ga_ls9c_ard_3-2-1_093077_2023-02-23_final.stac-item
2023-02-23 09:36:43	ga_ls9c_ard_3-2-1_093078_2023-02-23_final.stac-item
2023-02-23 09:37:07	ga_ls9c_ard_3-2-1_093079_2023-02-23_final.stac-item
2023-02-23 09:37:55	ga_ls9c_ard_3-2-1_093081_2023-02-23_final.stac-item
2023-02-23 09:38:43	ga_ls9c_ard_3-2-1_093083_2023-02-23_final.stac-item
2023-02-23 09:39:07	ga_ls9c_ard_3-2-1_093084_2023-02-23_final.stac-item
2023-02-23 09:39:31	ga_ls9c_ard_3-2-1_093085_2023-02-23_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-02-23 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-02-23_final.stac-item
2023-02-23 11:14:24	ga_ls9c_ard_3-2-1_109075_2023-02-23_final.stac-item
2023-02-24 10:17:58	ga_ls9c_ard_3-2-1_100073_2023-02-24_final.stac-item
2023-02-24 10:18:22	ga_ls9c_ard_3-2-1_100074_2023-02-24_final.stac-item
2023-02-24 10:19:34	ga_ls9c_ard_3-2-1_100077_2023-02-24_final.stac-item
2023-02-24 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-02-24_final.stac-item
2023-02-24 10:22:21	ga_ls9c_ard_3-2-1_100084_2023-02-24_final.stac-item
2023-02-25 09:21:57	ga_ls9c_ard_3-2-1_091072_2023-02-24_final.stac-item
2023-02-25 09:22:21	ga_ls9c_ard_3-2-1_091073_2023-02-24_final.stac-item
2023-02-25 09:25:32	ga_ls9c_ard_3-2-1_091081_2023-02-24_final.stac-item
2023-02-25 09:26:44	ga_ls9c_ard_3-2-1_091084_2023-02-24_final.stac-item
2023-02-25 09:27:08	ga_ls9c_ard_3-2-1_091085_2023-02-24_final.stac-item
2023-02-25 09:28:44	ga_ls9c_ard_3-2-1_091089_2023-02-24_final.stac-item
2023-02-25 11:01:14	ga_ls9c_ard_3-2-1_107073_2023-02-25_final.stac-item
2023-02-25 11:05:13	ga_ls9c_ard_3-2-1_107083_2023-02-25_final.stac-item
2023-02-26 10:05:37	ga_ls9c_ard_3-2-1_098073_2023-02-26_final.stac-item
2023-02-26 10:06:48	ga_ls9c_ard_3-2-1_098076_2023-02-26_final.stac-item
2023-02-26 10:08:24	ga_ls9c_ard_3-2-1_098080_2023-02-26_final.stac-item
2023-02-26 10:08:48	ga_ls9c_ard_3-2-1_098081_2023-02-26_final.stac-item
2023-02-26 10:09:12	ga_ls9c_ard_3-2-1_098082_2023-02-26_final.stac-item
2023-02-26 11:46:05	ga_ls9c_ard_3-2-1_114077_2023-02-26_final.stac-item
2023-02-27 09:11:11	ga_ls9c_ard_3-2-1_089076_2023-02-26_final.stac-item
2023-02-27 09:12:23	ga_ls9c_ard_3-2-1_089079_2023-02-26_final.stac-item
2023-02-27 09:13:11	ga_ls9c_ard_3-2-1_089081_2023-02-26_final.stac-item
2023-02-27 09:13:35	ga_ls9c_ard_3-2-1_089082_2023-02-26_final.stac-item
2023-02-27 09:16:46	ga_ls9c_ard_3-2-1_089090_2023-02-26_final.stac-item
2023-02-27 10:46:29	ga_ls9c_ard_3-2-1_105067_2023-02-27_final.stac-item
2023-02-27 10:52:04	ga_ls9c_ard_3-2-1_105081_2023-02-27_final.stac-item
2023-03-01 10:34:55	ga_ls9c_ard_3-2-1_103069_2023-03-01_final.stac-item
2023-03-01 10:35:18	ga_ls9c_ard_3-2-1_103070_2023-03-01_final.stac-item
2023-03-01 10:36:06	ga_ls9c_ard_3-2-1_103072_2023-03-01_final.stac-item
2023-03-01 10:36:30	ga_ls9c_ard_3-2-1_103073_2023-03-01_final.stac-item
2023-03-01 10:39:42	ga_ls9c_ard_3-2-1_103081_2023-03-01_final.stac-item
2023-03-02 09:40:05	ga_ls9c_ard_3-2-1_094071_2023-03-02_final.stac-item
2023-03-02 09:42:04	ga_ls9c_ard_3-2-1_094076_2023-03-02_final.stac-item
2023-03-02 09:42:28	ga_ls9c_ard_3-2-1_094077_2023-03-02_final.stac-item
2023-03-02 09:44:28	ga_ls9c_ard_3-2-1_094082_2023-03-02_final.stac-item
2023-03-02 11:18:10	ga_ls9c_ard_3-2-1_110069_2023-03-02_final.stac-item
2023-03-02 11:18:34	ga_ls9c_ard_3-2-1_110070_2023-03-02_final.stac-item
2023-03-02 11:21:21	ga_ls9c_ard_3-2-1_110077_2023-03-02_final.stac-item
2023-03-02 11:23:45	ga_ls9c_ard_3-2-1_110083_2023-03-02_final.stac-item
2023-03-02 11:24:09	ga_ls9c_ard_3-2-1_110084_2023-03-02_final.stac-item
2023-03-03 10:25:20	ga_ls9c_ard_3-2-1_101076_2023-03-03_final.stac-item
2023-03-03 10:27:19	ga_ls9c_ard_3-2-1_101081_2023-03-03_final.stac-item
2023-03-04 09:28:30	ga_ls9c_ard_3-2-1_092073_2023-03-03_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years