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

72 results

Time (local)	Label
2023-06-25 10:10:50	ga_ls9c_ard_3-2-1_099073_2023-06-25_final.stac-item
2023-06-25 10:12:02	ga_ls9c_ard_3-2-1_099076_2023-06-25_final.stac-item
2023-06-25 10:14:02	ga_ls9c_ard_3-2-1_099081_2023-06-25_final.stac-item
2023-06-25 11:50:55	ga_ls9c_ard_3-2-1_115076_2023-06-25_final.stac-item
2023-06-26 09:17:13	ga_ls9c_ard_3-2-1_090078_2023-06-25_final.stac-item
2023-06-26 09:21:37	ga_ls9c_ard_3-2-1_090089_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
2023-06-26 10:52:55	ga_ls9c_ard_3-2-1_106070_2023-06-26_final.stac-item
2023-06-26 10:58:06	ga_ls9c_ard_3-2-1_106083_2023-06-26_final.stac-item
2023-06-27 09:56:08	ga_ls9c_ard_3-2-1_097067_2023-06-27_final.stac-item
2023-06-27 09:56:31	ga_ls9c_ard_3-2-1_097068_2023-06-27_final.stac-item
2023-06-27 09:57:19	ga_ls9c_ard_3-2-1_097070_2023-06-27_final.stac-item
2023-06-27 09:58:31	ga_ls9c_ard_3-2-1_097073_2023-06-27_final.stac-item
2023-06-27 09:58:55	ga_ls9c_ard_3-2-1_097074_2023-06-27_final.stac-item
2023-06-27 09:59:43	ga_ls9c_ard_3-2-1_097076_2023-06-27_final.stac-item
2023-06-27 10:00:07	ga_ls9c_ard_3-2-1_097077_2023-06-27_final.stac-item
2023-06-27 10:01:43	ga_ls9c_ard_3-2-1_097081_2023-06-27_final.stac-item
2023-06-27 11:37:24	ga_ls9c_ard_3-2-1_113073_2023-06-27_final.stac-item
2023-06-27 11:38:12	ga_ls9c_ard_3-2-1_113075_2023-06-27_final.stac-item
2023-06-27 11:38:36	ga_ls9c_ard_3-2-1_113076_2023-06-27_final.stac-item
2023-06-27 11:39:00	ga_ls9c_ard_3-2-1_113077_2023-06-27_final.stac-item
2023-06-27 11:40:12	ga_ls9c_ard_3-2-1_113080_2023-06-27_final.stac-item
2023-06-27 11:41:24	ga_ls9c_ard_3-2-1_113083_2023-06-27_final.stac-item
2023-06-28 10:39:49	ga_ls9c_ard_3-2-1_104068_2023-06-28_final.stac-item
2023-06-28 10:40:13	ga_ls9c_ard_3-2-1_104069_2023-06-28_final.stac-item
2023-06-28 10:40:37	ga_ls9c_ard_3-2-1_104070_2023-06-28_final.stac-item
2023-06-28 10:41:01	ga_ls9c_ard_3-2-1_104071_2023-06-28_final.stac-item
2023-06-28 10:41:25	ga_ls9c_ard_3-2-1_104072_2023-06-28_final.stac-item
2023-06-28 10:41:49	ga_ls9c_ard_3-2-1_104073_2023-06-28_final.stac-item
2023-06-28 10:42:13	ga_ls9c_ard_3-2-1_104074_2023-06-28_final.stac-item
2023-06-28 10:42:37	ga_ls9c_ard_3-2-1_104075_2023-06-28_final.stac-item
2023-06-28 10:43:01	ga_ls9c_ard_3-2-1_104076_2023-06-28_final.stac-item
2023-06-28 10:43:25	ga_ls9c_ard_3-2-1_104077_2023-06-28_final.stac-item
2023-06-28 10:43:48	ga_ls9c_ard_3-2-1_104078_2023-06-28_final.stac-item
2023-06-28 10:44:12	ga_ls9c_ard_3-2-1_104079_2023-06-28_final.stac-item
2023-06-28 10:44:36	ga_ls9c_ard_3-2-1_104080_2023-06-28_final.stac-item
2023-06-28 10:45:00	ga_ls9c_ard_3-2-1_104081_2023-06-28_final.stac-item
2023-06-28 10:45:24	ga_ls9c_ard_3-2-1_104082_2023-06-28_final.stac-item
2023-06-29 09:45:25	ga_ls9c_ard_3-2-1_095071_2023-06-29_final.stac-item
2023-06-29 09:45:49	ga_ls9c_ard_3-2-1_095072_2023-06-29_final.stac-item
2023-06-29 09:46:13	ga_ls9c_ard_3-2-1_095073_2023-06-29_final.stac-item
2023-06-29 09:46:37	ga_ls9c_ard_3-2-1_095074_2023-06-29_final.stac-item
2023-06-29 09:47:01	ga_ls9c_ard_3-2-1_095075_2023-06-29_final.stac-item
2023-06-29 09:47:25	ga_ls9c_ard_3-2-1_095076_2023-06-29_final.stac-item
2023-06-29 09:47:49	ga_ls9c_ard_3-2-1_095077_2023-06-29_final.stac-item
2023-06-29 09:48:13	ga_ls9c_ard_3-2-1_095078_2023-06-29_final.stac-item
2023-06-29 09:48:37	ga_ls9c_ard_3-2-1_095079_2023-06-29_final.stac-item
2023-06-29 09:49:01	ga_ls9c_ard_3-2-1_095080_2023-06-29_final.stac-item
2023-06-29 09:49:25	ga_ls9c_ard_3-2-1_095081_2023-06-29_final.stac-item
2023-06-29 09:49:49	ga_ls9c_ard_3-2-1_095082_2023-06-29_final.stac-item
2023-06-29 09:50:13	ga_ls9c_ard_3-2-1_095083_2023-06-29_final.stac-item
2023-06-29 09:50:37	ga_ls9c_ard_3-2-1_095084_2023-06-29_final.stac-item
2023-06-29 09:51:01	ga_ls9c_ard_3-2-1_095085_2023-06-29_final.stac-item
2023-06-29 09:51:25	ga_ls9c_ard_3-2-1_095086_2023-06-29_final.stac-item
2023-06-29 09:51:48	ga_ls9c_ard_3-2-1_095087_2023-06-29_final.stac-item
2023-06-29 11:23:07	ga_ls9c_ard_3-2-1_111068_2023-06-29_final.stac-item
2023-06-29 11:23:31	ga_ls9c_ard_3-2-1_111069_2023-06-29_final.stac-item
2023-06-29 11:23:55	ga_ls9c_ard_3-2-1_111070_2023-06-29_final.stac-item
2023-06-29 11:24:18	ga_ls9c_ard_3-2-1_111071_2023-06-29_final.stac-item
2023-06-29 11:24:42	ga_ls9c_ard_3-2-1_111072_2023-06-29_final.stac-item
2023-06-29 11:25:06	ga_ls9c_ard_3-2-1_111073_2023-06-29_final.stac-item
2023-06-29 11:25:30	ga_ls9c_ard_3-2-1_111074_2023-06-29_final.stac-item
2023-06-29 11:25:54	ga_ls9c_ard_3-2-1_111075_2023-06-29_final.stac-item
2023-06-29 11:26:18	ga_ls9c_ard_3-2-1_111076_2023-06-29_final.stac-item
2023-06-29 11:26:42	ga_ls9c_ard_3-2-1_111077_2023-06-29_final.stac-item
2023-06-29 11:27:06	ga_ls9c_ard_3-2-1_111078_2023-06-29_final.stac-item
2023-06-29 11:27:30	ga_ls9c_ard_3-2-1_111079_2023-06-29_final.stac-item
2023-06-29 11:27:54	ga_ls9c_ard_3-2-1_111080_2023-06-29_final.stac-item
2023-06-29 11:28:18	ga_ls9c_ard_3-2-1_111081_2023-06-29_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-06-29 11:29:06	ga_ls9c_ard_3-2-1_111083_2023-06-29_final.stac-item
2023-06-29 11:29:30	ga_ls9c_ard_3-2-1_111084_2023-06-29_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