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

67 results

Time (local)	Label
2023-04-05 09:30:36	ga_ls9c_ard_3-2-1_092079_2023-04-05_final.stac-item
2023-04-05 09:33:48	ga_ls9c_ard_3-2-1_092087_2023-04-05_final.stac-item
2023-04-05 09:35:00	ga_ls9c_ard_3-2-1_092090_2023-04-05_final.stac-item
2023-04-05 11:06:18	ga_ls9c_ard_3-2-1_108071_2023-04-05_final.stac-item
2023-04-05 11:06:42	ga_ls9c_ard_3-2-1_108072_2023-04-05_final.stac-item
2023-04-05 11:07:54	ga_ls9c_ard_3-2-1_108075_2023-04-05_final.stac-item
2023-04-05 11:08:42	ga_ls9c_ard_3-2-1_108077_2023-04-05_final.stac-item
2023-04-05 11:09:05	ga_ls9c_ard_3-2-1_108078_2023-04-05_final.stac-item
2023-04-05 11:10:17	ga_ls9c_ard_3-2-1_108081_2023-04-05_final.stac-item
2023-04-05 11:11:05	ga_ls9c_ard_3-2-1_108083_2023-04-05_final.stac-item
2023-04-06 10:10:16	ga_ls9c_ard_3-2-1_099070_2023-04-06_final.stac-item
2023-04-06 10:11:28	ga_ls9c_ard_3-2-1_099073_2023-04-06_final.stac-item
2023-04-06 10:12:16	ga_ls9c_ard_3-2-1_099075_2023-04-06_final.stac-item
2023-04-06 10:12:40	ga_ls9c_ard_3-2-1_099076_2023-04-06_final.stac-item
2023-04-06 10:14:40	ga_ls9c_ard_3-2-1_099081_2023-04-06_final.stac-item
2023-04-06 10:15:04	ga_ls9c_ard_3-2-1_099082_2023-04-06_final.stac-item
2023-04-06 11:51:33	ga_ls9c_ard_3-2-1_115076_2023-04-06_final.stac-item
2023-04-06 11:52:45	ga_ls9c_ard_3-2-1_115079_2023-04-06_final.stac-item
2023-04-06 11:53:09	ga_ls9c_ard_3-2-1_115080_2023-04-06_final.stac-item
2023-04-07 09:16:14	ga_ls9c_ard_3-2-1_090074_2023-04-06_final.stac-item
2023-04-07 09:16:38	ga_ls9c_ard_3-2-1_090075_2023-04-06_final.stac-item
2023-04-07 09:17:02	ga_ls9c_ard_3-2-1_090076_2023-04-06_final.stac-item
2023-04-07 09:18:14	ga_ls9c_ard_3-2-1_090079_2023-04-06_final.stac-item
2023-04-07 09:18:38	ga_ls9c_ard_3-2-1_090080_2023-04-06_final.stac-item
2023-04-07 09:19:50	ga_ls9c_ard_3-2-1_090083_2023-04-06_final.stac-item
2023-04-07 09:20:14	ga_ls9c_ard_3-2-1_090084_2023-04-06_final.stac-item
2023-04-07 10:52:44	ga_ls9c_ard_3-2-1_106068_2023-04-07_final.stac-item
2023-04-07 10:54:43	ga_ls9c_ard_3-2-1_106073_2023-04-07_final.stac-item
2023-04-07 10:57:07	ga_ls9c_ard_3-2-1_106079_2023-04-07_final.stac-item
2023-04-07 10:57:31	ga_ls9c_ard_3-2-1_106080_2023-04-07_final.stac-item
2023-04-07 10:58:19	ga_ls9c_ard_3-2-1_106082_2023-04-07_final.stac-item
2023-04-07 10:58:43	ga_ls9c_ard_3-2-1_106083_2023-04-07_final.stac-item
2023-04-08 09:56:42	ga_ls9c_ard_3-2-1_097067_2023-04-08_final.stac-item
2023-04-08 09:57:06	ga_ls9c_ard_3-2-1_097068_2023-04-08_final.stac-item
2023-04-08 09:57:30	ga_ls9c_ard_3-2-1_097069_2023-04-08_final.stac-item
2023-04-08 09:57:54	ga_ls9c_ard_3-2-1_097070_2023-04-08_final.stac-item
2023-04-08 09:58:18	ga_ls9c_ard_3-2-1_097071_2023-04-08_final.stac-item
2023-04-08 09:58:42	ga_ls9c_ard_3-2-1_097072_2023-04-08_final.stac-item
2023-04-08 09:59:06	ga_ls9c_ard_3-2-1_097073_2023-04-08_final.stac-item
2023-04-08 09:59:30	ga_ls9c_ard_3-2-1_097074_2023-04-08_final.stac-item
2023-04-08 09:59:53	ga_ls9c_ard_3-2-1_097075_2023-04-08_final.stac-item
2023-04-08 10:00:17	ga_ls9c_ard_3-2-1_097076_2023-04-08_final.stac-item
2023-04-08 10:00:41	ga_ls9c_ard_3-2-1_097077_2023-04-08_final.stac-item
2023-04-08 10:01:05	ga_ls9c_ard_3-2-1_097078_2023-04-08_final.stac-item
2023-04-08 10:01:29	ga_ls9c_ard_3-2-1_097079_2023-04-08_final.stac-item
2023-04-08 10:01:53	ga_ls9c_ard_3-2-1_097080_2023-04-08_final.stac-item
2023-04-08 10:02:17	ga_ls9c_ard_3-2-1_097081_2023-04-08_final.stac-item
2023-04-08 10:02:41	ga_ls9c_ard_3-2-1_097082_2023-04-08_final.stac-item
2023-04-08 10:03:05	ga_ls9c_ard_3-2-1_097083_2023-04-08_final.stac-item
2023-04-08 10:03:29	ga_ls9c_ard_3-2-1_097084_2023-04-08_final.stac-item
2023-04-08 10:03:53	ga_ls9c_ard_3-2-1_097085_2023-04-08_final.stac-item
2023-04-08 11:37:35	ga_ls9c_ard_3-2-1_113072_2023-04-08_final.stac-item
2023-04-08 11:37:59	ga_ls9c_ard_3-2-1_113073_2023-04-08_final.stac-item
2023-04-08 11:38:23	ga_ls9c_ard_3-2-1_113074_2023-04-08_final.stac-item
2023-04-08 11:38:47	ga_ls9c_ard_3-2-1_113075_2023-04-08_final.stac-item
2023-04-08 11:39:10	ga_ls9c_ard_3-2-1_113076_2023-04-08_final.stac-item
2023-04-08 11:39:34	ga_ls9c_ard_3-2-1_113077_2023-04-08_final.stac-item
2023-04-08 11:39:58	ga_ls9c_ard_3-2-1_113078_2023-04-08_final.stac-item
2023-04-08 11:40:22	ga_ls9c_ard_3-2-1_113079_2023-04-08_final.stac-item
2023-04-08 11:40:46	ga_ls9c_ard_3-2-1_113080_2023-04-08_final.stac-item
2023-04-08 11:41:10	ga_ls9c_ard_3-2-1_113081_2023-04-08_final.stac-item
2023-04-08 11:41:34	ga_ls9c_ard_3-2-1_113082_2023-04-08_final.stac-item
2023-04-08 11:41:58	ga_ls9c_ard_3-2-1_113083_2023-04-08_final.stac-item
2023-04-09 09:06:15	ga_ls9c_ard_3-2-1_088080_2023-04-08_final.stac-item
2023-04-09 09:06:39	ga_ls9c_ard_3-2-1_088081_2023-04-08_final.stac-item
2023-04-09 09:07:03	ga_ls9c_ard_3-2-1_088082_2023-04-08_final.stac-item
2023-04-09 09:07:27	ga_ls9c_ard_3-2-1_088083_2023-04-08_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