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

51 results

Time (local)	Label
2023-09-13 10:09:12	ga_ls9c_ard_3-2-1_099067_2023-09-13_final.stac-item
2023-09-13 10:09:36	ga_ls9c_ard_3-2-1_099068_2023-09-13_final.stac-item
2023-09-13 10:10:00	ga_ls9c_ard_3-2-1_099069_2023-09-13_final.stac-item
2023-09-13 10:10:24	ga_ls9c_ard_3-2-1_099070_2023-09-13_final.stac-item
2023-09-13 10:10:48	ga_ls9c_ard_3-2-1_099071_2023-09-13_final.stac-item
2023-09-13 10:11:12	ga_ls9c_ard_3-2-1_099072_2023-09-13_final.stac-item
2023-09-13 10:11:36	ga_ls9c_ard_3-2-1_099073_2023-09-13_final.stac-item
2023-09-13 10:12:00	ga_ls9c_ard_3-2-1_099074_2023-09-13_final.stac-item
2023-09-13 10:13:35	ga_ls9c_ard_3-2-1_099078_2023-09-13_final.stac-item
2023-09-13 10:13:59	ga_ls9c_ard_3-2-1_099079_2023-09-13_final.stac-item
2023-09-13 10:14:23	ga_ls9c_ard_3-2-1_099080_2023-09-13_final.stac-item
2023-09-13 10:14:47	ga_ls9c_ard_3-2-1_099081_2023-09-13_final.stac-item
2023-09-13 10:15:11	ga_ls9c_ard_3-2-1_099082_2023-09-13_final.stac-item
2023-09-13 10:15:35	ga_ls9c_ard_3-2-1_099083_2023-09-13_final.stac-item
2023-09-13 10:15:59	ga_ls9c_ard_3-2-1_099084_2023-09-13_final.stac-item
2023-09-13 10:16:23	ga_ls9c_ard_3-2-1_099085_2023-09-13_final.stac-item
2023-09-13 11:50:53	ga_ls9c_ard_3-2-1_115074_2023-09-13_final.stac-item
2023-09-13 11:51:17	ga_ls9c_ard_3-2-1_115075_2023-09-13_final.stac-item
2023-09-13 11:52:28	ga_ls9c_ard_3-2-1_115078_2023-09-13_final.stac-item
2023-09-13 11:52:52	ga_ls9c_ard_3-2-1_115079_2023-09-13_final.stac-item
2023-09-13 11:53:16	ga_ls9c_ard_3-2-1_115080_2023-09-13_final.stac-item
2023-09-14 09:16:22	ga_ls9c_ard_3-2-1_090074_2023-09-13_final.stac-item
2023-09-14 09:16:46	ga_ls9c_ard_3-2-1_090075_2023-09-13_final.stac-item
2023-09-14 09:17:10	ga_ls9c_ard_3-2-1_090076_2023-09-13_final.stac-item
2023-09-14 09:17:34	ga_ls9c_ard_3-2-1_090077_2023-09-13_final.stac-item
2023-09-14 09:17:58	ga_ls9c_ard_3-2-1_090078_2023-09-13_final.stac-item
2023-09-14 09:18:22	ga_ls9c_ard_3-2-1_090079_2023-09-13_final.stac-item
2023-09-14 09:18:46	ga_ls9c_ard_3-2-1_090080_2023-09-13_final.stac-item
2023-09-14 09:19:10	ga_ls9c_ard_3-2-1_090081_2023-09-13_final.stac-item
2023-09-14 09:19:34	ga_ls9c_ard_3-2-1_090082_2023-09-13_final.stac-item
2023-09-14 09:20:22	ga_ls9c_ard_3-2-1_090084_2023-09-13_final.stac-item
2023-09-14 09:20:46	ga_ls9c_ard_3-2-1_090085_2023-09-13_final.stac-item
2023-09-14 09:21:10	ga_ls9c_ard_3-2-1_090086_2023-09-13_final.stac-item
2023-09-14 09:22:22	ga_ls9c_ard_3-2-1_090089_2023-09-13_final.stac-item
2023-09-14 09:22:46	ga_ls9c_ard_3-2-1_090090_2023-09-13_final.stac-item
2023-09-14 10:52:52	ga_ls9c_ard_3-2-1_106068_2023-09-14_final.stac-item
2023-09-14 10:53:16	ga_ls9c_ard_3-2-1_106069_2023-09-14_final.stac-item
2023-09-14 10:53:40	ga_ls9c_ard_3-2-1_106070_2023-09-14_final.stac-item
2023-09-14 10:54:04	ga_ls9c_ard_3-2-1_106071_2023-09-14_final.stac-item
2023-09-14 10:54:28	ga_ls9c_ard_3-2-1_106072_2023-09-14_final.stac-item
2023-09-14 10:54:52	ga_ls9c_ard_3-2-1_106073_2023-09-14_final.stac-item
2023-09-14 10:55:15	ga_ls9c_ard_3-2-1_106074_2023-09-14_final.stac-item
2023-09-14 10:55:39	ga_ls9c_ard_3-2-1_106075_2023-09-14_final.stac-item
2023-09-14 10:56:03	ga_ls9c_ard_3-2-1_106076_2023-09-14_final.stac-item
2023-09-14 10:56:27	ga_ls9c_ard_3-2-1_106077_2023-09-14_final.stac-item
2023-09-14 10:56:51	ga_ls9c_ard_3-2-1_106078_2023-09-14_final.stac-item
2023-09-14 10:57:15	ga_ls9c_ard_3-2-1_106079_2023-09-14_final.stac-item
2023-09-14 10:57:39	ga_ls9c_ard_3-2-1_106080_2023-09-14_final.stac-item
2023-09-14 10:58:03	ga_ls9c_ard_3-2-1_106081_2023-09-14_final.stac-item
2023-09-14 10:58:27	ga_ls9c_ard_3-2-1_106082_2023-09-14_final.stac-item
2023-09-14 10:58:51	ga_ls9c_ard_3-2-1_106083_2023-09-14_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