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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

40 results

Time (local)	Label
2023-03-13 11:01:31	ga_ls9c_ard_3-2-1_107074_2023-03-13_final.stac-item
2023-03-15 09:11:04	ga_ls9c_ard_3-2-1_089076_2023-03-14_final.stac-item
2023-03-16 09:55:32	ga_ls9c_ard_3-2-1_096079_2023-03-16_final.stac-item
2023-03-18 09:42:21	ga_ls9c_ard_3-2-1_094077_2023-03-18_final.stac-item
2023-03-18 09:43:33	ga_ls9c_ard_3-2-1_094080_2023-03-18_final.stac-item
2023-03-18 09:45:33	ga_ls9c_ard_3-2-1_094085_2023-03-18_final.stac-item
2023-03-18 11:18:51	ga_ls9c_ard_3-2-1_110071_2023-03-18_final.stac-item
2023-03-18 11:19:39	ga_ls9c_ard_3-2-1_110073_2023-03-18_final.stac-item
2023-03-18 11:22:02	ga_ls9c_ard_3-2-1_110079_2023-03-18_final.stac-item
2023-03-19 10:27:12	ga_ls9c_ard_3-2-1_101081_2023-03-19_final.stac-item
2023-03-20 09:28:23	ga_ls9c_ard_3-2-1_092073_2023-03-19_final.stac-item
2023-03-20 09:29:59	ga_ls9c_ard_3-2-1_092077_2023-03-19_final.stac-item
2023-03-20 09:31:11	ga_ls9c_ard_3-2-1_092080_2023-03-20_final.stac-item
2023-03-20 09:32:23	ga_ls9c_ard_3-2-1_092083_2023-03-20_final.stac-item
2023-03-20 09:34:46	ga_ls9c_ard_3-2-1_092089_2023-03-20_final.stac-item
2023-03-20 11:08:52	ga_ls9c_ard_3-2-1_108077_2023-03-20_final.stac-item
2023-03-21 10:09:15	ga_ls9c_ard_3-2-1_099067_2023-03-21_final.stac-item
2023-03-21 10:14:26	ga_ls9c_ard_3-2-1_099080_2023-03-21_final.stac-item
2023-03-21 10:14:50	ga_ls9c_ard_3-2-1_099081_2023-03-21_final.stac-item
2023-03-21 10:16:02	ga_ls9c_ard_3-2-1_099084_2023-03-21_final.stac-item
2023-03-22 09:16:24	ga_ls9c_ard_3-2-1_090074_2023-03-21_final.stac-item
2023-03-22 09:16:48	ga_ls9c_ard_3-2-1_090075_2023-03-21_final.stac-item
2023-03-22 09:18:00	ga_ls9c_ard_3-2-1_090078_2023-03-21_final.stac-item
2023-03-22 09:19:12	ga_ls9c_ard_3-2-1_090081_2023-03-21_final.stac-item
2023-03-22 09:21:12	ga_ls9c_ard_3-2-1_090086_2023-03-21_final.stac-item
2023-03-22 10:58:29	ga_ls9c_ard_3-2-1_106082_2023-03-22_final.stac-item
2023-03-23 10:00:27	ga_ls9c_ard_3-2-1_097076_2023-03-23_final.stac-item
2023-03-23 10:04:02	ga_ls9c_ard_3-2-1_097085_2023-03-23_final.stac-item
2023-03-23 11:40:56	ga_ls9c_ard_3-2-1_113080_2023-03-23_final.stac-item
2023-03-23 11:42:08	ga_ls9c_ard_3-2-1_113083_2023-03-23_final.stac-item
2023-03-24 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-03-23_final.stac-item
2023-03-24 10:41:18	ga_ls9c_ard_3-2-1_104070_2023-03-24_final.stac-item
2023-03-24 10:43:42	ga_ls9c_ard_3-2-1_104076_2023-03-24_final.stac-item
2023-03-24 10:44:30	ga_ls9c_ard_3-2-1_104078_2023-03-24_final.stac-item
2023-03-24 10:45:41	ga_ls9c_ard_3-2-1_104081_2023-03-24_final.stac-item
2023-04-20 10:25:44	ga_ls9c_ard_3-2-1_101078_2023-04-20_final.stac-item
2023-04-21 09:27:19	ga_ls9c_ard_3-2-1_092071_2023-04-20_final.stac-item
2023-04-21 09:27:43	ga_ls9c_ard_3-2-1_092072_2023-04-20_final.stac-item
2023-04-21 09:28:07	ga_ls9c_ard_3-2-1_092073_2023-04-20_final.stac-item
2023-04-21 09:28:31	ga_ls9c_ard_3-2-1_092074_2023-04-20_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