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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

51 results

Time (local)	Label
2021-12-17 10:30:44	ga_ls9c_ard_3-2-1_102074_2021-12-17_final.stac-item
2022-01-08 11:32:31	ga_ls9c_ard_3-2-1_112074_2022-01-08_final.stac-item
2022-01-09 10:38:06	ga_ls9c_ard_3-2-1_103077_2022-01-09_final.stac-item
2022-02-04 09:39:30	ga_ls9c_ard_3-2-1_093085_2022-02-04_final.stac-item
2022-02-11 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-02-11_final.stac-item
2022-02-27 11:19:34	ga_ls9c_ard_3-2-1_110073_2022-02-27_final.stac-item
2022-03-03 10:54:00	ga_ls9c_ard_3-2-1_106071_2022-03-03_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-04-11 09:21:35	ga_ls9c_ard_3-2-1_091072_2022-04-10_final.stac-item
2022-04-15 10:34:30	ga_ls9c_ard_3-2-1_103069_2022-04-15_final.stac-item
2022-04-29 09:15:51	ga_ls9c_ard_3-2-1_089089_2022-04-28_final.stac-item
2022-05-18 11:21:03	ga_ls9c_ard_3-2-1_110078_2022-05-18_final.stac-item
2022-05-21 10:09:26	ga_ls9c_ard_3-2-1_099069_2022-05-21_final.stac-item
2022-06-05 11:11:04	ga_ls9c_ard_3-2-1_108084_2022-06-05_final.stac-item
2022-06-16 09:14:08	ga_ls9c_ard_3-2-1_089085_2022-06-15_final.stac-item
2022-09-04 09:15:08	ga_ls9c_ard_3-2-1_089086_2022-09-03_final.stac-item
2022-09-09 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-09-09_final.stac-item
2022-10-19 10:20:33	ga_ls9c_ard_3-2-1_100079_2022-10-19_final.stac-item
2022-10-28 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-10-28_final.stac-item
2022-11-12 09:32:19	ga_ls9c_ard_3-2-1_092082_2022-11-12_final.stac-item
2022-11-16 09:08:00	ga_ls9c_ard_3-2-1_088083_2022-11-15_final.stac-item
2022-11-29 10:11:57	ga_ls9c_ard_3-2-1_099073_2022-11-29_final.stac-item
2022-12-08 10:04:59	ga_ls9c_ard_3-2-1_098071_2022-12-08_final.stac-item
2023-01-04 09:52:27	ga_ls9c_ard_3-2-1_095086_2023-01-04_final.stac-item
2023-02-05 11:24:59	ga_ls9c_ard_3-2-1_111070_2023-02-05_final.stac-item
2023-02-14 11:19:35	ga_ls9c_ard_3-2-1_110072_2023-02-14_final.stac-item
2023-06-13 09:51:45	ga_ls9c_ard_3-2-1_095087_2023-06-13_final.stac-item
2023-06-17 09:28:11	ga_ls9c_ard_3-2-1_091090_2023-06-16_final.stac-item
2023-06-20 09:57:30	ga_ls9c_ard_3-2-1_096086_2023-06-20_final.stac-item
2023-07-09 10:22:39	ga_ls9c_ard_3-2-1_101071_2023-07-09_final.stac-item
2023-07-14 10:42:01	ga_ls9c_ard_3-2-1_104073_2023-07-14_final.stac-item
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-09-12 11:07:36	ga_ls9c_ard_3-2-1_108074_2023-09-12_final.stac-item
2023-10-15 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-10-15_final.stac-item
2023-10-16 10:56:13	ga_ls9c_ard_3-2-1_106076_2023-10-16_final.stac-item
2023-10-19 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-10-19_final.stac-item
2024-01-07 09:47:02	ga_ls9c_ard_3-2-1_095073_2024-01-07_final.stac-item
2024-01-17 10:26:09	ga_ls9c_ard_3-2-1_101078_2024-01-17_final.stac-item
2024-01-26 10:22:19	ga_ls9c_ard_3-2-1_100084_2024-01-26_final.stac-item
2024-02-06 09:57:29	ga_ls9c_ard_3-2-1_097068_2024-02-06_final.stac-item
2024-02-08 09:52:42	ga_ls9c_ard_3-2-1_095087_2024-02-08_final.stac-item
2024-02-14 10:50:04	ga_ls9c_ard_3-2-1_105076_2024-02-14_final.stac-item
2024-02-21 09:18:01	ga_ls9c_ard_3-2-1_090078_2024-02-20_final.stac-item
2024-02-27 10:19:02	ga_ls9c_ard_3-2-1_100076_2024-02-27_final.stac-item
2024-02-28 09:23:49	ga_ls9c_ard_3-2-1_091077_2024-02-27_final.stac-item
2024-03-22 09:33:59	ga_ls9c_ard_3-2-1_092087_2024-03-22_final.stac-item
2024-04-02 09:11:44	ga_ls9c_ard_3-2-1_089078_2024-04-01_final.stac-item
2024-04-09 10:52:46	ga_ls9c_ard_3-2-1_106068_2024-04-09_final.stac-item
2024-04-12 09:46:20	ga_ls9c_ard_3-2-1_095072_2024-04-12_final.stac-item
2024-04-16 09:21:33	ga_ls9c_ard_3-2-1_091072_2024-04-15_final.stac-item
2024-04-16 09:23:33	ga_ls9c_ard_3-2-1_091077_2024-04-15_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