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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

55 results

Time (local)	Label
2021-12-05 10:10:08	ga_ls9c_ard_3-2-1_098084_2021-12-05_final.stac-item
2021-12-06 09:12:06	ga_ls9c_ard_3-2-1_089078_2021-12-05_final.stac-item
2021-12-26 10:28:10	ga_ls9c_ard_3-2-1_101083_2021-12-26_final.stac-item
2022-01-10 09:40:28	ga_ls9c_ard_3-2-1_094072_2022-01-10_final.stac-item
2022-01-13 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-01-13_final.stac-item
2022-01-14 09:17:20	ga_ls9c_ard_3-2-1_090076_2022-01-13_final.stac-item
2022-01-22 10:04:01	ga_ls9c_ard_3-2-1_098069_2022-01-22_final.stac-item
2022-02-06 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-02-06_final.stac-item
2022-02-13 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-02-12_final.stac-item
2022-02-13 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-02-13_final.stac-item
2022-02-27 09:40:41	ga_ls9c_ard_3-2-1_094073_2022-02-27_final.stac-item
2022-04-04 09:17:26	ga_ls9c_ard_3-2-1_090077_2022-04-03_final.stac-item
2022-04-11 11:00:04	ga_ls9c_ard_3-2-1_107071_2022-04-11_final.stac-item
2022-04-13 09:09:59	ga_ls9c_ard_3-2-1_089074_2022-04-12_final.stac-item
2022-04-20 09:17:40	ga_ls9c_ard_3-2-1_090078_2022-04-19_final.stac-item
2022-06-07 10:52:20	ga_ls9c_ard_3-2-1_106068_2022-06-07_final.stac-item
2022-06-15 10:09:21	ga_ls9c_ard_3-2-1_098084_2022-06-15_final.stac-item
2022-08-01 09:24:32	ga_ls9c_ard_3-2-1_091079_2022-07-31_final.stac-item
2022-08-03 10:52:17	ga_ls9c_ard_3-2-1_105082_2022-08-03_final.stac-item
2022-09-05 11:31:42	ga_ls9c_ard_3-2-1_112072_2022-09-05_final.stac-item
2022-09-11 10:59:01	ga_ls9c_ard_3-2-1_106083_2022-09-11_final.stac-item
2022-09-23 09:45:21	ga_ls9c_ard_3-2-1_094084_2022-09-23_final.stac-item
2022-09-27 10:55:56	ga_ls9c_ard_3-2-1_106075_2022-09-27_final.stac-item
2022-10-27 09:29:07	ga_ls9c_ard_3-2-1_092074_2022-10-26_final.stac-item
2022-10-28 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-10-28_final.stac-item
2022-11-26 09:41:04	ga_ls9c_ard_3-2-1_094073_2022-11-26_final.stac-item
2022-12-12 09:45:52	ga_ls9c_ard_3-2-1_094085_2022-12-12_final.stac-item
2022-12-14 09:28:19	ga_ls9c_ard_3-2-1_092072_2022-12-13_final.stac-item
2022-12-14 09:34:18	ga_ls9c_ard_3-2-1_092087_2022-12-14_final.stac-item
2023-01-03 10:42:05	ga_ls9c_ard_3-2-1_104071_2023-01-03_final.stac-item
2023-03-07 09:57:21	ga_ls9c_ard_3-2-1_097068_2023-03-07_final.stac-item
2023-04-05 09:27:49	ga_ls9c_ard_3-2-1_092072_2023-04-04_final.stac-item
2023-04-17 11:32:07	ga_ls9c_ard_3-2-1_112074_2023-04-17_final.stac-item
2023-04-22 10:13:46	ga_ls9c_ard_3-2-1_099079_2023-04-22_final.stac-item
2023-05-01 10:07:03	ga_ls9c_ard_3-2-1_098078_2023-05-01_final.stac-item
2023-05-02 09:09:49	ga_ls9c_ard_3-2-1_089074_2023-05-01_final.stac-item
2023-05-22 10:27:24	ga_ls9c_ard_3-2-1_101083_2023-05-22_final.stac-item
2023-06-27 09:56:31	ga_ls9c_ard_3-2-1_097068_2023-06-27_final.stac-item
2023-07-13 09:57:10	ga_ls9c_ard_3-2-1_097069_2023-07-13_final.stac-item
2023-07-27 10:13:08	ga_ls9c_ard_3-2-1_099078_2023-07-27_final.stac-item
2023-09-26 11:17:56	ga_ls9c_ard_3-2-1_110069_2023-09-26_final.stac-item
2023-09-28 09:28:39	ga_ls9c_ard_3-2-1_092074_2023-09-27_final.stac-item
2023-10-02 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-10-01_final.stac-item
2023-10-27 10:36:04	ga_ls9c_ard_3-2-1_103072_2023-10-27_final.stac-item
2023-11-13 09:40:24	ga_ls9c_ard_3-2-1_094072_2023-11-13_final.stac-item
2023-12-10 11:01:37	ga_ls9c_ard_3-2-1_107074_2023-12-10_final.stac-item
2023-12-26 09:22:49	ga_ls9c_ard_3-2-1_091074_2023-12-25_final.stac-item
2023-12-27 11:47:45	ga_ls9c_ard_3-2-1_114081_2023-12-27_final.stac-item
2024-01-22 09:06:58	ga_ls9c_ard_3-2-1_088081_2024-01-21_final.stac-item
2024-01-29 09:10:23	ga_ls9c_ard_3-2-1_089074_2024-01-28_final.stac-item
2024-03-24 09:22:00	ga_ls9c_ard_3-2-1_090088_2024-03-23_final.stac-item
2024-04-01 10:03:22	ga_ls9c_ard_3-2-1_098068_2024-04-01_final.stac-item
2024-04-03 09:57:23	ga_ls9c_ard_3-2-1_096084_2024-04-03_final.stac-item
2024-04-03 11:31:28	ga_ls9c_ard_3-2-1_112072_2024-04-03_final.stac-item
2024-05-16 09:34:20	ga_ls9c_ard_3-2-1_093074_2024-05-16_nrt.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