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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

44 results

Time (local)	Label
2021-11-07 10:58:56	ga_ls9c_ard_3-2-1_106082_2021-11-07_final.stac-item
2021-12-04 11:02:58	ga_ls9c_ard_3-2-1_107077_2021-12-04_final.stac-item
2021-12-14 09:57:28	ga_ls9c_ard_3-2-1_097068_2021-12-14_final.stac-item
2021-12-24 10:37:44	ga_ls9c_ard_3-2-1_103076_2021-12-24_final.stac-item
2022-01-29 10:14:36	ga_ls9c_ard_3-2-1_099080_2022-01-29_final.stac-item
2022-02-04 09:39:30	ga_ls9c_ard_3-2-1_093085_2022-02-04_final.stac-item
2022-02-04 11:14:00	ga_ls9c_ard_3-2-1_109074_2022-02-04_final.stac-item
2022-02-28 10:22:44	ga_ls9c_ard_3-2-1_101070_2022-02-28_final.stac-item
2022-03-08 11:14:09	ga_ls9c_ard_3-2-1_109075_2022-03-08_final.stac-item
2022-04-12 11:45:42	ga_ls9c_ard_3-2-1_114077_2022-04-12_final.stac-item
2022-04-20 10:53:22	ga_ls9c_ard_3-2-1_106070_2022-04-20_final.stac-item
2022-05-02 11:20:26	ga_ls9c_ard_3-2-1_110076_2022-05-02_final.stac-item
2022-05-30 10:09:39	ga_ls9c_ard_3-2-1_098085_2022-05-30_final.stac-item
2022-06-26 11:23:59	ga_ls9c_ard_3-2-1_111069_2022-06-26_final.stac-item
2022-06-29 10:21:58	ga_ls9c_ard_3-2-1_100084_2022-06-29_final.stac-item
2022-06-30 11:04:50	ga_ls9c_ard_3-2-1_107083_2022-06-30_final.stac-item
2022-07-05 09:40:53	ga_ls9c_ard_3-2-1_094074_2022-07-05_final.stac-item
2022-08-17 11:04:22	ga_ls9c_ard_3-2-1_107081_2022-08-17_final.stac-item
2022-08-28 10:46:15	ga_ls9c_ard_3-2-1_104082_2022-08-28_final.stac-item
2022-09-23 09:43:46	ga_ls9c_ard_3-2-1_094080_2022-09-23_final.stac-item
2022-10-06 10:50:09	ga_ls9c_ard_3-2-1_105076_2022-10-06_final.stac-item
2022-12-25 10:50:12	ga_ls9c_ard_3-2-1_105076_2022-12-25_final.stac-item
2023-01-27 11:35:52	ga_ls9c_ard_3-2-1_112082_2023-01-27_final.stac-item
2023-03-05 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-03-05_final.stac-item
2023-03-08 10:41:00	ga_ls9c_ard_3-2-1_104069_2023-03-08_final.stac-item
2023-03-21 10:15:38	ga_ls9c_ard_3-2-1_099083_2023-03-21_final.stac-item
2023-04-04 10:23:02	ga_ls9c_ard_3-2-1_101071_2023-04-04_final.stac-item
2023-04-15 10:09:58	ga_ls9c_ard_3-2-1_098085_2023-04-15_final.stac-item
2023-06-15 09:33:46	ga_ls9c_ard_3-2-1_093073_2023-06-15_final.stac-item
2023-06-24 09:30:22	ga_ls9c_ard_3-2-1_092080_2023-06-24_final.stac-item
2023-06-29 09:49:49	ga_ls9c_ard_3-2-1_095082_2023-06-29_final.stac-item
2023-07-31 09:45:41	ga_ls9c_ard_3-2-1_095071_2023-07-31_final.stac-item
2023-08-01 10:33:21	ga_ls9c_ard_3-2-1_102082_2023-08-01_final.stac-item
2023-09-01 11:25:38	ga_ls9c_ard_3-2-1_111073_2023-09-01_final.stac-item
2023-12-05 09:06:36	ga_ls9c_ard_3-2-1_088080_2023-12-04_final.stac-item
2023-12-05 10:45:29	ga_ls9c_ard_3-2-1_104080_2023-12-05_final.stac-item
2023-12-08 11:14:21	ga_ls9c_ard_3-2-1_109075_2023-12-08_final.stac-item
2023-12-08 11:16:44	ga_ls9c_ard_3-2-1_109081_2023-12-08_final.stac-item
2023-12-22 08:11:03	ga_ls9c_ard_3-2-1_079080_2023-12-21_final.stac-item
2024-03-01 10:47:10	ga_ls9c_ard_3-2-1_105069_2024-03-01_final.stac-item
2024-03-23 10:14:26	ga_ls9c_ard_3-2-1_099080_2024-03-23_final.stac-item
2024-04-15 11:57:40	ga_ls9c_ard_3-2-1_116076_2024-04-15_final.stac-item
2024-04-25 09:21:31	ga_ls9c_ard_3-2-1_090088_2024-04-24_final.stac-item
2024-05-01 10:21:42	ga_ls9c_ard_3-2-1_100084_2024-05-01_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