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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

52 results

Time (local)	Label
2021-11-18 09:59:35	ga_ls9c_ard_3-2-1_097068_2021-11-18_final.stac-item
2021-12-04 09:22:53	ga_ls9c_ard_3-2-1_091074_2021-12-03_final.stac-item
2022-01-03 11:14:24	ga_ls9c_ard_3-2-1_109075_2022-01-03_final.stac-item
2022-01-21 11:00:50	ga_ls9c_ard_3-2-1_107072_2022-01-21_final.stac-item
2022-01-26 11:19:47	ga_ls9c_ard_3-2-1_110073_2022-01-26_final.stac-item
2022-02-09 09:52:26	ga_ls9c_ard_3-2-1_096071_2022-02-09_final.stac-item
2022-02-22 09:26:12	ga_ls9c_ard_3-2-1_091083_2022-02-21_final.stac-item
2022-03-06 11:24:31	ga_ls9c_ard_3-2-1_111070_2022-03-06_final.stac-item
2022-03-19 10:52:47	ga_ls9c_ard_3-2-1_106068_2022-03-19_final.stac-item
2022-04-17 10:27:18	ga_ls9c_ard_3-2-1_101082_2022-04-17_final.stac-item
2022-04-30 09:57:07	ga_ls9c_ard_3-2-1_096084_2022-04-30_final.stac-item
2022-05-15 09:11:19	ga_ls9c_ard_3-2-1_089078_2022-05-14_final.stac-item
2022-05-29 09:22:48	ga_ls9c_ard_3-2-1_091076_2022-05-28_final.stac-item
2022-06-03 09:39:21	ga_ls9c_ard_3-2-1_094071_2022-06-03_final.stac-item
2022-06-22 10:08:56	ga_ls9c_ard_3-2-1_099067_2022-06-22_final.stac-item
2022-07-02 10:46:29	ga_ls9c_ard_3-2-1_105068_2022-07-02_final.stac-item
2022-08-06 11:18:02	ga_ls9c_ard_3-2-1_110069_2022-08-06_final.stac-item
2022-09-12 11:41:30	ga_ls9c_ard_3-2-1_113081_2022-09-12_final.stac-item
2022-09-26 10:15:28	ga_ls9c_ard_3-2-1_099082_2022-09-26_final.stac-item
2022-10-11 11:06:21	ga_ls9c_ard_3-2-1_108070_2022-10-11_final.stac-item
2022-10-21 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-10-21_final.stac-item
2022-11-12 09:29:08	ga_ls9c_ard_3-2-1_092074_2022-11-11_final.stac-item
2022-12-14 11:07:12	ga_ls9c_ard_3-2-1_108072_2022-12-14_final.stac-item
2022-12-21 09:34:51	ga_ls9c_ard_3-2-1_093073_2022-12-21_final.stac-item
2023-01-11 11:33:06	ga_ls9c_ard_3-2-1_112075_2023-01-11_final.stac-item
2023-02-08 10:22:12	ga_ls9c_ard_3-2-1_100083_2023-02-08_final.stac-item
2023-03-22 09:20:48	ga_ls9c_ard_3-2-1_090085_2023-03-21_final.stac-item
2023-03-26 10:28:54	ga_ls9c_ard_3-2-1_102070_2023-03-26_final.stac-item
2023-04-19 11:19:22	ga_ls9c_ard_3-2-1_110073_2023-04-19_final.stac-item
2023-05-13 10:27:42	ga_ls9c_ard_3-2-1_102068_2023-05-13_final.stac-item
2023-05-24 10:12:12	ga_ls9c_ard_3-2-1_099076_2023-05-24_final.stac-item
2023-05-25 10:52:16	ga_ls9c_ard_3-2-1_106068_2023-05-25_final.stac-item
2023-07-06 09:57:43	ga_ls9c_ard_3-2-1_096086_2023-07-06_final.stac-item
2023-07-22 09:51:47	ga_ls9c_ard_3-2-1_096071_2023-07-22_final.stac-item
2023-10-12 09:40:49	ga_ls9c_ard_3-2-1_094073_2023-10-12_final.stac-item
2023-10-16 10:55:49	ga_ls9c_ard_3-2-1_106075_2023-10-16_final.stac-item
2023-10-27 10:39:39	ga_ls9c_ard_3-2-1_103081_2023-10-27_final.stac-item
2023-11-01 09:17:15	ga_ls9c_ard_3-2-1_090076_2023-10-31_final.stac-item
2023-11-01 10:55:44	ga_ls9c_ard_3-2-1_106075_2023-11-01_final.stac-item
2023-12-22 11:24:50	ga_ls9c_ard_3-2-1_111070_2023-12-22_final.stac-item
2024-01-05 11:42:16	ga_ls9c_ard_3-2-1_113083_2024-01-05_final.stac-item
2024-01-07 09:47:26	ga_ls9c_ard_3-2-1_095074_2024-01-07_final.stac-item
2024-01-07 11:25:55	ga_ls9c_ard_3-2-1_111073_2024-01-07_final.stac-item
2024-01-13 10:50:05	ga_ls9c_ard_3-2-1_105076_2024-01-13_final.stac-item
2024-02-08 09:52:42	ga_ls9c_ard_3-2-1_095087_2024-02-08_final.stac-item
2024-02-19 09:34:25	ga_ls9c_ard_3-2-1_092088_2024-02-19_final.stac-item
2024-03-04 09:40:48	ga_ls9c_ard_3-2-1_094073_2024-03-04_final.stac-item
2024-03-22 09:28:48	ga_ls9c_ard_3-2-1_092074_2024-03-21_final.stac-item
2024-03-29 11:14:32	ga_ls9c_ard_3-2-1_109076_2024-03-29_final.stac-item
2024-04-11 10:45:10	ga_ls9c_ard_3-2-1_104080_2024-04-11_final.stac-item
2024-05-12 09:57:57	ga_ls9c_ard_3-2-1_097071_2024-05-12_final.stac-item
2024-05-14 09:46:44	ga_ls9c_ard_3-2-1_095074_2024-05-14_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