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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
2021-11-02 09:17:23	ga_ls9c_ard_3-2-1_090081_2021-11-01_final.stac-item
2021-11-07 09:23:27	ga_ls9c_ard_3-2-1_090090_2021-11-06_final.stac-item
2022-01-30 10:53:52	ga_ls9c_ard_3-2-1_106070_2022-01-30_final.stac-item
2022-02-13 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-02-13_final.stac-item
2022-04-11 09:21:35	ga_ls9c_ard_3-2-1_091072_2022-04-10_final.stac-item
2022-04-25 09:33:24	ga_ls9c_ard_3-2-1_093071_2022-04-25_final.stac-item
2022-05-05 10:12:50	ga_ls9c_ard_3-2-1_099077_2022-05-05_final.stac-item
2022-05-11 11:14:10	ga_ls9c_ard_3-2-1_109076_2022-05-11_final.stac-item
2022-05-29 09:25:59	ga_ls9c_ard_3-2-1_091084_2022-05-28_final.stac-item
2022-06-07 10:58:19	ga_ls9c_ard_3-2-1_106083_2022-06-07_final.stac-item
2022-06-21 09:28:25	ga_ls9c_ard_3-2-1_092074_2022-06-20_final.stac-item
2022-07-02 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-02_final.stac-item
2022-08-16 10:19:30	ga_ls9c_ard_3-2-1_100077_2022-08-16_final.stac-item
2022-08-26 09:17:20	ga_ls9c_ard_3-2-1_090076_2022-08-25_final.stac-item
2022-08-27 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-08-27_final.stac-item
2022-09-08 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-09-08_final.stac-item
2022-10-18 09:36:53	ga_ls9c_ard_3-2-1_093078_2022-10-18_final.stac-item
2022-11-03 09:38:02	ga_ls9c_ard_3-2-1_093081_2022-11-03_final.stac-item
2022-11-12 09:33:07	ga_ls9c_ard_3-2-1_092084_2022-11-12_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2023-01-11 09:53:25	ga_ls9c_ard_3-2-1_096073_2023-01-11_final.stac-item
2023-01-16 11:53:34	ga_ls9c_ard_3-2-1_115080_2023-01-16_final.stac-item
2023-02-20 09:05:06	ga_ls9c_ard_3-2-1_088076_2023-02-19_interim.stac-item
2023-02-24 11:57:39	ga_ls9c_ard_3-2-1_116075_2023-02-24_final.stac-item
2023-02-24 11:58:03	ga_ls9c_ard_3-2-1_116076_2023-02-24_final.stac-item
2023-04-03 11:23:03	ga_ls9c_ard_3-2-1_110082_2023-04-03_final.stac-item
2023-04-14 09:22:20	ga_ls9c_ard_3-2-1_091074_2023-04-13_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-24 09:57:48	ga_ls9c_ard_3-2-1_097070_2023-04-24_final.stac-item
2023-05-21 09:39:46	ga_ls9c_ard_3-2-1_094072_2023-05-21_final.stac-item
2023-05-28 09:51:28	ga_ls9c_ard_3-2-1_095086_2023-05-28_final.stac-item
2023-06-04 09:55:14	ga_ls9c_ard_3-2-1_096080_2023-06-04_final.stac-item
2023-06-16 11:57:06	ga_ls9c_ard_3-2-1_116076_2023-06-16_final.stac-item
2023-07-06 11:35:00	ga_ls9c_ard_3-2-1_112082_2023-07-06_final.stac-item
2023-07-12 09:16:17	ga_ls9c_ard_3-2-1_090075_2023-07-11_final.stac-item
2023-07-12 09:21:05	ga_ls9c_ard_3-2-1_090087_2023-07-11_final.stac-item
2023-07-14 10:42:01	ga_ls9c_ard_3-2-1_104073_2023-07-14_final.stac-item
2023-08-13 10:55:21	ga_ls9c_ard_3-2-1_106075_2023-08-13_final.stac-item
2023-08-14 09:56:33	ga_ls9c_ard_3-2-1_097067_2023-08-14_final.stac-item
2023-09-01 09:51:08	ga_ls9c_ard_3-2-1_095084_2023-09-01_final.stac-item
2023-09-23 09:12:34	ga_ls9c_ard_3-2-1_089080_2023-09-22_final.stac-item
2023-12-18 10:11:03	ga_ls9c_ard_3-2-1_099071_2023-12-18_final.stac-item
2023-12-28 10:49:20	ga_ls9c_ard_3-2-1_105074_2023-12-28_final.stac-item
2024-01-11 09:22:21	ga_ls9c_ard_3-2-1_091073_2024-01-10_final.stac-item
2024-01-27 09:27:55	ga_ls9c_ard_3-2-1_091087_2024-01-26_final.stac-item
2024-01-29 09:11:35	ga_ls9c_ard_3-2-1_089077_2024-01-28_final.stac-item
2024-02-03 09:28:34	ga_ls9c_ard_3-2-1_092073_2024-02-02_final.stac-item
2024-02-29 11:47:34	ga_ls9c_ard_3-2-1_114081_2024-02-29_final.stac-item
2024-03-01 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-02-29_final.stac-item
2024-03-11 11:23:52	ga_ls9c_ard_3-2-1_111068_2024-03-11_final.stac-item
2024-04-01 10:02:58	ga_ls9c_ard_3-2-1_098067_2024-04-01_final.stac-item
2024-04-19 09:57:10	ga_ls9c_ard_3-2-1_096084_2024-04-19_final.stac-item
2024-05-11 09:21:29	ga_ls9c_ard_3-2-1_090088_2024-05-10_final.stac-item
2024-05-19 11:44:06	ga_ls9c_ard_3-2-1_114074_2024-05-19_nrt.stac-item
2024-05-30 11:23:51	ga_ls9c_ard_3-2-1_111070_2024-05-30_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