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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

68 results

Time (local)	Label
2021-11-07 09:21:28	ga_ls9c_ard_3-2-1_090085_2021-11-06_final.stac-item
2021-12-16 09:46:41	ga_ls9c_ard_3-2-1_095072_2021-12-16_final.stac-item
2021-12-18 09:40:42	ga_ls9c_ard_3-2-1_093088_2021-12-18_final.stac-item
2021-12-27 11:06:38	ga_ls9c_ard_3-2-1_108071_2021-12-27_final.stac-item
2022-03-22 11:24:52	ga_ls9c_ard_3-2-1_111071_2022-03-22_final.stac-item
2022-03-28 10:46:33	ga_ls9c_ard_3-2-1_105068_2022-03-28_final.stac-item
2022-04-08 10:27:59	ga_ls9c_ard_3-2-1_102068_2022-04-08_final.stac-item
2022-04-16 11:20:08	ga_ls9c_ard_3-2-1_110075_2022-04-16_final.stac-item
2022-04-17 10:27:42	ga_ls9c_ard_3-2-1_101083_2022-04-17_final.stac-item
2022-04-19 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-04-19_final.stac-item
2022-05-20 11:05:27	ga_ls9c_ard_3-2-1_108070_2022-05-20_final.stac-item
2022-05-21 11:50:43	ga_ls9c_ard_3-2-1_115075_2022-05-21_final.stac-item
2022-05-28 10:16:25	ga_ls9c_ard_3-2-1_100071_2022-05-28_final.stac-item
2022-06-20 10:27:36	ga_ls9c_ard_3-2-1_101083_2022-06-20_final.stac-item
2022-06-22 10:09:44	ga_ls9c_ard_3-2-1_099069_2022-06-22_final.stac-item
2022-06-30 09:27:33	ga_ls9c_ard_3-2-1_091087_2022-06-29_final.stac-item
2022-07-24 10:09:53	ga_ls9c_ard_3-2-1_099069_2022-07-24_final.stac-item
2022-08-03 10:46:42	ga_ls9c_ard_3-2-1_105068_2022-08-03_final.stac-item
2022-08-09 10:09:17	ga_ls9c_ard_3-2-1_099067_2022-08-09_final.stac-item
2022-08-13 09:52:10	ga_ls9c_ard_3-2-1_095086_2022-08-13_final.stac-item
2022-09-09 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-09-08_final.stac-item
2022-09-11 09:22:56	ga_ls9c_ard_3-2-1_090090_2022-09-10_final.stac-item
2022-09-12 09:57:26	ga_ls9c_ard_3-2-1_097068_2022-09-12_final.stac-item
2022-10-25 09:40:41	ga_ls9c_ard_3-2-1_094072_2022-10-25_final.stac-item
2022-10-28 10:09:35	ga_ls9c_ard_3-2-1_099067_2022-10-28_final.stac-item
2022-11-01 09:52:25	ga_ls9c_ard_3-2-1_095086_2022-11-01_final.stac-item
2022-11-01 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-11-01_final.stac-item
2022-11-08 11:36:42	ga_ls9c_ard_3-2-1_112084_2022-11-08_final.stac-item
2022-11-12 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-11-11_final.stac-item
2022-11-25 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-11-25_final.stac-item
2022-11-28 09:33:53	ga_ls9c_ard_3-2-1_092086_2022-11-28_final.stac-item
2022-12-03 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-12-03_final.stac-item
2022-12-07 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-12-06_final.stac-item
2022-12-13 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-12-13_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2023-01-13 09:40:14	ga_ls9c_ard_3-2-1_094071_2023-01-13_final.stac-item
2023-01-16 11:52:46	ga_ls9c_ard_3-2-1_115078_2023-01-16_final.stac-item
2023-02-12 11:32:46	ga_ls9c_ard_3-2-1_112074_2023-02-12_final.stac-item
2023-02-13 10:39:55	ga_ls9c_ard_3-2-1_103081_2023-02-13_final.stac-item
2023-03-15 10:46:46	ga_ls9c_ard_3-2-1_105068_2023-03-15_final.stac-item
2023-04-01 11:32:13	ga_ls9c_ard_3-2-1_112074_2023-04-01_final.stac-item
2023-04-11 10:28:46	ga_ls9c_ard_3-2-1_102070_2023-04-11_final.stac-item
2023-04-12 09:34:20	ga_ls9c_ard_3-2-1_093073_2023-04-12_final.stac-item
2023-04-21 09:28:54	ga_ls9c_ard_3-2-1_092075_2023-04-20_final.stac-item
2023-04-22 10:13:46	ga_ls9c_ard_3-2-1_099079_2023-04-22_final.stac-item
2023-05-26 11:37:55	ga_ls9c_ard_3-2-1_113074_2023-05-26_final.stac-item
2023-06-01 09:21:33	ga_ls9c_ard_3-2-1_091073_2023-05-31_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-06-01 09:27:08	ga_ls9c_ard_3-2-1_091087_2023-05-31_final.stac-item
2023-06-04 11:30:55	ga_ls9c_ard_3-2-1_112072_2023-06-04_final.stac-item
2023-06-11 09:56:09	ga_ls9c_ard_3-2-1_097067_2023-06-11_final.stac-item
2023-07-05 10:50:32	ga_ls9c_ard_3-2-1_105079_2023-07-05_final.stac-item
2023-07-20 10:09:20	ga_ls9c_ard_3-2-1_098084_2023-07-20_final.stac-item
2023-08-13 10:55:45	ga_ls9c_ard_3-2-1_106076_2023-08-13_final.stac-item
2023-08-20 09:25:52	ga_ls9c_ard_3-2-1_091083_2023-08-19_final.stac-item
2023-09-28 09:29:03	ga_ls9c_ard_3-2-1_092075_2023-09-27_final.stac-item
2023-09-30 09:17:32	ga_ls9c_ard_3-2-1_090077_2023-09-29_final.stac-item
2023-10-05 09:33:45	ga_ls9c_ard_3-2-1_093071_2023-10-05_final.stac-item
2023-10-22 10:17:09	ga_ls9c_ard_3-2-1_100071_2023-10-22_final.stac-item
2023-10-31 11:52:34	ga_ls9c_ard_3-2-1_115078_2023-10-31_final.stac-item
2023-11-14 10:26:03	ga_ls9c_ard_3-2-1_101078_2023-11-14_final.stac-item
2023-11-23 10:17:35	ga_ls9c_ard_3-2-1_100072_2023-11-23_final.stac-item
2023-12-01 09:29:22	ga_ls9c_ard_3-2-1_092075_2023-11-30_final.stac-item
2024-01-03 10:09:24	ga_ls9c_ard_3-2-1_099067_2024-01-03_final.stac-item
2024-01-03 11:51:28	ga_ls9c_ard_3-2-1_115075_2024-01-03_final.stac-item
2024-02-18 10:23:16	ga_ls9c_ard_3-2-1_101071_2024-02-18_final.stac-item
2024-02-25 10:28:58	ga_ls9c_ard_3-2-1_102070_2024-02-25_final.stac-item
2024-04-27 09:06:46	ga_ls9c_ard_3-2-1_088082_2024-04-26_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