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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
2021-11-22 09:23:40	ga_ls9c_ard_3-2-1_091072_2021-11-21_final.stac-item
2021-11-24 10:41:59	ga_ls9c_ard_3-2-1_104068_2021-11-24_final.stac-item
2021-12-08 10:35:01	ga_ls9c_ard_3-2-1_103069_2021-12-08_final.stac-item
2021-12-22 09:10:24	ga_ls9c_ard_3-2-1_089074_2021-12-21_final.stac-item
2021-12-28 10:14:12	ga_ls9c_ard_3-2-1_099079_2021-12-28_final.stac-item
2022-01-01 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-01-01_final.stac-item
2022-01-05 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-05_final.stac-item
2022-01-12 09:34:29	ga_ls9c_ard_3-2-1_092088_2022-01-12_final.stac-item
2022-02-07 10:09:59	ga_ls9c_ard_3-2-1_098084_2022-02-07_final.stac-item
2022-02-26 10:39:30	ga_ls9c_ard_3-2-1_103081_2022-02-26_final.stac-item
2022-03-12 09:12:09	ga_ls9c_ard_3-2-1_089079_2022-03-11_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-04-11 09:27:34	ga_ls9c_ard_3-2-1_091087_2022-04-10_final.stac-item
2022-04-20 09:22:28	ga_ls9c_ard_3-2-1_090090_2022-04-19_final.stac-item
2022-05-29 09:27:11	ga_ls9c_ard_3-2-1_091087_2022-05-28_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-06-04 10:25:01	ga_ls9c_ard_3-2-1_101077_2022-06-04_final.stac-item
2022-07-12 11:26:42	ga_ls9c_ard_3-2-1_111076_2022-07-12_final.stac-item
2022-07-19 09:53:15	ga_ls9c_ard_3-2-1_096074_2022-07-19_final.stac-item
2022-09-11 09:22:56	ga_ls9c_ard_3-2-1_090090_2022-09-10_final.stac-item
2022-09-14 09:52:16	ga_ls9c_ard_3-2-1_095086_2022-09-14_final.stac-item
2022-09-16 09:33:56	ga_ls9c_ard_3-2-1_093071_2022-09-16_final.stac-item
2022-09-16 09:34:44	ga_ls9c_ard_3-2-1_093073_2022-09-16_final.stac-item
2022-09-19 10:10:03	ga_ls9c_ard_3-2-1_098084_2022-09-19_final.stac-item
2022-09-24 10:25:02	ga_ls9c_ard_3-2-1_101075_2022-09-24_final.stac-item
2022-10-13 10:53:13	ga_ls9c_ard_3-2-1_106068_2022-10-13_final.stac-item
2022-10-16 11:26:32	ga_ls9c_ard_3-2-1_111074_2022-10-16_final.stac-item
2022-10-29 09:17:56	ga_ls9c_ard_3-2-1_090077_2022-10-28_final.stac-item
2022-11-05 09:29:17	ga_ls9c_ard_3-2-1_091090_2022-11-04_final.stac-item
2022-11-13 10:09:36	ga_ls9c_ard_3-2-1_099067_2022-11-13_final.stac-item
2022-11-13 10:10:00	ga_ls9c_ard_3-2-1_099068_2022-11-13_final.stac-item
2022-11-13 10:10:48	ga_ls9c_ard_3-2-1_099070_2022-11-13_final.stac-item
2022-11-22 10:06:12	ga_ls9c_ard_3-2-1_098074_2022-11-22_final.stac-item
2022-11-24 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-24_final.stac-item
2022-12-07 09:23:19	ga_ls9c_ard_3-2-1_091075_2022-12-06_nrt.stac-item
2022-12-14 09:33:06	ga_ls9c_ard_3-2-1_092084_2022-12-14_final.stac-item
2022-12-24 10:04:32	ga_ls9c_ard_3-2-1_098070_2022-12-24_final.stac-item
2023-01-09 10:03:48	ga_ls9c_ard_3-2-1_098068_2023-01-09_final.stac-item
2023-01-10 09:15:21	ga_ls9c_ard_3-2-1_089086_2023-01-09_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-01-26 10:52:35	ga_ls9c_ard_3-2-1_105082_2023-01-26_final.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
2023-02-27 09:10:23	ga_ls9c_ard_3-2-1_089074_2023-02-26_final.stac-item
2023-03-11 11:11:52	ga_ls9c_ard_3-2-1_109069_2023-03-11_final.stac-item
2023-03-13 09:22:38	ga_ls9c_ard_3-2-1_091074_2023-03-12_final.stac-item
2023-06-22 11:17:38	ga_ls9c_ard_3-2-1_110070_2023-06-22_final.stac-item
2023-07-01 09:39:54	ga_ls9c_ard_3-2-1_093088_2023-07-01_final.stac-item
2023-07-03 09:25:58	ga_ls9c_ard_3-2-1_091084_2023-07-02_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
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-08-03 11:57:55	ga_ls9c_ard_3-2-1_116077_2023-08-03_final.stac-item
2023-08-06 09:15:51	ga_ls9c_ard_3-2-1_089089_2023-08-05_final.stac-item
2023-08-16 11:28:39	ga_ls9c_ard_3-2-1_111081_2023-08-16_final.stac-item
2023-09-28 11:07:08	ga_ls9c_ard_3-2-1_108073_2023-09-28_final.stac-item
2023-11-20 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-11-20_final.stac-item
2023-12-17 11:08:40	ga_ls9c_ard_3-2-1_108076_2023-12-17_final.stac-item
2023-12-24 09:33:59	ga_ls9c_ard_3-2-1_093071_2023-12-24_final.stac-item
2023-12-31 11:19:48	ga_ls9c_ard_3-2-1_110073_2023-12-31_final.stac-item
2024-01-13 09:14:47	ga_ls9c_ard_3-2-1_089085_2024-01-12_final.stac-item
2024-02-08 09:47:31	ga_ls9c_ard_3-2-1_095074_2024-02-08_final.stac-item
2024-02-27 10:19:49	ga_ls9c_ard_3-2-1_100078_2024-02-27_final.stac-item
2024-02-29 10:07:29	ga_ls9c_ard_3-2-1_098078_2024-02-29_final.stac-item
2024-03-18 09:58:20	ga_ls9c_ard_3-2-1_096086_2024-03-18_final.stac-item
2024-03-20 11:19:15	ga_ls9c_ard_3-2-1_110072_2024-03-20_final.stac-item
2024-04-05 11:19:06	ga_ls9c_ard_3-2-1_110072_2024-04-05_final.stac-item
2024-04-10 09:58:43	ga_ls9c_ard_3-2-1_097072_2024-04-10_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