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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
2021-12-04 09:25:17	ga_ls9c_ard_3-2-1_091080_2021-12-03_final.stac-item
2021-12-17 10:29:32	ga_ls9c_ard_3-2-1_102071_2021-12-17_final.stac-item
2021-12-28 10:14:36	ga_ls9c_ard_3-2-1_099080_2021-12-28_final.stac-item
2021-12-28 10:16:36	ga_ls9c_ard_3-2-1_099085_2021-12-28_final.stac-item
2021-12-29 09:19:23	ga_ls9c_ard_3-2-1_090081_2021-12-28_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-02-02 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-02-02_final.stac-item
2022-02-08 10:49:15	ga_ls9c_ard_3-2-1_105074_2022-02-08_final.stac-item
2022-02-09 09:58:01	ga_ls9c_ard_3-2-1_096085_2022-02-09_final.stac-item
2022-02-09 11:32:31	ga_ls9c_ard_3-2-1_112074_2022-02-09_final.stac-item
2022-03-23 10:28:50	ga_ls9c_ard_3-2-1_102070_2022-03-23_final.stac-item
2022-04-16 11:20:08	ga_ls9c_ard_3-2-1_110075_2022-04-16_final.stac-item
2022-04-20 10:55:45	ga_ls9c_ard_3-2-1_106076_2022-04-20_final.stac-item
2022-05-05 10:15:37	ga_ls9c_ard_3-2-1_099084_2022-05-05_final.stac-item
2022-05-13 11:02:11	ga_ls9c_ard_3-2-1_107077_2022-05-13_final.stac-item
2022-06-04 10:27:01	ga_ls9c_ard_3-2-1_101082_2022-06-04_final.stac-item
2022-07-05 09:46:04	ga_ls9c_ard_3-2-1_094087_2022-07-05_final.stac-item
2022-07-28 09:46:25	ga_ls9c_ard_3-2-1_095072_2022-07-28_final.stac-item
2022-09-07 11:23:43	ga_ls9c_ard_3-2-1_110083_2022-09-07_final.stac-item
2022-10-02 11:14:53	ga_ls9c_ard_3-2-1_109076_2022-10-02_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-11-05 09:23:41	ga_ls9c_ard_3-2-1_091076_2022-11-04_final.stac-item
2022-11-14 10:56:27	ga_ls9c_ard_3-2-1_106076_2022-11-14_final.stac-item
2022-11-16 10:40:54	ga_ls9c_ard_3-2-1_104068_2022-11-16_final.stac-item
2022-11-19 09:35:43	ga_ls9c_ard_3-2-1_093075_2022-11-19_final.stac-item
2022-11-23 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-11-22_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-25 10:47:48	ga_ls9c_ard_3-2-1_105070_2022-12-25_final.stac-item
2022-12-26 09:52:12	ga_ls9c_ard_3-2-1_096070_2022-12-26_final.stac-item
2023-01-07 10:22:09	ga_ls9c_ard_3-2-1_100083_2023-01-07_final.stac-item
2023-01-17 09:22:38	ga_ls9c_ard_3-2-1_090089_2023-01-16_final.stac-item
2023-01-17 10:55:32	ga_ls9c_ard_3-2-1_106074_2023-01-17_final.stac-item
2023-02-01 10:14:23	ga_ls9c_ard_3-2-1_099079_2023-02-01_final.stac-item
2023-02-01 11:53:16	ga_ls9c_ard_3-2-1_115079_2023-02-01_final.stac-item
2023-03-06 09:22:30	ga_ls9c_ard_3-2-1_090089_2023-03-05_final.stac-item
2023-03-15 09:13:28	ga_ls9c_ard_3-2-1_089082_2023-03-14_final.stac-item
2023-03-21 10:10:50	ga_ls9c_ard_3-2-1_099071_2023-03-21_final.stac-item
2023-05-10 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-05-10_final.stac-item
2023-05-17 10:03:20	ga_ls9c_ard_3-2-1_098069_2023-05-17_final.stac-item
2023-06-01 09:21:57	ga_ls9c_ard_3-2-1_091074_2023-05-31_final.stac-item
2023-06-20 09:57:30	ga_ls9c_ard_3-2-1_096086_2023-06-20_final.stac-item
2023-07-12 10:57:10	ga_ls9c_ard_3-2-1_106080_2023-07-12_final.stac-item
2023-07-30 09:06:48	ga_ls9c_ard_3-2-1_088082_2023-07-29_final.stac-item
2023-09-02 10:30:01	ga_ls9c_ard_3-2-1_102073_2023-09-02_final.stac-item
2023-09-12 09:33:07	ga_ls9c_ard_3-2-1_092085_2023-09-12_final.stac-item
2023-09-19 11:13:48	ga_ls9c_ard_3-2-1_109074_2023-09-19_final.stac-item
2023-09-24 09:52:14	ga_ls9c_ard_3-2-1_096071_2023-09-24_final.stac-item
2023-10-03 09:47:17	ga_ls9c_ard_3-2-1_095074_2023-10-03_final.stac-item
2023-10-26 11:31:42	ga_ls9c_ard_3-2-1_112072_2023-10-26_final.stac-item
2023-10-28 09:40:50	ga_ls9c_ard_3-2-1_094073_2023-10-28_final.stac-item
2023-11-02 09:58:06	ga_ls9c_ard_3-2-1_097070_2023-11-02_final.stac-item
2023-11-08 09:21:51	ga_ls9c_ard_3-2-1_091072_2023-11-07_final.stac-item
2023-12-07 10:30:17	ga_ls9c_ard_3-2-1_102073_2023-12-07_final.stac-item
2023-12-08 11:17:32	ga_ls9c_ard_3-2-1_109083_2023-12-08_final.stac-item
2023-12-25 10:17:39	ga_ls9c_ard_3-2-1_100072_2023-12-25_final.stac-item
2024-01-07 09:46:14	ga_ls9c_ard_3-2-1_095071_2024-01-07_final.stac-item
2024-01-29 09:13:35	ga_ls9c_ard_3-2-1_089082_2024-01-28_final.stac-item
2024-02-05 10:54:18	ga_ls9c_ard_3-2-1_106071_2024-02-05_final.stac-item
2024-02-06 09:58:17	ga_ls9c_ard_3-2-1_097070_2024-02-06_final.stac-item
2024-02-06 09:58:41	ga_ls9c_ard_3-2-1_097071_2024-02-06_final.stac-item
2024-02-06 09:59:53	ga_ls9c_ard_3-2-1_097074_2024-02-06_final.stac-item
2024-02-06 11:41:33	ga_ls9c_ard_3-2-1_113081_2024-02-06_final.stac-item
2024-02-18 10:23:16	ga_ls9c_ard_3-2-1_101071_2024-02-18_final.stac-item
2024-02-21 09:18:01	ga_ls9c_ard_3-2-1_090078_2024-02-20_final.stac-item
2024-02-26 11:14:38	ga_ls9c_ard_3-2-1_109076_2024-02-26_final.stac-item
2024-03-28 10:28:30	ga_ls9c_ard_3-2-1_102069_2024-03-28_final.stac-item
2024-04-17 10:06:47	ga_ls9c_ard_3-2-1_098077_2024-04-17_final.stac-item
2024-04-25 10:55:36	ga_ls9c_ard_3-2-1_106076_2024-04-25_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