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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

53 results

Time (local)	Label
2021-12-06 10:49:24	ga_ls9c_ard_3-2-1_105074_2021-12-06_final.stac-item
2022-01-19 09:34:18	ga_ls9c_ard_3-2-1_093072_2022-01-19_final.stac-item
2022-02-20 11:14:16	ga_ls9c_ard_3-2-1_109075_2022-02-20_final.stac-item
2022-02-22 09:22:36	ga_ls9c_ard_3-2-1_091074_2022-02-21_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-06-01 11:31:48	ga_ls9c_ard_3-2-1_112074_2022-06-01_final.stac-item
2022-07-02 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-02_final.stac-item
2022-07-03 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-07-03_final.stac-item
2022-07-08 10:14:10	ga_ls9c_ard_3-2-1_099080_2022-07-08_final.stac-item
2022-07-11 09:06:57	ga_ls9c_ard_3-2-1_088082_2022-07-10_final.stac-item
2022-07-19 11:31:21	ga_ls9c_ard_3-2-1_112072_2022-07-19_final.stac-item
2022-07-25 09:21:28	ga_ls9c_ard_3-2-1_090087_2022-07-24_final.stac-item
2022-07-26 09:57:09	ga_ls9c_ard_3-2-1_097068_2022-07-26_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-09-25 09:29:01	ga_ls9c_ard_3-2-1_092074_2022-09-24_final.stac-item
2022-10-28 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-10-28_final.stac-item
2022-11-08 11:32:43	ga_ls9c_ard_3-2-1_112074_2022-11-08_final.stac-item
2022-11-14 09:21:10	ga_ls9c_ard_3-2-1_090085_2022-11-13_final.stac-item
2022-12-16 09:17:33	ga_ls9c_ard_3-2-1_090076_2022-12-15_final.stac-item
2022-12-25 09:13:19	ga_ls9c_ard_3-2-1_089081_2022-12-24_final.stac-item
2023-02-07 09:35:21	ga_ls9c_ard_3-2-1_093074_2023-02-07_final.stac-item
2023-03-28 11:57:22	ga_ls9c_ard_3-2-1_116075_2023-03-28_final.stac-item
2023-03-29 09:26:26	ga_ls9c_ard_3-2-1_091084_2023-03-28_final.stac-item
2023-04-17 11:31:19	ga_ls9c_ard_3-2-1_112072_2023-04-17_final.stac-item
2023-05-13 10:27:42	ga_ls9c_ard_3-2-1_102068_2023-05-13_final.stac-item
2023-06-14 10:32:36	ga_ls9c_ard_3-2-1_102081_2023-06-14_final.stac-item
2023-06-19 09:10:39	ga_ls9c_ard_3-2-1_089077_2023-06-18_final.stac-item
2023-06-25 10:13:38	ga_ls9c_ard_3-2-1_099080_2023-06-25_final.stac-item
2023-07-15 11:28:29	ga_ls9c_ard_3-2-1_111081_2023-07-15_final.stac-item
2023-07-27 10:13:32	ga_ls9c_ard_3-2-1_099079_2023-07-27_final.stac-item
2023-09-03 11:14:29	ga_ls9c_ard_3-2-1_109076_2023-09-03_final.stac-item
2023-09-15 09:57:15	ga_ls9c_ard_3-2-1_097068_2023-09-15_final.stac-item
2023-10-05 09:34:33	ga_ls9c_ard_3-2-1_093073_2023-10-05_final.stac-item
2023-10-23 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-10-23_final.stac-item
2023-10-30 09:28:50	ga_ls9c_ard_3-2-1_092074_2023-10-29_final.stac-item
2023-11-07 10:19:52	ga_ls9c_ard_3-2-1_100078_2023-11-07_final.stac-item
2023-11-24 09:27:58	ga_ls9c_ard_3-2-1_091087_2023-11-23_final.stac-item
2023-11-28 10:36:09	ga_ls9c_ard_3-2-1_103072_2023-11-28_final.stac-item
2023-12-02 10:14:13	ga_ls9c_ard_3-2-1_099079_2023-12-02_final.stac-item
2023-12-26 09:23:37	ga_ls9c_ard_3-2-1_091076_2023-12-25_final.stac-item
2024-01-01 10:25:46	ga_ls9c_ard_3-2-1_101077_2024-01-01_final.stac-item
2024-01-02 09:28:08	ga_ls9c_ard_3-2-1_092072_2024-01-01_final.stac-item
2024-01-03 10:11:23	ga_ls9c_ard_3-2-1_099072_2024-01-03_final.stac-item
2024-01-27 09:29:07	ga_ls9c_ard_3-2-1_091090_2024-01-26_final.stac-item
2024-01-28 10:07:12	ga_ls9c_ard_3-2-1_098077_2024-01-28_final.stac-item
2024-02-08 11:24:24	ga_ls9c_ard_3-2-1_111069_2024-02-08_final.stac-item
2024-02-12 09:23:34	ga_ls9c_ard_3-2-1_091076_2024-02-11_final.stac-item
2024-02-25 10:28:58	ga_ls9c_ard_3-2-1_102070_2024-02-25_final.stac-item
2024-02-26 09:34:09	ga_ls9c_ard_3-2-1_093072_2024-02-26_final.stac-item
2024-03-11 11:26:40	ga_ls9c_ard_3-2-1_111075_2024-03-11_final.stac-item
2024-04-11 10:42:22	ga_ls9c_ard_3-2-1_104073_2024-04-11_final.stac-item
2024-04-29 10:33:16	ga_ls9c_ard_3-2-1_102082_2024-04-29_final.stac-item
2024-05-04 09:09:43	ga_ls9c_ard_3-2-1_089074_2024-05-03_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