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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

62 results

Time (local)	Label
2021-11-03 09:52:58	ga_ls9c_ard_3-2-1_096070_2021-11-03_final.stac-item
2022-02-04 11:12:24	ga_ls9c_ard_3-2-1_109070_2022-02-04_final.stac-item
2022-02-14 10:09:20	ga_ls9c_ard_3-2-1_099067_2022-02-14_final.stac-item
2022-02-14 10:16:07	ga_ls9c_ard_3-2-1_099084_2022-02-14_final.stac-item
2022-03-02 10:09:09	ga_ls9c_ard_3-2-1_099067_2022-03-02_final.stac-item
2022-03-10 09:22:31	ga_ls9c_ard_3-2-1_091074_2022-03-09_final.stac-item
2022-04-20 09:20:52	ga_ls9c_ard_3-2-1_090086_2022-04-19_final.stac-item
2022-04-21 10:00:55	ga_ls9c_ard_3-2-1_097078_2022-04-21_final.stac-item
2022-05-24 10:40:20	ga_ls9c_ard_3-2-1_104069_2022-05-24_final.stac-item
2022-06-23 09:16:32	ga_ls9c_ard_3-2-1_090075_2022-06-22_final.stac-item
2022-06-26 11:24:22	ga_ls9c_ard_3-2-1_111070_2022-06-26_final.stac-item
2022-07-27 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-07-27_final.stac-item
2022-08-26 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-08-25_final.stac-item
2022-08-29 11:30:19	ga_ls9c_ard_3-2-1_111084_2022-08-29_final.stac-item
2022-09-02 09:22:43	ga_ls9c_ard_3-2-1_091074_2022-09-01_final.stac-item
2022-09-04 09:12:21	ga_ls9c_ard_3-2-1_089079_2022-09-03_final.stac-item
2022-09-10 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-09-10_final.stac-item
2022-09-18 11:01:41	ga_ls9c_ard_3-2-1_107074_2022-09-18_final.stac-item
2022-10-31 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-10-31_final.stac-item
2022-11-23 10:47:04	ga_ls9c_ard_3-2-1_105068_2022-11-23_final.stac-item
2022-11-24 11:36:43	ga_ls9c_ard_3-2-1_112084_2022-11-24_final.stac-item
2022-11-29 10:13:57	ga_ls9c_ard_3-2-1_099078_2022-11-29_final.stac-item
2022-12-06 10:22:08	ga_ls9c_ard_3-2-1_100083_2022-12-06_final.stac-item
2022-12-19 11:24:55	ga_ls9c_ard_3-2-1_111070_2022-12-19_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 10:47:51	ga_ls9c_ard_3-2-1_105070_2023-01-10_final.stac-item
2023-01-15 11:07:32	ga_ls9c_ard_3-2-1_108073_2023-01-15_final.stac-item
2023-02-14 11:20:47	ga_ls9c_ard_3-2-1_110075_2023-02-14_final.stac-item
2023-02-18 10:55:59	ga_ls9c_ard_3-2-1_106075_2023-02-18_final.stac-item
2023-03-04 11:07:47	ga_ls9c_ard_3-2-1_108074_2023-03-04_final.stac-item
2023-03-05 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-03-05_final.stac-item
2023-03-21 11:51:43	ga_ls9c_ard_3-2-1_115076_2023-03-21_final.stac-item
2023-03-21 11:52:31	ga_ls9c_ard_3-2-1_115078_2023-03-21_final.stac-item
2023-03-25 11:24:33	ga_ls9c_ard_3-2-1_111070_2023-03-25_final.stac-item
2023-04-30 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-04-29_final.stac-item
2023-05-18 10:48:35	ga_ls9c_ard_3-2-1_105074_2023-05-18_final.stac-item
2023-07-12 10:52:47	ga_ls9c_ard_3-2-1_106069_2023-07-12_final.stac-item
2023-07-13 09:59:09	ga_ls9c_ard_3-2-1_097074_2023-07-13_final.stac-item
2023-08-20 10:59:34	ga_ls9c_ard_3-2-1_107070_2023-08-20_final.stac-item
2023-09-03 11:11:41	ga_ls9c_ard_3-2-1_109069_2023-09-03_final.stac-item
2023-09-09 10:34:17	ga_ls9c_ard_3-2-1_103068_2023-09-09_final.stac-item
2023-10-12 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-12_final.stac-item
2023-10-19 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_final.stac-item
2023-10-20 10:30:19	ga_ls9c_ard_3-2-1_102073_2023-10-20_final.stac-item
2023-11-15 09:33:13	ga_ls9c_ard_3-2-1_092085_2023-11-15_final.stac-item
2023-12-23 10:30:25	ga_ls9c_ard_3-2-1_102073_2023-12-23_final.stac-item
2024-01-02 09:28:56	ga_ls9c_ard_3-2-1_092074_2024-01-01_final.stac-item
2024-01-08 10:31:54	ga_ls9c_ard_3-2-1_102077_2024-01-08_final.stac-item
2024-01-14 09:58:27	ga_ls9c_ard_3-2-1_096086_2024-01-14_final.stac-item
2024-01-14 11:32:33	ga_ls9c_ard_3-2-1_112074_2024-01-14_final.stac-item
2024-01-16 11:18:59	ga_ls9c_ard_3-2-1_110071_2024-01-16_final.stac-item
2024-01-28 10:10:23	ga_ls9c_ard_3-2-1_098085_2024-01-28_final.stac-item
2024-02-12 11:00:27	ga_ls9c_ard_3-2-1_107071_2024-02-12_final.stac-item
2024-03-13 09:33:48	ga_ls9c_ard_3-2-1_093071_2024-03-13_final.stac-item
2024-03-31 09:22:53	ga_ls9c_ard_3-2-1_091075_2024-03-30_final.stac-item
2024-04-02 09:13:43	ga_ls9c_ard_3-2-1_089083_2024-04-01_final.stac-item
2024-05-06 10:34:15	ga_ls9c_ard_3-2-1_103069_2024-05-06_final.stac-item
2024-05-13 09:06:42	ga_ls9c_ard_3-2-1_088082_2024-05-12_final.stac-item
2024-05-18 09:21:57	ga_ls9c_ard_3-2-1_091074_2024-05-17_nrt.stac-item
2024-05-18 11:04:26	ga_ls9c_ard_3-2-1_107083_2024-05-18_nrt.stac-item
2024-06-01 09:34:12	ga_ls9c_ard_3-2-1_093074_2024-06-01_nrt.stac-item
2024-06-02 10:17:28	ga_ls9c_ard_3-2-1_100074_2024-06-02_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