Search ga_ls9c_ard_3 whole collection

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

49 results

Time (local)	Label
2021-11-08 09:55:27	ga_ls9c_ard_3-2-1_097070_2021-11-08_final.stac-item
2021-11-11 10:18:39	ga_ls9c_ard_3-2-1_100075_2021-11-11_final.stac-item
2021-11-18 09:59:35	ga_ls9c_ard_3-2-1_097068_2021-11-18_final.stac-item
2022-01-10 11:18:10	ga_ls9c_ard_3-2-1_110069_2022-01-10_final.stac-item
2022-01-23 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-23_final.stac-item
2022-01-29 10:14:12	ga_ls9c_ard_3-2-1_099079_2022-01-29_final.stac-item
2022-02-04 11:14:47	ga_ls9c_ard_3-2-1_109076_2022-02-04_final.stac-item
2022-02-14 10:10:08	ga_ls9c_ard_3-2-1_099069_2022-02-14_final.stac-item
2022-03-01 09:28:41	ga_ls9c_ard_3-2-1_092074_2022-02-28_final.stac-item
2022-03-06 11:24:07	ga_ls9c_ard_3-2-1_111069_2022-03-06_final.stac-item
2022-04-11 09:22:22	ga_ls9c_ard_3-2-1_091074_2022-04-10_final.stac-item
2022-04-26 10:21:27	ga_ls9c_ard_3-2-1_100083_2022-04-26_final.stac-item
2022-06-10 09:45:33	ga_ls9c_ard_3-2-1_095071_2022-06-10_final.stac-item
2022-06-26 11:24:22	ga_ls9c_ard_3-2-1_111070_2022-06-26_final.stac-item
2022-07-12 11:26:42	ga_ls9c_ard_3-2-1_111076_2022-07-12_final.stac-item
2022-08-06 11:24:01	ga_ls9c_ard_3-2-1_110084_2022-08-06_final.stac-item
2022-08-17 09:28:16	ga_ls9c_ard_3-2-1_091088_2022-08-16_final.stac-item
2022-08-18 10:09:57	ga_ls9c_ard_3-2-1_098084_2022-08-18_final.stac-item
2022-08-25 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-08-25_final.stac-item
2022-09-05 09:57:36	ga_ls9c_ard_3-2-1_096084_2022-09-05_final.stac-item
2022-09-11 10:55:50	ga_ls9c_ard_3-2-1_106075_2022-09-11_final.stac-item
2022-09-28 09:59:31	ga_ls9c_ard_3-2-1_097073_2022-09-28_final.stac-item
2022-10-06 10:52:32	ga_ls9c_ard_3-2-1_105082_2022-10-06_final.stac-item
2022-10-29 10:56:01	ga_ls9c_ard_3-2-1_106075_2022-10-29_final.stac-item
2022-12-03 11:24:54	ga_ls9c_ard_3-2-1_111070_2022-12-03_final.stac-item
2022-12-26 11:32:41	ga_ls9c_ard_3-2-1_112074_2022-12-26_final.stac-item
2023-01-01 09:22:20	ga_ls9c_ard_3-2-1_090088_2022-12-31_final.stac-item
2023-01-24 09:23:14	ga_ls9c_ard_3-2-1_091075_2023-01-23_final.stac-item
2023-02-13 10:35:08	ga_ls9c_ard_3-2-1_103069_2023-02-13_final.stac-item
2023-02-21 11:24:02	ga_ls9c_ard_3-2-1_111068_2023-02-21_final.stac-item
2023-03-21 10:09:15	ga_ls9c_ard_3-2-1_099067_2023-03-21_final.stac-item
2023-04-01 11:31:25	ga_ls9c_ard_3-2-1_112072_2023-04-01_final.stac-item
2023-04-03 11:23:51	ga_ls9c_ard_3-2-1_110084_2023-04-03_final.stac-item
2023-07-04 11:46:32	ga_ls9c_ard_3-2-1_114080_2023-07-04_final.stac-item
2023-08-12 10:13:17	ga_ls9c_ard_3-2-1_099078_2023-08-12_final.stac-item
2023-08-17 10:33:25	ga_ls9c_ard_3-2-1_102082_2023-08-17_final.stac-item
2023-09-12 09:34:19	ga_ls9c_ard_3-2-1_092088_2023-09-12_final.stac-item
2023-10-15 10:10:09	ga_ls9c_ard_3-2-1_099069_2023-10-15_final.stac-item
2023-10-21 09:39:29	ga_ls9c_ard_3-2-1_093085_2023-10-21_final.stac-item
2023-11-17 09:22:53	ga_ls9c_ard_3-2-1_090090_2023-11-16_final.stac-item
2023-11-22 09:34:43	ga_ls9c_ard_3-2-1_093073_2023-11-22_final.stac-item
2023-11-22 11:12:00	ga_ls9c_ard_3-2-1_109069_2023-11-22_final.stac-item
2023-12-08 11:14:45	ga_ls9c_ard_3-2-1_109076_2023-12-08_final.stac-item
2024-02-03 11:05:51	ga_ls9c_ard_3-2-1_108069_2024-02-03_final.stac-item
2024-02-06 09:59:53	ga_ls9c_ard_3-2-1_097074_2024-02-06_final.stac-item
2024-03-15 11:01:31	ga_ls9c_ard_3-2-1_107074_2024-03-15_final.stac-item
2024-03-29 09:34:27	ga_ls9c_ard_3-2-1_093073_2024-03-29_final.stac-item
2024-04-01 10:03:22	ga_ls9c_ard_3-2-1_098068_2024-04-01_final.stac-item
2024-04-25 10:55:36	ga_ls9c_ard_3-2-1_106076_2024-04-25_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