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

63 results

Time (local)	Label
2021-11-10 09:37:54	ga_ls9c_ard_3-2-1_094073_2021-11-10_final.stac-item
2021-12-06 09:14:54	ga_ls9c_ard_3-2-1_089085_2021-12-05_final.stac-item
2021-12-22 10:49:17	ga_ls9c_ard_3-2-1_105074_2021-12-22_final.stac-item
2022-02-09 09:52:02	ga_ls9c_ard_3-2-1_096070_2022-02-09_final.stac-item
2022-02-16 09:58:09	ga_ls9c_ard_3-2-1_097070_2022-02-16_final.stac-item
2022-02-27 09:40:41	ga_ls9c_ard_3-2-1_094073_2022-02-27_final.stac-item
2022-04-30 11:32:01	ga_ls9c_ard_3-2-1_112074_2022-04-30_final.stac-item
2022-07-18 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-18_final.stac-item
2022-08-01 09:23:44	ga_ls9c_ard_3-2-1_091077_2022-07-31_final.stac-item
2022-08-06 09:39:57	ga_ls9c_ard_3-2-1_094071_2022-08-06_final.stac-item
2022-08-13 11:24:40	ga_ls9c_ard_3-2-1_111070_2022-08-13_final.stac-item
2022-08-26 09:17:20	ga_ls9c_ard_3-2-1_090076_2022-08-25_final.stac-item
2022-09-20 10:46:56	ga_ls9c_ard_3-2-1_105068_2022-09-20_final.stac-item
2022-09-23 11:18:15	ga_ls9c_ard_3-2-1_110069_2022-09-23_final.stac-item
2022-10-06 10:46:57	ga_ls9c_ard_3-2-1_105068_2022-10-06_final.stac-item
2022-10-16 09:52:50	ga_ls9c_ard_3-2-1_095087_2022-10-16_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-12-07 09:23:19	ga_ls9c_ard_3-2-1_091075_2022-12-06_final.stac-item
2022-12-11 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-12-11_final.stac-item
2022-12-15 10:09:11	ga_ls9c_ard_3-2-1_099066_2022-12-15_final.stac-item
2022-12-19 11:24:31	ga_ls9c_ard_3-2-1_111069_2022-12-19_final.stac-item
2023-01-01 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-12-31_final.stac-item
2023-01-01 10:54:50	ga_ls9c_ard_3-2-1_106072_2023-01-01_final.stac-item
2023-01-03 10:42:29	ga_ls9c_ard_3-2-1_104072_2023-01-03_final.stac-item
2023-01-04 11:24:09	ga_ls9c_ard_3-2-1_111068_2023-01-04_final.stac-item
2023-01-09 10:04:11	ga_ls9c_ard_3-2-1_098069_2023-01-09_final.stac-item
2023-01-16 10:11:54	ga_ls9c_ard_3-2-1_099073_2023-01-16_final.stac-item
2023-02-13 10:35:08	ga_ls9c_ard_3-2-1_103069_2023-02-13_final.stac-item
2023-03-08 10:46:11	ga_ls9c_ard_3-2-1_104082_2023-03-08_final.stac-item
2023-03-09 09:52:32	ga_ls9c_ard_3-2-1_095087_2023-03-09_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
2023-03-30 10:02:54	ga_ls9c_ard_3-2-1_098067_2023-03-30_final.stac-item
2023-03-30 11:44:34	ga_ls9c_ard_3-2-1_114074_2023-03-30_final.stac-item
2023-04-06 10:09:05	ga_ls9c_ard_3-2-1_099067_2023-04-06_final.stac-item
2023-05-09 09:16:45	ga_ls9c_ard_3-2-1_090076_2023-05-08_final.stac-item
2023-05-22 10:27:00	ga_ls9c_ard_3-2-1_101082_2023-05-22_final.stac-item
2023-06-10 09:20:53	ga_ls9c_ard_3-2-1_090087_2023-06-09_final.stac-item
2023-06-11 09:56:33	ga_ls9c_ard_3-2-1_097068_2023-06-11_final.stac-item
2023-07-03 09:27:10	ga_ls9c_ard_3-2-1_091087_2023-07-02_final.stac-item
2023-07-03 09:28:22	ga_ls9c_ard_3-2-1_091090_2023-07-02_final.stac-item
2023-07-13 11:40:50	ga_ls9c_ard_3-2-1_113081_2023-07-13_final.stac-item
2023-07-17 11:13:20	ga_ls9c_ard_3-2-1_109074_2023-07-17_final.stac-item
2023-08-20 09:21:29	ga_ls9c_ard_3-2-1_091072_2023-08-19_final.stac-item
2023-08-27 09:34:09	ga_ls9c_ard_3-2-1_092088_2023-08-27_final.stac-item
2023-09-13 10:08:48	ga_ls9c_ard_3-2-1_099066_2023-09-13_final.stac-item
2023-09-14 09:17:10	ga_ls9c_ard_3-2-1_090076_2023-09-13_final.stac-item
2023-09-29 10:10:44	ga_ls9c_ard_3-2-1_099071_2023-09-29_final.stac-item
2023-10-03 09:46:53	ga_ls9c_ard_3-2-1_095073_2023-10-03_final.stac-item
2023-11-17 09:17:41	ga_ls9c_ard_3-2-1_090077_2023-11-16_final.stac-item
2023-12-10 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-12-10_final.stac-item
2023-12-18 10:09:04	ga_ls9c_ard_3-2-1_099066_2023-12-18_final.stac-item
2023-12-28 10:50:08	ga_ls9c_ard_3-2-1_105076_2023-12-28_final.stac-item
2024-01-02 11:07:49	ga_ls9c_ard_3-2-1_108074_2024-01-02_final.stac-item
2024-01-04 09:22:08	ga_ls9c_ard_3-2-1_090088_2024-01-03_final.stac-item
2024-01-07 11:25:55	ga_ls9c_ard_3-2-1_111073_2024-01-07_final.stac-item
2024-02-14 10:49:40	ga_ls9c_ard_3-2-1_105075_2024-02-14_final.stac-item
2024-03-08 09:17:17	ga_ls9c_ard_3-2-1_090076_2024-03-07_final.stac-item
2024-03-25 09:57:40	ga_ls9c_ard_3-2-1_097069_2024-03-25_final.stac-item
2024-04-01 10:03:45	ga_ls9c_ard_3-2-1_098069_2024-04-01_final.stac-item
2024-04-14 11:14:02	ga_ls9c_ard_3-2-1_109075_2024-04-14_final.stac-item
2024-04-20 10:34:01	ga_ls9c_ard_3-2-1_103068_2024-04-20_interim.stac-item
2024-04-27 09:07:09	ga_ls9c_ard_3-2-1_088083_2024-04-26_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