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
2021-11-07 09:19:28	ga_ls9c_ard_3-2-1_090080_2021-11-06_final.stac-item
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final.stac-item
2021-12-28 11:51:30	ga_ls9c_ard_3-2-1_115075_2021-12-28_final.stac-item
2022-01-29 11:52:41	ga_ls9c_ard_3-2-1_115078_2022-01-29_final.stac-item
2022-02-07 11:44:53	ga_ls9c_ard_3-2-1_114074_2022-02-07_final.stac-item
2022-02-27 09:41:05	ga_ls9c_ard_3-2-1_094074_2022-02-27_final.stac-item
2022-03-10 09:27:42	ga_ls9c_ard_3-2-1_091087_2022-03-09_final.stac-item
2022-03-29 09:57:43	ga_ls9c_ard_3-2-1_096085_2022-03-29_final.stac-item
2022-06-16 10:49:02	ga_ls9c_ard_3-2-1_105075_2022-06-16_final.stac-item
2022-07-26 09:57:57	ga_ls9c_ard_3-2-1_097070_2022-07-26_final.stac-item
2022-08-03 10:49:29	ga_ls9c_ard_3-2-1_105075_2022-08-03_final.stac-item
2022-08-22 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-08-22_final.stac-item
2022-08-29 11:26:19	ga_ls9c_ard_3-2-1_111074_2022-08-29_final.stac-item
2022-09-23 09:44:10	ga_ls9c_ard_3-2-1_094081_2022-09-23_final.stac-item
2022-10-04 09:23:14	ga_ls9c_ard_3-2-1_091075_2022-10-03_final.stac-item
2022-10-04 11:01:43	ga_ls9c_ard_3-2-1_107074_2022-10-04_final.stac-item
2022-10-12 10:13:56	ga_ls9c_ard_3-2-1_099078_2022-10-12_final.stac-item
2022-10-13 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-10-13_final.stac-item
2022-10-25 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-10-25_final.stac-item
2022-11-05 11:02:11	ga_ls9c_ard_3-2-1_107075_2022-11-05_final.stac-item
2022-11-18 10:30:08	ga_ls9c_ard_3-2-1_102072_2022-11-18_final.stac-item
2022-12-03 11:24:30	ga_ls9c_ard_3-2-1_111069_2022-12-03_final.stac-item
2022-12-12 11:20:45	ga_ls9c_ard_3-2-1_110075_2022-12-12_final.stac-item
2023-01-02 10:04:00	ga_ls9c_ard_3-2-1_097084_2023-01-02_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-22 09:38:44	ga_ls9c_ard_3-2-1_093083_2023-01-22_final.stac-item
2023-01-26 09:14:06	ga_ls9c_ard_3-2-1_089083_2023-01-25_final.stac-item
2023-01-30 10:23:56	ga_ls9c_ard_3-2-1_101072_2023-01-30_final.stac-item
2023-01-31 11:06:00	ga_ls9c_ard_3-2-1_108069_2023-01-31_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-03-06 10:54:35	ga_ls9c_ard_3-2-1_106072_2023-03-06_final.stac-item
2023-03-13 09:25:25	ga_ls9c_ard_3-2-1_091081_2023-03-12_final.stac-item
2023-03-31 09:12:52	ga_ls9c_ard_3-2-1_089081_2023-03-30_final.stac-item
2023-04-30 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-04-29_final.stac-item
2023-05-25 10:55:27	ga_ls9c_ard_3-2-1_106076_2023-05-25_final.stac-item
2023-05-28 09:46:17	ga_ls9c_ard_3-2-1_095073_2023-05-28_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-21 10:35:10	ga_ls9c_ard_3-2-1_103072_2023-06-21_final.stac-item
2023-06-22 09:39:57	ga_ls9c_ard_3-2-1_094073_2023-06-22_final.stac-item
2023-06-24 09:27:59	ga_ls9c_ard_3-2-1_092074_2023-06-23_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-08-03 10:16:38	ga_ls9c_ard_3-2-1_100071_2023-08-03_final.stac-item
2023-08-30 11:37:35	ga_ls9c_ard_3-2-1_113072_2023-08-30_final.stac-item
2023-09-26 09:41:02	ga_ls9c_ard_3-2-1_094074_2023-09-26_final.stac-item
2023-10-18 10:41:28	ga_ls9c_ard_3-2-1_104070_2023-10-18_final.stac-item
2023-10-23 09:23:55	ga_ls9c_ard_3-2-1_091077_2023-10-22_final.stac-item
2023-11-03 09:06:27	ga_ls9c_ard_3-2-1_088080_2023-11-02_final.stac-item
2023-11-06 09:40:35	ga_ls9c_ard_3-2-1_093088_2023-11-06_final.stac-item
2023-11-15 09:33:37	ga_ls9c_ard_3-2-1_092086_2023-11-15_final.stac-item
2023-11-22 11:12:00	ga_ls9c_ard_3-2-1_109069_2023-11-22_final.stac-item
2023-11-23 10:17:35	ga_ls9c_ard_3-2-1_100072_2023-11-23_final.stac-item
2023-12-28 10:52:55	ga_ls9c_ard_3-2-1_105083_2023-12-28_final.stac-item
2023-12-31 11:20:36	ga_ls9c_ard_3-2-1_110075_2023-12-31_final.stac-item
2024-01-01 10:25:22	ga_ls9c_ard_3-2-1_101076_2024-01-01_final.stac-item
2024-01-02 11:06:13	ga_ls9c_ard_3-2-1_108070_2024-01-02_final.stac-item
2024-01-03 10:12:59	ga_ls9c_ard_3-2-1_099076_2024-01-03_final.stac-item
2024-01-11 09:23:57	ga_ls9c_ard_3-2-1_091077_2024-01-10_final.stac-item
2024-01-18 09:28:56	ga_ls9c_ard_3-2-1_092074_2024-01-17_final.stac-item
2024-01-18 11:05:49	ga_ls9c_ard_3-2-1_108069_2024-01-18_final.stac-item
2024-01-27 11:00:49	ga_ls9c_ard_3-2-1_107072_2024-01-27_final.stac-item
2024-03-15 09:27:02	ga_ls9c_ard_3-2-1_091085_2024-03-14_final.stac-item
2024-03-27 09:52:26	ga_ls9c_ard_3-2-1_095087_2024-03-27_final.stac-item
2024-04-24 11:50:49	ga_ls9c_ard_3-2-1_115075_2024-04-24_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