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

73 results

Time (local)	Label
2022-01-13 10:11:21	ga_ls9c_ard_3-2-1_099072_2022-01-13_final.stac-item
2022-01-13 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-01-13_final.stac-item
2022-02-07 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-02-07_final.stac-item
2022-03-03 09:21:30	ga_ls9c_ard_3-2-1_090087_2022-03-02_final.stac-item
2022-03-12 10:49:26	ga_ls9c_ard_3-2-1_105075_2022-03-12_final.stac-item
2022-04-26 10:20:39	ga_ls9c_ard_3-2-1_100081_2022-04-26_final.stac-item
2022-04-27 09:27:25	ga_ls9c_ard_3-2-1_091087_2022-04-26_final.stac-item
2022-04-28 10:02:42	ga_ls9c_ard_3-2-1_098067_2022-04-28_final.stac-item
2022-05-08 09:06:49	ga_ls9c_ard_3-2-1_088082_2022-05-07_final.stac-item
2022-05-13 09:28:05	ga_ls9c_ard_3-2-1_091089_2022-05-12_final.stac-item
2022-05-14 10:02:33	ga_ls9c_ard_3-2-1_098067_2022-05-14_final.stac-item
2022-05-25 09:51:30	ga_ls9c_ard_3-2-1_095086_2022-05-25_final.stac-item
2022-05-27 09:39:08	ga_ls9c_ard_3-2-1_093086_2022-05-27_final.stac-item
2022-06-15 10:03:22	ga_ls9c_ard_3-2-1_098069_2022-06-15_final.stac-item
2022-07-28 09:46:25	ga_ls9c_ard_3-2-1_095072_2022-07-28_final.stac-item
2022-07-28 09:52:00	ga_ls9c_ard_3-2-1_095086_2022-07-28_final.stac-item
2022-09-11 10:53:02	ga_ls9c_ard_3-2-1_106068_2022-09-11_final.stac-item
2022-09-25 11:06:18	ga_ls9c_ard_3-2-1_108070_2022-09-25_final.stac-item
2022-10-01 10:28:26	ga_ls9c_ard_3-2-1_102068_2022-10-01_final.stac-item
2022-10-13 10:53:13	ga_ls9c_ard_3-2-1_106068_2022-10-13_final.stac-item
2022-10-18 11:14:34	ga_ls9c_ard_3-2-1_109075_2022-10-18_final.stac-item
2022-10-30 10:02:24	ga_ls9c_ard_3-2-1_097080_2022-10-30_final.stac-item
2022-11-04 10:17:18	ga_ls9c_ard_3-2-1_100071_2022-11-04_final.stac-item
2022-11-07 10:50:14	ga_ls9c_ard_3-2-1_105076_2022-11-07_final.stac-item
2022-11-09 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-11-09_final.stac-item
2022-11-11 10:23:33	ga_ls9c_ard_3-2-1_101071_2022-11-11_final.stac-item
2022-11-20 10:17:22	ga_ls9c_ard_3-2-1_100071_2022-11-20_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-12-19 09:46:26	ga_ls9c_ard_3-2-1_095071_2022-12-19_final.stac-item
2022-12-24 10:04:32	ga_ls9c_ard_3-2-1_098070_2022-12-24_final.stac-item
2023-01-04 09:46:52	ga_ls9c_ard_3-2-1_095072_2023-01-04_final.stac-item
2023-01-10 09:11:45	ga_ls9c_ard_3-2-1_089077_2023-01-09_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-15 10:23:33	ga_ls9c_ard_3-2-1_101071_2023-02-15_final.stac-item
2023-02-18 09:17:54	ga_ls9c_ard_3-2-1_090077_2023-02-17_final.stac-item
2023-02-20 09:05:06	ga_ls9c_ard_3-2-1_088076_2023-02-19_interim.stac-item
2023-02-27 09:10:47	ga_ls9c_ard_3-2-1_089075_2023-02-26_final.stac-item
2023-04-14 11:03:37	ga_ls9c_ard_3-2-1_107080_2023-04-14_final.stac-item
2023-05-07 09:28:43	ga_ls9c_ard_3-2-1_092075_2023-05-06_final.stac-item
2023-05-24 10:09:48	ga_ls9c_ard_3-2-1_099070_2023-05-24_final.stac-item
2023-05-28 09:51:52	ga_ls9c_ard_3-2-1_095087_2023-05-28_final.stac-item
2023-06-11 09:56:57	ga_ls9c_ard_3-2-1_097069_2023-06-11_final.stac-item
2023-06-12 09:06:54	ga_ls9c_ard_3-2-1_088083_2023-06-11_final.stac-item
2023-07-15 11:25:17	ga_ls9c_ard_3-2-1_111073_2023-07-15_final.stac-item
2023-08-20 09:22:41	ga_ls9c_ard_3-2-1_091075_2023-08-19_final.stac-item
2023-08-24 10:35:43	ga_ls9c_ard_3-2-1_103072_2023-08-24_final.stac-item
2023-08-28 10:10:14	ga_ls9c_ard_3-2-1_099070_2023-08-28_final.stac-item
2023-08-29 09:21:49	ga_ls9c_ard_3-2-1_090088_2023-08-28_final.stac-item
2023-08-30 09:57:06	ga_ls9c_ard_3-2-1_097068_2023-08-30_final.stac-item
2023-09-16 09:07:37	ga_ls9c_ard_3-2-1_088083_2023-09-15_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-11-05 10:30:13	ga_ls9c_ard_3-2-1_102073_2023-11-05_final.stac-item
2023-11-10 10:49:59	ga_ls9c_ard_3-2-1_105076_2023-11-10_final.stac-item
2023-11-16 11:52:34	ga_ls9c_ard_3-2-1_115078_2023-11-16_final.stac-item
2023-11-26 09:12:49	ga_ls9c_ard_3-2-1_089080_2023-11-25_final.stac-item
2023-12-01 11:07:51	ga_ls9c_ard_3-2-1_108074_2023-12-01_final.stac-item
2023-12-02 10:11:01	ga_ls9c_ard_3-2-1_099071_2023-12-02_final.stac-item
2023-12-02 10:11:25	ga_ls9c_ard_3-2-1_099072_2023-12-02_final.stac-item
2023-12-04 11:42:19	ga_ls9c_ard_3-2-1_113083_2023-12-04_final.stac-item
2023-12-12 09:16:23	ga_ls9c_ard_3-2-1_089089_2023-12-11_final.stac-item
2023-12-18 11:52:44	ga_ls9c_ard_3-2-1_115078_2023-12-18_final.stac-item
2023-12-31 09:40:55	ga_ls9c_ard_3-2-1_094073_2023-12-31_final.stac-item
2024-01-12 10:05:13	ga_ls9c_ard_3-2-1_098072_2024-01-12_final.stac-item
2024-01-14 11:31:45	ga_ls9c_ard_3-2-1_112072_2024-01-14_final.stac-item
2024-01-29 09:16:23	ga_ls9c_ard_3-2-1_089089_2024-01-28_final.stac-item
2024-02-04 11:51:31	ga_ls9c_ard_3-2-1_115075_2024-02-04_final.stac-item
2024-02-10 11:14:26	ga_ls9c_ard_3-2-1_109075_2024-02-10_final.stac-item
2024-02-13 10:04:01	ga_ls9c_ard_3-2-1_098069_2024-02-13_final.stac-item
2024-03-02 09:52:45	ga_ls9c_ard_3-2-1_096072_2024-03-02_final.stac-item
2024-03-17 10:52:45	ga_ls9c_ard_3-2-1_105083_2024-03-17_final.stac-item
2024-04-23 09:33:54	ga_ls9c_ard_3-2-1_092088_2024-04-23_final.stac-item
2024-04-30 09:38:51	ga_ls9c_ard_3-2-1_093085_2024-04-30_final.stac-item
2024-04-30 11:13:20	ga_ls9c_ard_3-2-1_109074_2024-04-30_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