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
2021-12-14 10:03:51	ga_ls9c_ard_3-2-1_097084_2021-12-14_final.stac-item
2021-12-27 09:32:57	ga_ls9c_ard_3-2-1_092084_2021-12-27_final.stac-item
2022-01-28 09:29:44	ga_ls9c_ard_3-2-1_092076_2022-01-27_final.stac-item
2022-01-29 11:51:53	ga_ls9c_ard_3-2-1_115076_2022-01-29_final.stac-item
2022-02-18 09:50:58	ga_ls9c_ard_3-2-1_095083_2022-02-18_final.stac-item
2022-03-10 09:22:07	ga_ls9c_ard_3-2-1_091073_2022-03-09_final.stac-item
2022-03-26 09:28:01	ga_ls9c_ard_3-2-1_091088_2022-03-25_final.stac-item
2022-06-02 10:34:35	ga_ls9c_ard_3-2-1_103070_2022-06-02_final.stac-item
2022-06-03 09:40:09	ga_ls9c_ard_3-2-1_094073_2022-06-03_final.stac-item
2022-07-03 11:31:20	ga_ls9c_ard_3-2-1_112072_2022-07-03_final.stac-item
2022-07-30 11:16:33	ga_ls9c_ard_3-2-1_109081_2022-07-30_final.stac-item
2022-08-10 10:53:45	ga_ls9c_ard_3-2-1_106070_2022-08-10_final.stac-item
2022-08-17 11:05:34	ga_ls9c_ard_3-2-1_107084_2022-08-17_final.stac-item
2022-08-22 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-08-22_final.stac-item
2022-08-25 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-08-25_final.stac-item
2022-08-27 10:03:23	ga_ls9c_ard_3-2-1_097083_2022-08-27_final.stac-item
2022-08-31 09:40:40	ga_ls9c_ard_3-2-1_093088_2022-08-31_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-09-30 11:30:26	ga_ls9c_ard_3-2-1_111084_2022-09-30_final.stac-item
2022-10-08 10:34:37	ga_ls9c_ard_3-2-1_103068_2022-10-08_final.stac-item
2022-10-08 10:35:01	ga_ls9c_ard_3-2-1_103069_2022-10-08_final.stac-item
2022-10-25 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-10-25_final.stac-item
2022-11-23 09:14:34	ga_ls9c_ard_3-2-1_089084_2022-11-22_final.stac-item
2022-12-18 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-12-17_final.stac-item
2022-12-22 10:22:06	ga_ls9c_ard_3-2-1_100083_2022-12-22_final.stac-item
2023-01-01 09:20:44	ga_ls9c_ard_3-2-1_090084_2022-12-31_final.stac-item
2023-01-09 10:09:47	ga_ls9c_ard_3-2-1_098083_2023-01-09_final.stac-item
2023-01-25 10:05:43	ga_ls9c_ard_3-2-1_098073_2023-01-25_final.stac-item
2023-02-01 11:51:40	ga_ls9c_ard_3-2-1_115075_2023-02-01_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-16 11:07:35	ga_ls9c_ard_3-2-1_108073_2023-02-16_final.stac-item
2023-02-19 11:42:25	ga_ls9c_ard_3-2-1_113083_2023-02-19_final.stac-item
2023-03-09 11:25:02	ga_ls9c_ard_3-2-1_111071_2023-03-09_final.stac-item
2023-04-01 09:51:45	ga_ls9c_ard_3-2-1_096070_2023-04-01_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-05-09 10:58:02	ga_ls9c_ard_3-2-1_106082_2023-05-09_final.stac-item
2023-05-16 09:26:28	ga_ls9c_ard_3-2-1_091085_2023-05-15_final.stac-item
2023-05-16 11:00:58	ga_ls9c_ard_3-2-1_107074_2023-05-16_final.stac-item
2023-05-16 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-05-16_final.stac-item
2023-05-18 09:13:41	ga_ls9c_ard_3-2-1_089084_2023-05-17_final.stac-item
2023-05-26 09:57:26	ga_ls9c_ard_3-2-1_097070_2023-05-26_final.stac-item
2023-05-26 10:03:02	ga_ls9c_ard_3-2-1_097084_2023-05-26_final.stac-item
2023-06-06 11:21:20	ga_ls9c_ard_3-2-1_110079_2023-06-06_final.stac-item
2023-06-18 10:04:16	ga_ls9c_ard_3-2-1_098072_2023-06-18_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-07-14 10:40:02	ga_ls9c_ard_3-2-1_104068_2023-07-14_final.stac-item
2023-07-26 09:33:27	ga_ls9c_ard_3-2-1_092087_2023-07-26_final.stac-item
2023-07-31 11:29:22	ga_ls9c_ard_3-2-1_111083_2023-07-31_final.stac-item
2023-08-13 10:54:57	ga_ls9c_ard_3-2-1_106074_2023-08-13_final.stac-item
2023-09-21 09:22:09	ga_ls9c_ard_3-2-1_091073_2023-09-20_final.stac-item
2023-10-17 10:01:24	ga_ls9c_ard_3-2-1_097078_2023-10-17_final.stac-item
2023-12-10 11:04:00	ga_ls9c_ard_3-2-1_107080_2023-12-10_final.stac-item
2023-12-17 09:32:59	ga_ls9c_ard_3-2-1_092084_2023-12-17_final.stac-item
2024-02-03 11:07:27	ga_ls9c_ard_3-2-1_108073_2024-02-03_final.stac-item
2024-03-04 11:18:53	ga_ls9c_ard_3-2-1_110071_2024-03-04_final.stac-item
2024-03-22 11:11:40	ga_ls9c_ard_3-2-1_108084_2024-03-22_final.stac-item
2024-03-29 11:13:20	ga_ls9c_ard_3-2-1_109073_2024-03-29_final.stac-item
2024-04-16 11:02:02	ga_ls9c_ard_3-2-1_107076_2024-04-16_final.stac-item
2024-05-10 10:15:31	ga_ls9c_ard_3-2-1_099084_2024-05-10_final.stac-item
2024-05-10 11:51:36	ga_ls9c_ard_3-2-1_115077_2024-05-10_final.stac-item
2024-05-13 09:07:06	ga_ls9c_ard_3-2-1_088083_2024-05-12_final.stac-item
2024-05-15 10:32:46	ga_ls9c_ard_3-2-1_102081_2024-05-15_final.stac-item
2024-06-01 09:37:48	ga_ls9c_ard_3-2-1_093083_2024-06-01_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