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

65 results

Time (local)	Label
2021-11-12 10:55:49	ga_ls9c_ard_3-2-1_106068_2021-11-12_final.stac-item
2022-01-03 11:14:48	ga_ls9c_ard_3-2-1_109076_2022-01-03_final.stac-item
2022-01-05 09:22:45	ga_ls9c_ard_3-2-1_091074_2022-01-04_final.stac-item
2022-02-06 09:22:44	ga_ls9c_ard_3-2-1_091074_2022-02-05_final.stac-item
2022-02-14 10:09:20	ga_ls9c_ard_3-2-1_099067_2022-02-14_final.stac-item
2022-02-24 10:49:54	ga_ls9c_ard_3-2-1_105076_2022-02-24_final.stac-item
2022-03-10 09:22:31	ga_ls9c_ard_3-2-1_091074_2022-03-09_final.stac-item
2022-03-11 10:09:46	ga_ls9c_ard_3-2-1_098084_2022-03-11_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-04-29 10:48:45	ga_ls9c_ard_3-2-1_105074_2022-04-29_final.stac-item
2022-05-13 09:22:06	ga_ls9c_ard_3-2-1_091074_2022-05-12_final.stac-item
2022-05-22 10:55:29	ga_ls9c_ard_3-2-1_106076_2022-05-22_final.stac-item
2022-06-04 10:27:01	ga_ls9c_ard_3-2-1_101082_2022-06-04_final.stac-item
2022-06-19 11:17:36	ga_ls9c_ard_3-2-1_110069_2022-06-19_final.stac-item
2022-06-19 11:22:48	ga_ls9c_ard_3-2-1_110082_2022-06-19_final.stac-item
2022-06-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-06-23_final.stac-item
2022-07-15 10:21:29	ga_ls9c_ard_3-2-1_100083_2022-07-15_final.stac-item
2022-07-28 09:52:00	ga_ls9c_ard_3-2-1_095086_2022-07-28_final.stac-item
2022-08-22 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-08-22_final.stac-item
2022-08-25 10:09:46	ga_ls9c_ard_3-2-1_099068_2022-08-25_final.stac-item
2022-09-09 09:28:05	ga_ls9c_ard_3-2-1_092072_2022-09-08_final.stac-item
2022-10-16 11:24:56	ga_ls9c_ard_3-2-1_111070_2022-10-16_final.stac-item
2022-10-25 09:41:05	ga_ls9c_ard_3-2-1_094073_2022-10-25_final.stac-item
2022-11-09 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-11-09_final.stac-item
2022-11-30 09:22:18	ga_ls9c_ard_3-2-1_090088_2022-11-29_final.stac-item
2023-01-17 09:22:38	ga_ls9c_ard_3-2-1_090089_2023-01-16_final.stac-item
2023-01-22 09:39:32	ga_ls9c_ard_3-2-1_093085_2023-01-22_final.stac-item
2023-02-08 10:17:49	ga_ls9c_ard_3-2-1_100072_2023-02-08_final.stac-item
2023-02-19 09:57:09	ga_ls9c_ard_3-2-1_097067_2023-02-19_final.stac-item
2023-03-01 10:38:06	ga_ls9c_ard_3-2-1_103077_2023-03-01_final.stac-item
2023-03-29 09:22:26	ga_ls9c_ard_3-2-1_091074_2023-03-28_final.stac-item
2023-04-06 10:09:05	ga_ls9c_ard_3-2-1_099067_2023-04-06_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-06-17 11:04:40	ga_ls9c_ard_3-2-1_107084_2023-06-17_final.stac-item
2023-06-24 11:06:52	ga_ls9c_ard_3-2-1_108074_2023-06-24_final.stac-item
2023-07-11 10:08:43	ga_ls9c_ard_3-2-1_099067_2023-07-11_final.stac-item
2023-07-19 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-07-18_final.stac-item
2023-07-29 11:41:18	ga_ls9c_ard_3-2-1_113082_2023-07-29_final.stac-item
2023-08-05 10:02:42	ga_ls9c_ard_3-2-1_098067_2023-08-05_final.stac-item
2023-09-20 10:16:59	ga_ls9c_ard_3-2-1_100071_2023-09-20_final.stac-item
2023-10-05 09:34:33	ga_ls9c_ard_3-2-1_093073_2023-10-05_final.stac-item
2023-10-06 10:22:13	ga_ls9c_ard_3-2-1_100084_2023-10-06_final.stac-item
2023-10-09 09:12:15	ga_ls9c_ard_3-2-1_089079_2023-10-08_final.stac-item
2023-10-23 09:22:19	ga_ls9c_ard_3-2-1_091073_2023-10-22_final.stac-item
2023-10-28 09:40:02	ga_ls9c_ard_3-2-1_094071_2023-10-28_final.stac-item
2023-11-08 09:23:27	ga_ls9c_ard_3-2-1_091076_2023-11-07_final.stac-item
2023-11-11 09:58:21	ga_ls9c_ard_3-2-1_096086_2023-11-11_final.stac-item
2023-11-11 11:32:27	ga_ls9c_ard_3-2-1_112074_2023-11-11_final.stac-item
2023-11-29 11:24:12	ga_ls9c_ard_3-2-1_110084_2023-11-29_final.stac-item
2023-12-26 09:22:25	ga_ls9c_ard_3-2-1_091073_2023-12-25_final.stac-item
2023-12-31 11:19:48	ga_ls9c_ard_3-2-1_110073_2023-12-31_final.stac-item
2024-01-08 10:28:43	ga_ls9c_ard_3-2-1_102069_2024-01-08_final.stac-item
2024-01-11 09:22:45	ga_ls9c_ard_3-2-1_091074_2024-01-10_final.stac-item
2024-01-19 10:13:47	ga_ls9c_ard_3-2-1_099078_2024-01-19_final.stac-item
2024-02-14 09:11:59	ga_ls9c_ard_3-2-1_089078_2024-02-13_final.stac-item
2024-03-06 11:07:44	ga_ls9c_ard_3-2-1_108074_2024-03-06_final.stac-item
2024-03-08 10:56:10	ga_ls9c_ard_3-2-1_106076_2024-03-08_final.stac-item
2024-03-11 11:26:40	ga_ls9c_ard_3-2-1_111075_2024-03-11_final.stac-item
2024-03-13 09:34:12	ga_ls9c_ard_3-2-1_093072_2024-03-13_final.stac-item
2024-03-22 11:05:41	ga_ls9c_ard_3-2-1_108069_2024-03-22_final.stac-item
2024-03-27 09:52:02	ga_ls9c_ard_3-2-1_095086_2024-03-27_final.stac-item
2024-04-08 11:52:23	ga_ls9c_ard_3-2-1_115078_2024-04-08_final.stac-item
2024-04-19 11:32:04	ga_ls9c_ard_3-2-1_112074_2024-04-19_final.stac-item
2024-04-24 10:13:08	ga_ls9c_ard_3-2-1_099078_2024-04-24_final.stac-item
2024-04-30 09:37:39	ga_ls9c_ard_3-2-1_093082_2024-04-30_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