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

49 results

Time (local)	Label
2021-12-04 09:22:53	ga_ls9c_ard_3-2-1_091074_2021-12-03_final.stac-item
2022-02-15 09:18:06	ga_ls9c_ard_3-2-1_090078_2022-02-14_final.stac-item
2022-03-27 11:44:34	ga_ls9c_ard_3-2-1_114074_2022-03-27_final.stac-item
2022-03-27 11:44:58	ga_ls9c_ard_3-2-1_114075_2022-03-27_final.stac-item
2022-04-15 10:35:42	ga_ls9c_ard_3-2-1_103072_2022-04-15_final.stac-item
2022-04-23 11:23:51	ga_ls9c_ard_3-2-1_111069_2022-04-23_final.stac-item
2022-05-02 11:20:26	ga_ls9c_ard_3-2-1_110076_2022-05-02_final.stac-item
2022-05-10 10:28:32	ga_ls9c_ard_3-2-1_102070_2022-05-10_final.stac-item
2022-05-31 10:46:08	ga_ls9c_ard_3-2-1_105068_2022-05-31_final.stac-item
2022-06-22 10:10:55	ga_ls9c_ard_3-2-1_099072_2022-06-22_final.stac-item
2022-07-09 09:16:32	ga_ls9c_ard_3-2-1_090075_2022-07-08_final.stac-item
2022-08-04 11:35:10	ga_ls9c_ard_3-2-1_112081_2022-08-04_final.stac-item
2022-08-18 10:09:57	ga_ls9c_ard_3-2-1_098084_2022-08-18_final.stac-item
2022-10-05 10:04:54	ga_ls9c_ard_3-2-1_098071_2022-10-05_final.stac-item
2022-10-16 09:52:50	ga_ls9c_ard_3-2-1_095087_2022-10-16_final.stac-item
2022-11-01 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-11-01_final.stac-item
2022-12-07 09:22:07	ga_ls9c_ard_3-2-1_091072_2022-12-06_final.stac-item
2022-12-08 11:45:04	ga_ls9c_ard_3-2-1_114074_2022-12-08_final.stac-item
2022-12-14 11:06:00	ga_ls9c_ard_3-2-1_108069_2022-12-14_final.stac-item
2023-01-02 10:01:13	ga_ls9c_ard_3-2-1_097077_2023-01-02_final.stac-item
2023-01-12 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-12_final.stac-item
2023-01-17 10:53:32	ga_ls9c_ard_3-2-1_106069_2023-01-17_final.stac-item
2023-01-24 09:22:26	ga_ls9c_ard_3-2-1_091073_2023-01-23_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 09:06:42	ga_ls9c_ard_3-2-1_088080_2023-02-19_final.stac-item
2023-04-03 11:21:04	ga_ls9c_ard_3-2-1_110077_2023-04-03_final.stac-item
2023-04-05 11:08:18	ga_ls9c_ard_3-2-1_108076_2023-04-05_final.stac-item
2023-04-10 11:26:00	ga_ls9c_ard_3-2-1_111074_2023-04-10_final.stac-item
2023-04-12 09:33:56	ga_ls9c_ard_3-2-1_093072_2023-04-12_final.stac-item
2023-05-21 11:22:38	ga_ls9c_ard_3-2-1_110082_2023-05-21_final.stac-item
2023-08-29 09:17:25	ga_ls9c_ard_3-2-1_090077_2023-08-28_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-22 10:19:33	ga_ls9c_ard_3-2-1_100077_2023-10-22_final.stac-item
2023-12-07 10:30:17	ga_ls9c_ard_3-2-1_102073_2023-12-07_final.stac-item
2023-12-11 10:08:24	ga_ls9c_ard_3-2-1_098080_2023-12-11_final.stac-item
2023-12-18 10:15:03	ga_ls9c_ard_3-2-1_099081_2023-12-18_final.stac-item
2024-01-09 11:14:47	ga_ls9c_ard_3-2-1_109076_2024-01-09_final.stac-item
2024-01-09 11:17:58	ga_ls9c_ard_3-2-1_109084_2024-01-09_final.stac-item
2024-02-10 09:34:21	ga_ls9c_ard_3-2-1_093072_2024-02-10_final.stac-item
2024-02-25 10:28:34	ga_ls9c_ard_3-2-1_102069_2024-02-25_final.stac-item
2024-03-15 09:22:38	ga_ls9c_ard_3-2-1_091074_2024-03-14_final.stac-item
2024-03-18 11:35:13	ga_ls9c_ard_3-2-1_112081_2024-03-18_final.stac-item
2024-03-20 11:22:27	ga_ls9c_ard_3-2-1_110080_2024-03-20_final.stac-item
2024-03-29 09:39:14	ga_ls9c_ard_3-2-1_093085_2024-03-29_final.stac-item
2024-04-04 10:34:15	ga_ls9c_ard_3-2-1_103068_2024-04-04_final.stac-item
2024-04-25 09:21:31	ga_ls9c_ard_3-2-1_090088_2024-04-24_final.stac-item
2024-04-25 10:55:36	ga_ls9c_ard_3-2-1_106076_2024-04-25_final.stac-item
2024-05-27 10:57:46	ga_ls9c_ard_3-2-1_106082_2024-05-27_nrt.stac-item
2024-05-29 09:06:05	ga_ls9c_ard_3-2-1_088081_2024-05-28_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