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

42 results

Time (local)	Label
2021-11-07 09:19:52	ga_ls9c_ard_3-2-1_090081_2021-11-06_final.stac-item
2021-12-23 11:31:45	ga_ls9c_ard_3-2-1_112072_2021-12-23_final.stac-item
2022-01-12 11:08:11	ga_ls9c_ard_3-2-1_108075_2022-01-12_final.stac-item
2022-01-15 11:38:41	ga_ls9c_ard_3-2-1_113074_2022-01-15_final.stac-item
2022-01-24 09:58:03	ga_ls9c_ard_3-2-1_096085_2022-01-24_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-03-21 09:06:19	ga_ls9c_ard_3-2-1_088080_2022-03-20_final.stac-item
2022-05-07 11:38:08	ga_ls9c_ard_3-2-1_113074_2022-05-07_final.stac-item
2022-05-12 10:16:32	ga_ls9c_ard_3-2-1_100071_2022-05-12_final.stac-item
2022-06-16 09:11:45	ga_ls9c_ard_3-2-1_089079_2022-06-15_final.stac-item
2022-09-25 09:34:12	ga_ls9c_ard_3-2-1_092087_2022-09-25_final.stac-item
2022-10-16 11:24:32	ga_ls9c_ard_3-2-1_111069_2022-10-16_final.stac-item
2022-11-06 11:47:51	ga_ls9c_ard_3-2-1_114081_2022-11-06_final.stac-item
2022-11-16 09:06:48	ga_ls9c_ard_3-2-1_088080_2022-11-15_final.stac-item
2022-12-14 09:34:42	ga_ls9c_ard_3-2-1_092088_2022-12-14_final.stac-item
2022-12-16 10:57:37	ga_ls9c_ard_3-2-1_106079_2022-12-16_final.stac-item
2023-01-15 09:34:14	ga_ls9c_ard_3-2-1_092087_2023-01-15_final.stac-item
2023-01-25 11:47:47	ga_ls9c_ard_3-2-1_114081_2023-01-25_final.stac-item
2023-02-03 09:59:15	ga_ls9c_ard_3-2-1_097072_2023-02-03_final.stac-item
2023-02-09 09:23:47	ga_ls9c_ard_3-2-1_091076_2023-02-08_final.stac-item
2023-02-21 11:24:26	ga_ls9c_ard_3-2-1_111069_2023-02-21_final.stac-item
2023-03-28 11:57:46	ga_ls9c_ard_3-2-1_116076_2023-03-28_final.stac-item
2023-04-15 10:03:59	ga_ls9c_ard_3-2-1_098070_2023-04-15_final.stac-item
2023-04-30 09:21:49	ga_ls9c_ard_3-2-1_091073_2023-04-29_final.stac-item
2023-05-02 09:10:13	ga_ls9c_ard_3-2-1_089075_2023-05-01_final.stac-item
2023-05-12 09:51:38	ga_ls9c_ard_3-2-1_095086_2023-05-12_final.stac-item
2023-06-27 09:57:19	ga_ls9c_ard_3-2-1_097070_2023-06-27_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-23 10:35:26	ga_ls9c_ard_3-2-1_103072_2023-07-23_final.stac-item
2023-08-08 10:35:36	ga_ls9c_ard_3-2-1_103072_2023-08-08_final.stac-item
2023-09-08 11:32:17	ga_ls9c_ard_3-2-1_112074_2023-09-08_final.stac-item
2023-09-15 11:38:31	ga_ls9c_ard_3-2-1_113074_2023-09-15_final.stac-item
2023-09-18 10:33:20	ga_ls9c_ard_3-2-1_102081_2023-09-18_final.stac-item
2023-10-23 09:22:19	ga_ls9c_ard_3-2-1_091073_2023-10-22_final.stac-item
2024-01-25 11:17:56	ga_ls9c_ard_3-2-1_109084_2024-01-25_final.stac-item
2024-01-25 11:17:56	ga_ls9c_ard_3-2-1_109084_2024-01-25_nrt.stac-item
2024-01-28 10:06:48	ga_ls9c_ard_3-2-1_098076_2024-01-28_final.stac-item
2024-02-12 09:23:34	ga_ls9c_ard_3-2-1_091076_2024-02-11_final.stac-item
2024-03-01 10:49:57	ga_ls9c_ard_3-2-1_105076_2024-03-01_final.stac-item
2024-04-10 09:59:31	ga_ls9c_ard_3-2-1_097074_2024-04-10_final.stac-item
2024-04-14 11:17:37	ga_ls9c_ard_3-2-1_109084_2024-04-14_final.stac-item
2024-04-22 10:26:46	ga_ls9c_ard_3-2-1_101081_2024-04-22_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years