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

47 results

Time (local)	Label
2021-12-24 10:36:08	ga_ls9c_ard_3-2-1_103072_2021-12-24_final.stac-item
2022-01-03 11:14:24	ga_ls9c_ard_3-2-1_109075_2022-01-03_final.stac-item
2022-01-12 09:28:06	ga_ls9c_ard_3-2-1_092072_2022-01-11_final.stac-item
2022-01-17 11:24:44	ga_ls9c_ard_3-2-1_111070_2022-01-17_final.stac-item
2022-01-30 10:53:52	ga_ls9c_ard_3-2-1_106070_2022-01-30_final.stac-item
2022-02-08 10:47:16	ga_ls9c_ard_3-2-1_105069_2022-02-08_final.stac-item
2022-03-19 10:55:35	ga_ls9c_ard_3-2-1_106075_2022-03-19_final.stac-item
2022-04-07 09:45:56	ga_ls9c_ard_3-2-1_095071_2022-04-07_final.stac-item
2022-05-13 09:24:06	ga_ls9c_ard_3-2-1_091079_2022-05-12_final.stac-item
2022-05-17 10:35:24	ga_ls9c_ard_3-2-1_103072_2022-05-17_final.stac-item
2022-05-18 09:39:22	ga_ls9c_ard_3-2-1_094071_2022-05-18_final.stac-item
2022-06-30 09:28:45	ga_ls9c_ard_3-2-1_091090_2022-06-29_final.stac-item
2022-07-10 09:57:00	ga_ls9c_ard_3-2-1_097068_2022-07-10_final.stac-item
2022-08-02 10:03:25	ga_ls9c_ard_3-2-1_098068_2022-08-02_final.stac-item
2022-09-25 09:29:01	ga_ls9c_ard_3-2-1_092074_2022-09-24_final.stac-item
2022-10-07 11:31:49	ga_ls9c_ard_3-2-1_112072_2022-10-07_final.stac-item
2022-11-12 09:33:31	ga_ls9c_ard_3-2-1_092085_2022-11-12_final.stac-item
2022-11-14 10:56:03	ga_ls9c_ard_3-2-1_106075_2022-11-14_final.stac-item
2022-11-19 09:34:07	ga_ls9c_ard_3-2-1_093071_2022-11-19_final.stac-item
2022-11-21 09:22:57	ga_ls9c_ard_3-2-1_091074_2022-11-20_final.stac-item
2022-11-23 09:16:34	ga_ls9c_ard_3-2-1_089089_2022-11-22_final.stac-item
2023-01-15 11:08:20	ga_ls9c_ard_3-2-1_108075_2023-01-15_final.stac-item
2023-01-16 10:11:06	ga_ls9c_ard_3-2-1_099071_2023-01-16_final.stac-item
2023-02-19 09:59:57	ga_ls9c_ard_3-2-1_097074_2023-02-19_final.stac-item
2023-03-14 10:05:06	ga_ls9c_ard_3-2-1_098072_2023-03-14_final.stac-item
2023-03-31 10:49:21	ga_ls9c_ard_3-2-1_105075_2023-03-31_final.stac-item
2023-03-31 10:49:45	ga_ls9c_ard_3-2-1_105076_2023-03-31_final.stac-item
2023-04-08 10:03:53	ga_ls9c_ard_3-2-1_097085_2023-04-08_final.stac-item
2023-04-10 09:45:55	ga_ls9c_ard_3-2-1_095071_2023-04-10_final.stac-item
2023-04-12 09:34:20	ga_ls9c_ard_3-2-1_093073_2023-04-12_final.stac-item
2023-06-17 09:21:24	ga_ls9c_ard_3-2-1_091073_2023-06-16_final.stac-item
2023-06-22 09:45:08	ga_ls9c_ard_3-2-1_094086_2023-06-22_final.stac-item
2023-07-18 10:18:54	ga_ls9c_ard_3-2-1_100077_2023-07-18_final.stac-item
2023-07-24 11:17:53	ga_ls9c_ard_3-2-1_110070_2023-07-24_final.stac-item
2023-07-28 10:55:13	ga_ls9c_ard_3-2-1_106075_2023-07-28_final.stac-item
2023-09-10 11:17:57	ga_ls9c_ard_3-2-1_110069_2023-09-10_final.stac-item
2023-09-16 09:07:37	ga_ls9c_ard_3-2-1_088083_2023-09-15_final.stac-item
2023-09-30 10:55:37	ga_ls9c_ard_3-2-1_106075_2023-09-30_final.stac-item
2023-10-12 11:20:06	ga_ls9c_ard_3-2-1_110074_2023-10-12_final.stac-item
2023-12-08 09:34:16	ga_ls9c_ard_3-2-1_093072_2023-12-08_final.stac-item
2024-01-11 09:22:21	ga_ls9c_ard_3-2-1_091073_2024-01-10_final.stac-item
2024-01-20 09:16:57	ga_ls9c_ard_3-2-1_090075_2024-01-19_final.stac-item
2024-02-09 10:29:34	ga_ls9c_ard_3-2-1_102071_2024-02-09_final.stac-item
2024-02-20 10:10:28	ga_ls9c_ard_3-2-1_099070_2024-02-20_final.stac-item
2024-02-22 09:57:15	ga_ls9c_ard_3-2-1_097068_2024-02-22_final.stac-item
2024-04-08 10:10:18	ga_ls9c_ard_3-2-1_099070_2024-04-08_final.stac-item
2024-05-10 10:09:56	ga_ls9c_ard_3-2-1_099070_2024-05-10_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