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

58 results

Time (local)	Label
2021-10-31 11:10:00	ga_ls9c_ard_3-2-1_109069_2021-10-31_final.stac-item
2021-11-05 11:12:30	ga_ls9c_ard_3-2-1_109069_2021-11-05_final.stac-item
2021-12-18 11:12:00	ga_ls9c_ard_3-2-1_109069_2021-12-18_final.stac-item
2022-01-03 11:12:00	ga_ls9c_ard_3-2-1_109069_2022-01-03_final.stac-item
2022-01-19 11:11:59	ga_ls9c_ard_3-2-1_109069_2022-01-19_final.stac-item
2022-02-04 11:12:00	ga_ls9c_ard_3-2-1_109069_2022-02-04_final.stac-item
2022-02-20 11:11:53	ga_ls9c_ard_3-2-1_109069_2022-02-20_final.stac-item
2022-03-08 11:11:46	ga_ls9c_ard_3-2-1_109069_2022-03-08_final.stac-item
2022-03-24 11:11:42	ga_ls9c_ard_3-2-1_109069_2022-03-24_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-25 11:11:29	ga_ls9c_ard_3-2-1_109069_2022-04-25_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-05-27 11:11:14	ga_ls9c_ard_3-2-1_109069_2022-05-27_final.stac-item
2022-06-12 11:11:18	ga_ls9c_ard_3-2-1_109069_2022-06-12_final.stac-item
2022-06-28 11:11:37	ga_ls9c_ard_3-2-1_109069_2022-06-28_final.stac-item
2022-07-14 11:11:32	ga_ls9c_ard_3-2-1_109069_2022-07-14_final.stac-item
2022-07-30 11:11:46	ga_ls9c_ard_3-2-1_109069_2022-07-30_final.stac-item
2022-08-15 11:11:56	ga_ls9c_ard_3-2-1_109069_2022-08-15_final.stac-item
2022-08-31 11:11:58	ga_ls9c_ard_3-2-1_109069_2022-08-31_final.stac-item
2022-09-16 11:12:02	ga_ls9c_ard_3-2-1_109069_2022-09-16_final.stac-item
2022-10-02 11:12:05	ga_ls9c_ard_3-2-1_109069_2022-10-02_final.stac-item
2022-10-18 11:12:11	ga_ls9c_ard_3-2-1_109069_2022-10-18_final.stac-item
2022-11-03 11:12:08	ga_ls9c_ard_3-2-1_109069_2022-11-03_final.stac-item
2022-11-19 11:12:12	ga_ls9c_ard_3-2-1_109069_2022-11-19_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-21 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-21_final.stac-item
2023-01-06 11:12:11	ga_ls9c_ard_3-2-1_109069_2023-01-06_final.stac-item
2023-01-22 11:12:02	ga_ls9c_ard_3-2-1_109069_2023-01-22_final.stac-item
2023-02-07 11:12:14	ga_ls9c_ard_3-2-1_109069_2023-02-07_final.stac-item
2023-02-23 11:12:01	ga_ls9c_ard_3-2-1_109069_2023-02-23_final.stac-item
2023-03-11 11:11:52	ga_ls9c_ard_3-2-1_109069_2023-03-11_final.stac-item
2023-03-27 11:11:44	ga_ls9c_ard_3-2-1_109069_2023-03-27_final.stac-item
2023-04-12 11:11:37	ga_ls9c_ard_3-2-1_109069_2023-04-12_final.stac-item
2023-04-28 11:11:30	ga_ls9c_ard_3-2-1_109069_2023-04-28_final.stac-item
2023-05-14 11:11:21	ga_ls9c_ard_3-2-1_109069_2023-05-14_final.stac-item
2023-05-30 11:11:12	ga_ls9c_ard_3-2-1_109069_2023-05-30_final.stac-item
2023-06-15 11:11:03	ga_ls9c_ard_3-2-1_109069_2023-06-15_final.stac-item
2023-07-01 11:11:12	ga_ls9c_ard_3-2-1_109069_2023-07-01_final.stac-item
2023-07-17 11:11:20	ga_ls9c_ard_3-2-1_109069_2023-07-17_final.stac-item
2023-08-02 11:11:27	ga_ls9c_ard_3-2-1_109069_2023-08-02_final.stac-item
2023-08-18 11:11:30	ga_ls9c_ard_3-2-1_109069_2023-08-18_final.stac-item
2023-09-03 11:11:41	ga_ls9c_ard_3-2-1_109069_2023-09-03_final.stac-item
2023-09-19 11:11:49	ga_ls9c_ard_3-2-1_109069_2023-09-19_final.stac-item
2023-10-05 11:11:50	ga_ls9c_ard_3-2-1_109069_2023-10-05_final.stac-item
2023-10-21 11:11:59	ga_ls9c_ard_3-2-1_109069_2023-10-21_final.stac-item
2023-11-06 11:11:53	ga_ls9c_ard_3-2-1_109069_2023-11-06_final.stac-item
2023-11-22 11:12:00	ga_ls9c_ard_3-2-1_109069_2023-11-22_final.stac-item
2023-12-08 11:11:57	ga_ls9c_ard_3-2-1_109069_2023-12-08_final.stac-item
2023-12-24 11:12:05	ga_ls9c_ard_3-2-1_109069_2023-12-24_final.stac-item
2024-01-09 11:11:59	ga_ls9c_ard_3-2-1_109069_2024-01-09_final.stac-item
2024-01-25 11:11:57	ga_ls9c_ard_3-2-1_109069_2024-01-25_final.stac-item
2024-02-10 11:12:02	ga_ls9c_ard_3-2-1_109069_2024-02-10_final.stac-item
2024-02-26 11:11:51	ga_ls9c_ard_3-2-1_109069_2024-02-26_final.stac-item
2024-03-13 11:11:54	ga_ls9c_ard_3-2-1_109069_2024-03-13_final.stac-item
2024-03-29 11:11:44	ga_ls9c_ard_3-2-1_109069_2024-03-29_final.stac-item
2024-04-14 11:11:38	ga_ls9c_ard_3-2-1_109069_2024-04-14_final.stac-item
2024-04-30 11:11:21	ga_ls9c_ard_3-2-1_109069_2024-04-30_final.stac-item
2024-05-16 11:11:13	ga_ls9c_ard_3-2-1_109069_2024-05-16_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