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
2021-11-12 09:20:21	ga_ls9c_ard_3-2-1_091076_2021-11-11_final.stac-item
2021-11-13 11:40:34	ga_ls9c_ard_3-2-1_113080_2021-11-13_final.stac-item
2022-01-28 11:07:25	ga_ls9c_ard_3-2-1_108073_2022-01-28_final.stac-item
2022-02-13 11:07:22	ga_ls9c_ard_3-2-1_108073_2022-02-13_final.stac-item
2022-02-21 10:19:02	ga_ls9c_ard_3-2-1_100076_2022-02-21_final.stac-item
2022-03-07 10:33:41	ga_ls9c_ard_3-2-1_102082_2022-03-07_final.stac-item
2022-03-26 09:22:02	ga_ls9c_ard_3-2-1_091073_2022-03-25_final.stac-item
2022-04-02 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-04-01_final.stac-item
2022-04-03 10:15:51	ga_ls9c_ard_3-2-1_099084_2022-04-03_final.stac-item
2022-04-30 09:57:55	ga_ls9c_ard_3-2-1_096086_2022-04-30_final.stac-item
2022-05-23 09:56:17	ga_ls9c_ard_3-2-1_097067_2022-05-23_final.stac-item
2022-06-19 11:18:00	ga_ls9c_ard_3-2-1_110070_2022-06-19_final.stac-item
2022-07-03 09:57:38	ga_ls9c_ard_3-2-1_096085_2022-07-03_final.stac-item
2022-07-15 10:21:29	ga_ls9c_ard_3-2-1_100083_2022-07-15_final.stac-item
2022-07-24 11:51:58	ga_ls9c_ard_3-2-1_115077_2022-07-24_final.stac-item
2022-08-09 10:10:29	ga_ls9c_ard_3-2-1_099070_2022-08-09_final.stac-item
2022-08-09 10:11:16	ga_ls9c_ard_3-2-1_099072_2022-08-09_final.stac-item
2022-08-26 09:22:07	ga_ls9c_ard_3-2-1_090088_2022-08-25_final.stac-item
2022-11-07 09:11:45	ga_ls9c_ard_3-2-1_089077_2022-11-06_final.stac-item
2022-11-07 09:16:32	ga_ls9c_ard_3-2-1_089089_2022-11-06_final.stac-item
2022-12-21 09:35:15	ga_ls9c_ard_3-2-1_093074_2022-12-21_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-18 11:39:11	ga_ls9c_ard_3-2-1_113075_2023-01-18_final.stac-item
2023-01-20 11:23:59	ga_ls9c_ard_3-2-1_111068_2023-01-20_final.stac-item
2023-03-06 09:17:18	ga_ls9c_ard_3-2-1_090076_2023-03-05_final.stac-item
2023-03-25 11:24:57	ga_ls9c_ard_3-2-1_111071_2023-03-25_final.stac-item
2023-04-26 11:23:30	ga_ls9c_ard_3-2-1_111068_2023-04-26_final.stac-item
2023-05-17 10:03:20	ga_ls9c_ard_3-2-1_098069_2023-05-17_final.stac-item
2023-06-09 10:08:56	ga_ls9c_ard_3-2-1_099068_2023-06-09_final.stac-item
2023-06-09 11:50:37	ga_ls9c_ard_3-2-1_115075_2023-06-09_final.stac-item
2023-06-26 09:19:37	ga_ls9c_ard_3-2-1_090084_2023-06-25_final.stac-item
2023-07-12 09:16:17	ga_ls9c_ard_3-2-1_090075_2023-07-11_final.stac-item
2023-07-15 11:23:18	ga_ls9c_ard_3-2-1_111068_2023-07-15_final.stac-item
2023-07-31 09:45:41	ga_ls9c_ard_3-2-1_095071_2023-07-31_final.stac-item
2023-08-07 09:57:56	ga_ls9c_ard_3-2-1_096086_2023-08-07_final.stac-item
2023-09-07 10:49:49	ga_ls9c_ard_3-2-1_105076_2023-09-07_final.stac-item
2023-10-04 10:30:10	ga_ls9c_ard_3-2-1_102073_2023-10-04_final.stac-item
2023-10-07 09:22:36	ga_ls9c_ard_3-2-1_091074_2023-10-06_final.stac-item
2023-10-09 09:10:39	ga_ls9c_ard_3-2-1_089075_2023-10-08_final.stac-item
2023-10-26 09:58:24	ga_ls9c_ard_3-2-1_096086_2023-10-26_final.stac-item
2023-11-13 11:20:05	ga_ls9c_ard_3-2-1_110074_2023-11-13_final.stac-item
2023-12-03 09:16:59	ga_ls9c_ard_3-2-1_090075_2023-12-02_final.stac-item
2024-01-24 10:30:16	ga_ls9c_ard_3-2-1_102073_2024-01-24_final.stac-item
2024-01-24 10:30:16	ga_ls9c_ard_3-2-1_102073_2024-01-24_nrt.stac-item
2024-02-02 10:27:47	ga_ls9c_ard_3-2-1_101082_2024-02-02_final.stac-item
2024-02-04 11:51:07	ga_ls9c_ard_3-2-1_115074_2024-02-04_final.stac-item
2024-02-15 09:58:25	ga_ls9c_ard_3-2-1_096086_2024-02-15_final.stac-item
2024-02-18 10:25:40	ga_ls9c_ard_3-2-1_101077_2024-02-18_final.stac-item
2024-04-16 09:28:44	ga_ls9c_ard_3-2-1_091090_2024-04-15_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