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
2021-11-07 09:23:27	ga_ls9c_ard_3-2-1_090090_2021-11-06_final.stac-item
2021-12-08 10:36:13	ga_ls9c_ard_3-2-1_103072_2021-12-08_final.stac-item
2021-12-20 09:23:57	ga_ls9c_ard_3-2-1_091077_2021-12-19_final.stac-item
2022-01-12 11:07:47	ga_ls9c_ard_3-2-1_108074_2022-01-12_final.stac-item
2022-01-13 10:09:46	ga_ls9c_ard_3-2-1_099068_2022-01-13_final.stac-item
2022-02-22 09:23:48	ga_ls9c_ard_3-2-1_091077_2022-02-21_final.stac-item
2022-04-11 09:21:35	ga_ls9c_ard_3-2-1_091072_2022-04-10_final.stac-item
2022-05-27 09:39:08	ga_ls9c_ard_3-2-1_093086_2022-05-27_final.stac-item
2022-05-31 10:50:55	ga_ls9c_ard_3-2-1_105080_2022-05-31_final.stac-item
2022-07-08 10:10:34	ga_ls9c_ard_3-2-1_099071_2022-07-08_final.stac-item
2022-08-06 11:23:37	ga_ls9c_ard_3-2-1_110083_2022-08-06_final.stac-item
2022-09-02 09:23:07	ga_ls9c_ard_3-2-1_091075_2022-09-01_final.stac-item
2022-09-02 09:27:54	ga_ls9c_ard_3-2-1_091087_2022-09-01_final.stac-item
2022-09-14 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-09-14_final.stac-item
2022-09-20 10:50:08	ga_ls9c_ard_3-2-1_105076_2022-09-20_final.stac-item
2022-09-28 09:57:32	ga_ls9c_ard_3-2-1_097068_2022-09-28_final.stac-item
2022-09-30 09:46:22	ga_ls9c_ard_3-2-1_095071_2022-09-30_final.stac-item
2022-10-09 11:20:17	ga_ls9c_ard_3-2-1_110074_2022-10-09_final.stac-item
2022-10-24 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-10-24_final.stac-item
2022-12-13 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-12-13_final.stac-item
2023-01-09 10:10:11	ga_ls9c_ard_3-2-1_098084_2023-01-09_final.stac-item
2023-03-15 10:46:46	ga_ls9c_ard_3-2-1_105068_2023-03-15_final.stac-item
2023-04-07 10:58:43	ga_ls9c_ard_3-2-1_106083_2023-04-07_final.stac-item
2023-05-07 09:27:31	ga_ls9c_ard_3-2-1_092072_2023-05-06_final.stac-item
2023-06-09 10:14:55	ga_ls9c_ard_3-2-1_099083_2023-06-09_final.stac-item
2023-06-15 09:33:46	ga_ls9c_ard_3-2-1_093073_2023-06-15_final.stac-item
2023-06-17 11:03:05	ga_ls9c_ard_3-2-1_107080_2023-06-17_final.stac-item
2023-07-07 10:38:59	ga_ls9c_ard_3-2-1_103081_2023-07-07_final.stac-item
2023-07-19 09:22:29	ga_ls9c_ard_3-2-1_091075_2023-07-18_final.stac-item
2023-08-03 10:19:01	ga_ls9c_ard_3-2-1_100077_2023-08-03_final.stac-item
2023-09-25 10:35:53	ga_ls9c_ard_3-2-1_103072_2023-09-25_final.stac-item
2023-09-30 09:17:08	ga_ls9c_ard_3-2-1_090076_2023-09-29_final.stac-item
2023-10-11 10:36:01	ga_ls9c_ard_3-2-1_103072_2023-10-11_final.stac-item
2023-11-05 10:33:48	ga_ls9c_ard_3-2-1_102082_2023-11-05_final.stac-item
2023-12-01 09:28:10	ga_ls9c_ard_3-2-1_092072_2023-11-30_final.stac-item
2023-12-01 11:07:27	ga_ls9c_ard_3-2-1_108073_2023-12-01_final.stac-item
2023-12-03 09:16:59	ga_ls9c_ard_3-2-1_090075_2023-12-02_final.stac-item
2023-12-04 09:57:26	ga_ls9c_ard_3-2-1_097068_2023-12-04_final.stac-item
2023-12-18 10:09:04	ga_ls9c_ard_3-2-1_099066_2023-12-18_final.stac-item
2023-12-24 09:34:23	ga_ls9c_ard_3-2-1_093072_2023-12-24_final.stac-item
2024-01-11 09:22:21	ga_ls9c_ard_3-2-1_091073_2024-01-10_final.stac-item
2024-01-30 11:32:33	ga_ls9c_ard_3-2-1_112074_2024-01-30_final.stac-item
2024-02-01 11:20:12	ga_ls9c_ard_3-2-1_110074_2024-02-01_final.stac-item
2024-02-05 09:17:49	ga_ls9c_ard_3-2-1_090077_2024-02-04_final.stac-item
2024-04-13 10:33:35	ga_ls9c_ard_3-2-1_102082_2024-04-13_final.stac-item
2024-04-14 09:34:21	ga_ls9c_ard_3-2-1_093073_2024-04-14_final.stac-item
2024-04-19 09:57:10	ga_ls9c_ard_3-2-1_096084_2024-04-19_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years