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

51 results

Time (local)	Label
2021-11-07 09:18:16	ga_ls9c_ard_3-2-1_090077_2021-11-06_final.stac-item
2021-11-12 10:56:13	ga_ls9c_ard_3-2-1_106069_2021-11-12_final.stac-item
2022-01-13 10:09:46	ga_ls9c_ard_3-2-1_099068_2022-01-13_final.stac-item
2022-02-01 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-01-31_final.stac-item
2022-02-07 10:09:59	ga_ls9c_ard_3-2-1_098084_2022-02-07_final.stac-item
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final.stac-item
2022-02-08 10:49:15	ga_ls9c_ard_3-2-1_105074_2022-02-08_final.stac-item
2022-02-09 11:31:43	ga_ls9c_ard_3-2-1_112072_2022-02-09_final.stac-item
2022-02-18 11:25:51	ga_ls9c_ard_3-2-1_111073_2022-02-18_final.stac-item
2022-03-11 10:09:46	ga_ls9c_ard_3-2-1_098084_2022-03-11_final.stac-item
2022-03-12 10:46:38	ga_ls9c_ard_3-2-1_105068_2022-03-12_final.stac-item
2022-04-21 09:57:44	ga_ls9c_ard_3-2-1_097070_2022-04-21_final.stac-item
2022-05-06 10:55:41	ga_ls9c_ard_3-2-1_106076_2022-05-06_final.stac-item
2022-06-01 09:56:54	ga_ls9c_ard_3-2-1_096084_2022-06-01_final.stac-item
2022-06-22 11:52:12	ga_ls9c_ard_3-2-1_115078_2022-06-22_final.stac-item
2022-07-23 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-07-22_final.stac-item
2022-10-02 09:34:48	ga_ls9c_ard_3-2-1_093073_2022-10-02_final.stac-item
2022-10-04 09:23:14	ga_ls9c_ard_3-2-1_091075_2022-10-03_final.stac-item
2022-11-07 09:12:09	ga_ls9c_ard_3-2-1_089078_2022-11-06_nrt.stac-item
2022-11-26 11:19:33	ga_ls9c_ard_3-2-1_110072_2022-11-26_final.stac-item
2022-12-09 09:11:46	ga_ls9c_ard_3-2-1_089077_2022-12-08_final.stac-item
2023-01-16 11:53:10	ga_ls9c_ard_3-2-1_115079_2023-01-16_final.stac-item
2023-03-12 10:19:51	ga_ls9c_ard_3-2-1_100078_2023-03-12_final.stac-item
2023-03-25 11:24:33	ga_ls9c_ard_3-2-1_111070_2023-03-25_final.stac-item
2023-03-29 09:22:50	ga_ls9c_ard_3-2-1_091075_2023-03-28_final.stac-item
2023-04-03 11:21:04	ga_ls9c_ard_3-2-1_110077_2023-04-03_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-07-05 09:11:38	ga_ls9c_ard_3-2-1_089079_2023-07-04_final.stac-item
2023-07-12 10:52:23	ga_ls9c_ard_3-2-1_106068_2023-07-12_final.stac-item
2023-07-19 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-07-18_final.stac-item
2023-07-31 11:23:47	ga_ls9c_ard_3-2-1_111069_2023-07-31_final.stac-item
2023-08-20 09:27:28	ga_ls9c_ard_3-2-1_091087_2023-08-19_final.stac-item
2023-08-22 10:49:14	ga_ls9c_ard_3-2-1_105075_2023-08-22_final.stac-item
2023-09-03 11:11:41	ga_ls9c_ard_3-2-1_109069_2023-09-03_final.stac-item
2023-09-08 11:31:30	ga_ls9c_ard_3-2-1_112072_2023-09-08_final.stac-item
2023-09-21 09:22:33	ga_ls9c_ard_3-2-1_091074_2023-09-20_final.stac-item
2023-09-25 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-25_final.stac-item
2023-10-01 09:57:37	ga_ls9c_ard_3-2-1_097069_2023-10-01_final.stac-item
2023-10-07 12:37:35	ga_ls9c_ard_3-2-1_123067_2023-10-07_final.stac-item
2023-10-28 09:40:02	ga_ls9c_ard_3-2-1_094071_2023-10-28_final.stac-item
2023-11-01 10:52:56	ga_ls9c_ard_3-2-1_106068_2023-11-01_final.stac-item
2023-11-29 09:40:56	ga_ls9c_ard_3-2-1_094073_2023-11-29_final.stac-item
2023-12-14 10:34:33	ga_ls9c_ard_3-2-1_103068_2023-12-14_final.stac-item
2024-01-03 11:53:04	ga_ls9c_ard_3-2-1_115079_2024-01-03_final.stac-item
2024-01-07 09:46:38	ga_ls9c_ard_3-2-1_095072_2024-01-07_final.stac-item
2024-01-17 10:27:45	ga_ls9c_ard_3-2-1_101082_2024-01-17_final.stac-item
2024-02-02 10:22:59	ga_ls9c_ard_3-2-1_101070_2024-02-02_final.stac-item
2024-02-03 11:05:51	ga_ls9c_ard_3-2-1_108069_2024-02-03_final.stac-item
2024-02-24 11:25:22	ga_ls9c_ard_3-2-1_111072_2024-02-24_final.stac-item
2024-03-18 09:52:20	ga_ls9c_ard_3-2-1_096071_2024-03-18_final.stac-item
2024-03-28 10:28:30	ga_ls9c_ard_3-2-1_102069_2024-03-28_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