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

41 results

Time (local)	Label
2021-12-12 11:53:07	ga_ls9c_ard_3-2-1_115079_2021-12-12_final.stac-item
2021-12-16 09:46:17	ga_ls9c_ard_3-2-1_095071_2021-12-16_final.stac-item
2022-01-05 09:27:09	ga_ls9c_ard_3-2-1_091085_2022-01-04_final.stac-item
2022-01-13 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-01-13_final.stac-item
2022-01-19 11:12:47	ga_ls9c_ard_3-2-1_109071_2022-01-19_final.stac-item
2022-02-18 09:46:34	ga_ls9c_ard_3-2-1_095072_2022-02-18_final.stac-item
2022-04-20 09:22:28	ga_ls9c_ard_3-2-1_090090_2022-04-19_final.stac-item
2022-04-23 11:25:02	ga_ls9c_ard_3-2-1_111072_2022-04-23_final.stac-item
2022-04-29 10:46:22	ga_ls9c_ard_3-2-1_105068_2022-04-29_final.stac-item
2022-06-05 09:27:24	ga_ls9c_ard_3-2-1_092072_2022-06-04_final.stac-item
2022-06-23 09:16:32	ga_ls9c_ard_3-2-1_090075_2022-06-22_final.stac-item
2022-07-01 10:07:13	ga_ls9c_ard_3-2-1_098078_2022-07-01_final.stac-item
2022-08-01 09:22:57	ga_ls9c_ard_3-2-1_091075_2022-07-31_final.stac-item
2022-08-02 11:47:30	ga_ls9c_ard_3-2-1_114081_2022-08-02_final.stac-item
2022-08-08 09:34:23	ga_ls9c_ard_3-2-1_092088_2022-08-08_final.stac-item
2022-08-17 09:22:17	ga_ls9c_ard_3-2-1_091073_2022-08-16_final.stac-item
2022-09-16 11:12:02	ga_ls9c_ard_3-2-1_109069_2022-09-16_final.stac-item
2022-11-14 10:53:16	ga_ls9c_ard_3-2-1_106068_2022-11-14_final.stac-item
2022-12-09 09:13:46	ga_ls9c_ard_3-2-1_089082_2022-12-08_final.stac-item
2022-12-17 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-12-17_final.stac-item
2022-12-23 09:28:04	ga_ls9c_ard_3-2-1_091087_2022-12-22_final.stac-item
2022-12-26 09:58:35	ga_ls9c_ard_3-2-1_096086_2022-12-26_final.stac-item
2023-02-11 09:12:13	ga_ls9c_ard_3-2-1_089078_2023-02-10_final.stac-item
2023-02-18 12:31:41	ga_ls9c_ard_3-2-1_122067_2023-02-18_final.stac-item
2023-03-25 09:46:27	ga_ls9c_ard_3-2-1_095072_2023-03-25_final.stac-item
2023-04-14 09:22:44	ga_ls9c_ard_3-2-1_091075_2023-04-13_final.stac-item
2023-05-04 10:35:30	ga_ls9c_ard_3-2-1_103072_2023-05-04_final.stac-item
2023-06-09 10:09:20	ga_ls9c_ard_3-2-1_099069_2023-06-09_final.stac-item
2023-06-10 09:16:30	ga_ls9c_ard_3-2-1_090076_2023-06-09_final.stac-item
2023-06-24 09:33:34	ga_ls9c_ard_3-2-1_092088_2023-06-24_final.stac-item
2023-07-27 10:14:44	ga_ls9c_ard_3-2-1_099082_2023-07-27_final.stac-item
2023-08-29 09:16:37	ga_ls9c_ard_3-2-1_090075_2023-08-28_final.stac-item
2023-09-13 10:10:48	ga_ls9c_ard_3-2-1_099071_2023-09-13_final.stac-item
2023-10-28 09:40:26	ga_ls9c_ard_3-2-1_094072_2023-10-28_final.stac-item
2023-11-18 11:37:51	ga_ls9c_ard_3-2-1_113072_2023-11-18_final.stac-item
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2024-01-28 10:07:36	ga_ls9c_ard_3-2-1_098078_2024-01-28_final.stac-item
2024-02-26 11:14:14	ga_ls9c_ard_3-2-1_109075_2024-02-26_final.stac-item
2024-04-02 09:11:44	ga_ls9c_ard_3-2-1_089078_2024-04-01_final.stac-item
2024-04-09 10:57:33	ga_ls9c_ard_3-2-1_106080_2024-04-09_final.stac-item
2024-04-26 10:03:35	ga_ls9c_ard_3-2-1_097085_2024-04-26_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