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

64 results

Time (local)	Label
2021-11-11 10:19:27	ga_ls9c_ard_3-2-1_100077_2021-11-11_final.stac-item
2021-11-17 09:22:28	ga_ls9c_ard_3-2-1_091075_2021-11-16_final.stac-item
2021-12-09 11:18:40	ga_ls9c_ard_3-2-1_110070_2021-12-09_final.stac-item
2021-12-11 09:34:11	ga_ls9c_ard_3-2-1_092087_2021-12-11_final.stac-item
2021-12-11 09:34:35	ga_ls9c_ard_3-2-1_092088_2021-12-11_final.stac-item
2021-12-21 10:10:01	ga_ls9c_ard_3-2-1_098084_2021-12-21_final.stac-item
2022-01-10 11:18:33	ga_ls9c_ard_3-2-1_110070_2022-01-10_final.stac-item
2022-01-13 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-01-13_final.stac-item
2022-01-18 10:33:30	ga_ls9c_ard_3-2-1_102081_2022-01-18_final.stac-item
2022-01-25 10:34:55	ga_ls9c_ard_3-2-1_103069_2022-01-25_final.stac-item
2022-03-24 09:40:00	ga_ls9c_ard_3-2-1_093087_2022-03-24_final.stac-item
2022-03-28 10:49:45	ga_ls9c_ard_3-2-1_105076_2022-03-28_final.stac-item
2022-04-21 09:56:56	ga_ls9c_ard_3-2-1_097068_2022-04-21_final.stac-item
2022-04-24 10:27:49	ga_ls9c_ard_3-2-1_102068_2022-04-24_final.stac-item
2022-04-27 11:03:55	ga_ls9c_ard_3-2-1_107081_2022-04-27_final.stac-item
2022-05-12 10:16:32	ga_ls9c_ard_3-2-1_100071_2022-05-12_final.stac-item
2022-06-01 11:31:00	ga_ls9c_ard_3-2-1_112072_2022-06-01_final.stac-item
2022-06-08 09:56:18	ga_ls9c_ard_3-2-1_097067_2022-06-08_final.stac-item
2022-07-03 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-07-03_final.stac-item
2022-07-16 09:21:54	ga_ls9c_ard_3-2-1_091073_2022-07-15_final.stac-item
2022-09-02 09:22:19	ga_ls9c_ard_3-2-1_091073_2022-09-01_final.stac-item
2022-10-05 10:05:18	ga_ls9c_ard_3-2-1_098072_2022-10-05_final.stac-item
2022-10-06 09:10:52	ga_ls9c_ard_3-2-1_089075_2022-10-05_final.stac-item
2022-12-16 09:17:33	ga_ls9c_ard_3-2-1_090076_2022-12-15_final.stac-item
2023-01-06 09:35:42	ga_ls9c_ard_3-2-1_093075_2023-01-06_final.stac-item
2023-01-16 10:09:30	ga_ls9c_ard_3-2-1_099067_2023-01-16_final.stac-item
2023-02-07 09:40:56	ga_ls9c_ard_3-2-1_093088_2023-02-07_final.stac-item
2023-02-08 10:17:25	ga_ls9c_ard_3-2-1_100071_2023-02-08_final.stac-item
2023-02-27 09:11:35	ga_ls9c_ard_3-2-1_089077_2023-02-26_final.stac-item
2023-02-27 09:16:23	ga_ls9c_ard_3-2-1_089089_2023-02-26_final.stac-item
2023-03-07 09:57:21	ga_ls9c_ard_3-2-1_097068_2023-03-07_final.stac-item
2023-03-07 09:58:09	ga_ls9c_ard_3-2-1_097070_2023-03-07_final.stac-item
2023-03-08 09:04:30	ga_ls9c_ard_3-2-1_088075_2023-03-07_interim.stac-item
2023-03-23 09:57:15	ga_ls9c_ard_3-2-1_097068_2023-03-23_final.stac-item
2023-04-02 10:39:24	ga_ls9c_ard_3-2-1_103081_2023-04-02_final.stac-item
2023-04-14 11:03:13	ga_ls9c_ard_3-2-1_107079_2023-04-14_final.stac-item
2023-04-20 10:27:20	ga_ls9c_ard_3-2-1_101082_2023-04-20_final.stac-item
2023-05-05 09:39:52	ga_ls9c_ard_3-2-1_094072_2023-05-05_final.stac-item
2023-05-09 09:16:45	ga_ls9c_ard_3-2-1_090076_2023-05-08_final.stac-item
2023-05-12 11:23:20	ga_ls9c_ard_3-2-1_111068_2023-05-12_final.stac-item
2023-06-03 09:13:10	ga_ls9c_ard_3-2-1_089083_2023-06-02_final.stac-item
2023-07-03 11:01:40	ga_ls9c_ard_3-2-1_107076_2023-07-03_final.stac-item
2023-07-21 10:49:24	ga_ls9c_ard_3-2-1_105076_2023-07-21_final.stac-item
2023-07-26 11:07:32	ga_ls9c_ard_3-2-1_108075_2023-07-26_final.stac-item
2023-07-27 10:14:44	ga_ls9c_ard_3-2-1_099082_2023-07-27_final.stac-item
2023-09-04 10:16:52	ga_ls9c_ard_3-2-1_100071_2023-09-04_final.stac-item
2023-09-17 09:46:29	ga_ls9c_ard_3-2-1_095072_2023-09-17_final.stac-item
2023-10-09 10:49:32	ga_ls9c_ard_3-2-1_105075_2023-10-09_final.stac-item
2023-10-10 11:31:38	ga_ls9c_ard_3-2-1_112072_2023-10-10_final.stac-item
2023-10-21 09:33:54	ga_ls9c_ard_3-2-1_093071_2023-10-21_final.stac-item
2023-10-21 11:13:58	ga_ls9c_ard_3-2-1_109074_2023-10-21_final.stac-item
2023-12-12 09:11:59	ga_ls9c_ard_3-2-1_089078_2023-12-11_final.stac-item
2023-12-22 09:46:21	ga_ls9c_ard_3-2-1_095071_2023-12-22_final.stac-item
2023-12-31 09:40:31	ga_ls9c_ard_3-2-1_094072_2023-12-31_final.stac-item
2024-01-10 10:19:34	ga_ls9c_ard_3-2-1_100077_2024-01-10_final.stac-item
2024-01-21 09:57:01	ga_ls9c_ard_3-2-1_097067_2024-01-21_final.stac-item
2024-02-05 10:55:54	ga_ls9c_ard_3-2-1_106075_2024-02-05_final.stac-item
2024-02-17 11:18:31	ga_ls9c_ard_3-2-1_110070_2024-02-17_final.stac-item
2024-02-23 09:07:36	ga_ls9c_ard_3-2-1_088083_2024-02-22_final.stac-item
2024-03-06 09:28:03	ga_ls9c_ard_3-2-1_092072_2024-03-05_final.stac-item
2024-03-28 10:30:05	ga_ls9c_ard_3-2-1_102073_2024-03-28_final.stac-item
2024-03-31 09:21:42	ga_ls9c_ard_3-2-1_091072_2024-03-30_final.stac-item
2024-04-08 11:53:11	ga_ls9c_ard_3-2-1_115080_2024-04-08_final.stac-item
2024-05-11 10:55:35	ga_ls9c_ard_3-2-1_106076_2024-05-11_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