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

First 100 results (query limit)

Time (local)	Label
2021-11-11 10:19:51	ga_ls9c_ard_3-2-1_100078_2021-11-11_final.stac-item
2021-12-12 10:13:50	ga_ls9c_ard_3-2-1_099078_2021-12-12_final.stac-item
2021-12-12 10:14:14	ga_ls9c_ard_3-2-1_099079_2021-12-12_final.stac-item
2021-12-17 10:28:20	ga_ls9c_ard_3-2-1_102068_2021-12-17_final.stac-item
2021-12-19 10:19:58	ga_ls9c_ard_3-2-1_100078_2021-12-19_final.stac-item
2021-12-19 10:20:22	ga_ls9c_ard_3-2-1_100079_2021-12-19_final.stac-item
2021-12-28 10:14:12	ga_ls9c_ard_3-2-1_099079_2021-12-28_final.stac-item
2022-01-02 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-01-02_final.stac-item
2022-01-04 10:19:58	ga_ls9c_ard_3-2-1_100078_2022-01-04_final.stac-item
2022-01-18 10:28:19	ga_ls9c_ard_3-2-1_102068_2022-01-18_final.stac-item
2022-01-20 10:19:57	ga_ls9c_ard_3-2-1_100078_2022-01-20_final.stac-item
2022-02-03 10:28:20	ga_ls9c_ard_3-2-1_102068_2022-02-03_final.stac-item
2022-02-19 10:28:14	ga_ls9c_ard_3-2-1_102068_2022-02-19_final.stac-item
2022-03-07 10:28:06	ga_ls9c_ard_3-2-1_102068_2022-03-07_final.stac-item
2022-03-09 10:19:44	ga_ls9c_ard_3-2-1_100078_2022-03-09_final.stac-item
2022-03-23 10:28:03	ga_ls9c_ard_3-2-1_102068_2022-03-23_final.stac-item
2022-03-25 10:19:39	ga_ls9c_ard_3-2-1_100078_2022-03-25_final.stac-item
2022-04-03 10:13:52	ga_ls9c_ard_3-2-1_099079_2022-04-03_final.stac-item
2022-04-08 10:27:59	ga_ls9c_ard_3-2-1_102068_2022-04-08_final.stac-item
2022-04-10 10:19:36	ga_ls9c_ard_3-2-1_100078_2022-04-10_final.stac-item
2022-04-24 10:27:49	ga_ls9c_ard_3-2-1_102068_2022-04-24_final.stac-item
2022-05-10 10:27:44	ga_ls9c_ard_3-2-1_102068_2022-05-10_final.stac-item
2022-05-12 10:19:20	ga_ls9c_ard_3-2-1_100078_2022-05-12_final.stac-item
2022-05-21 10:13:02	ga_ls9c_ard_3-2-1_099078_2022-05-21_final.stac-item
2022-05-26 10:27:34	ga_ls9c_ard_3-2-1_102068_2022-05-26_final.stac-item
2022-05-28 10:19:12	ga_ls9c_ard_3-2-1_100078_2022-05-28_final.stac-item
2022-05-28 10:19:36	ga_ls9c_ard_3-2-1_100079_2022-05-28_final.stac-item
2022-06-13 10:19:41	ga_ls9c_ard_3-2-1_100079_2022-06-13_final.stac-item
2022-06-22 10:13:19	ga_ls9c_ard_3-2-1_099078_2022-06-22_final.stac-item
2022-06-22 10:13:43	ga_ls9c_ard_3-2-1_099079_2022-06-22_final.stac-item
2022-06-27 10:27:57	ga_ls9c_ard_3-2-1_102068_2022-06-27_final.stac-item
2022-07-13 10:27:53	ga_ls9c_ard_3-2-1_102068_2022-07-13_final.stac-item
2022-07-13 10:28:16	ga_ls9c_ard_3-2-1_102069_2022-07-13_final.stac-item
2022-07-15 10:19:54	ga_ls9c_ard_3-2-1_100079_2022-07-15_final.stac-item
2022-07-24 10:13:52	ga_ls9c_ard_3-2-1_099079_2022-07-24_final.stac-item
2022-08-14 10:28:16	ga_ls9c_ard_3-2-1_102068_2022-08-14_final.stac-item
2022-08-30 10:28:18	ga_ls9c_ard_3-2-1_102068_2022-08-30_final.stac-item
2022-09-15 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-09-15_final.stac-item
2022-10-01 10:28:26	ga_ls9c_ard_3-2-1_102068_2022-10-01_final.stac-item
2022-10-01 10:28:50	ga_ls9c_ard_3-2-1_102069_2022-10-01_final.stac-item
2022-10-12 10:14:44	ga_ls9c_ard_3-2-1_099080_2022-10-12_final.stac-item
2022-10-17 10:28:31	ga_ls9c_ard_3-2-1_102068_2022-10-17_final.stac-item
2022-10-28 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-10-28_final.stac-item
2022-11-02 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-11-02_final.stac-item
2022-11-02 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-11-02_final.stac-item
2022-11-18 10:28:33	ga_ls9c_ard_3-2-1_102068_2022-11-18_final.stac-item
2022-11-20 10:20:34	ga_ls9c_ard_3-2-1_100079_2022-11-20_final.stac-item
2022-12-04 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-04_final.stac-item
2022-12-04 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-12-04_final.stac-item
2022-12-20 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-20_final.stac-item
2022-12-22 10:20:30	ga_ls9c_ard_3-2-1_100079_2022-12-22_final.stac-item
2022-12-31 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-12-31_final.stac-item
2023-01-05 10:28:32	ga_ls9c_ard_3-2-1_102068_2023-01-05_final.stac-item
2023-01-21 10:28:21	ga_ls9c_ard_3-2-1_102068_2023-01-21_final.stac-item
2023-01-21 10:28:45	ga_ls9c_ard_3-2-1_102069_2023-01-21_final.stac-item
2023-01-23 10:20:26	ga_ls9c_ard_3-2-1_100079_2023-01-23_final.stac-item
2023-02-01 10:14:47	ga_ls9c_ard_3-2-1_099080_2023-02-01_final.stac-item
2023-02-06 10:28:34	ga_ls9c_ard_3-2-1_102068_2023-02-06_final.stac-item
2023-02-17 10:13:57	ga_ls9c_ard_3-2-1_099078_2023-02-17_final.stac-item
2023-02-22 10:28:47	ga_ls9c_ard_3-2-1_102069_2023-02-22_final.stac-item
2023-02-24 10:19:58	ga_ls9c_ard_3-2-1_100078_2023-02-24_final.stac-item
2023-03-05 10:14:32	ga_ls9c_ard_3-2-1_099080_2023-03-05_final.stac-item
2023-03-10 10:28:12	ga_ls9c_ard_3-2-1_102068_2023-03-10_final.stac-item
2023-03-10 10:28:36	ga_ls9c_ard_3-2-1_102069_2023-03-10_final.stac-item
2023-03-12 10:20:15	ga_ls9c_ard_3-2-1_100079_2023-03-12_final.stac-item
2023-03-21 10:14:02	ga_ls9c_ard_3-2-1_099079_2023-03-21_final.stac-item
2023-03-21 10:14:26	ga_ls9c_ard_3-2-1_099080_2023-03-21_final.stac-item
2023-03-26 10:28:06	ga_ls9c_ard_3-2-1_102068_2023-03-26_final.stac-item
2023-03-28 10:19:41	ga_ls9c_ard_3-2-1_100078_2023-03-28_final.stac-item
2023-04-06 10:13:28	ga_ls9c_ard_3-2-1_099078_2023-04-06_final.stac-item
2023-04-11 10:27:58	ga_ls9c_ard_3-2-1_102068_2023-04-11_final.stac-item
2023-04-11 10:28:22	ga_ls9c_ard_3-2-1_102069_2023-04-11_final.stac-item
2023-04-22 10:13:46	ga_ls9c_ard_3-2-1_099079_2023-04-22_final.stac-item
2023-04-27 10:27:52	ga_ls9c_ard_3-2-1_102068_2023-04-27_final.stac-item
2023-04-29 10:19:51	ga_ls9c_ard_3-2-1_100079_2023-04-29_final.stac-item
2023-05-08 10:13:34	ga_ls9c_ard_3-2-1_099079_2023-05-08_final.stac-item
2023-05-08 10:13:58	ga_ls9c_ard_3-2-1_099080_2023-05-08_final.stac-item
2023-05-13 10:27:42	ga_ls9c_ard_3-2-1_102068_2023-05-13_final.stac-item
2023-05-15 10:19:43	ga_ls9c_ard_3-2-1_100079_2023-05-15_final.stac-item
2023-05-29 10:27:33	ga_ls9c_ard_3-2-1_102068_2023-05-29_final.stac-item
2023-05-29 10:27:57	ga_ls9c_ard_3-2-1_102069_2023-05-29_final.stac-item
2023-06-14 10:27:24	ga_ls9c_ard_3-2-1_102068_2023-06-14_final.stac-item
2023-06-25 10:13:14	ga_ls9c_ard_3-2-1_099079_2023-06-25_final.stac-item
2023-06-30 10:27:31	ga_ls9c_ard_3-2-1_102068_2023-06-30_final.stac-item
2023-07-11 10:13:30	ga_ls9c_ard_3-2-1_099079_2023-07-11_final.stac-item
2023-07-18 10:18:54	ga_ls9c_ard_3-2-1_100077_2023-07-18_final.stac-item
2023-07-18 10:19:42	ga_ls9c_ard_3-2-1_100079_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
2023-08-12 10:13:17	ga_ls9c_ard_3-2-1_099078_2023-08-12_final.stac-item
2023-08-17 10:27:50	ga_ls9c_ard_3-2-1_102068_2023-08-17_final.stac-item
2023-08-19 10:19:29	ga_ls9c_ard_3-2-1_100078_2023-08-19_final.stac-item
2023-10-04 10:28:10	ga_ls9c_ard_3-2-1_102068_2023-10-04_final.stac-item
2023-10-22 10:19:33	ga_ls9c_ard_3-2-1_100077_2023-10-22_final.stac-item
2023-11-05 10:28:13	ga_ls9c_ard_3-2-1_102068_2023-11-05_final.stac-item
2023-12-07 10:28:18	ga_ls9c_ard_3-2-1_102068_2023-12-07_final.stac-item
2023-12-25 10:19:39	ga_ls9c_ard_3-2-1_100077_2023-12-25_final.stac-item
2024-01-08 10:28:19	ga_ls9c_ard_3-2-1_102068_2024-01-08_final.stac-item
2024-01-24 10:28:16	ga_ls9c_ard_3-2-1_102068_2024-01-24_final.stac-item
2024-02-11 10:19:36	ga_ls9c_ard_3-2-1_100077_2024-02-11_final.stac-item
2024-02-25 10:28:10	ga_ls9c_ard_3-2-1_102068_2024-02-25_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