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
2021-11-20 11:22:41	ga_ls9c_ard_3-2-1_110076_2021-11-20_final.stac-item
2021-12-09 11:21:51	ga_ls9c_ard_3-2-1_110078_2021-12-09_final.stac-item
2021-12-16 11:25:10	ga_ls9c_ard_3-2-1_111071_2021-12-16_final.stac-item
2021-12-16 11:27:09	ga_ls9c_ard_3-2-1_111076_2021-12-16_final.stac-item
2022-01-01 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-01-01_final.stac-item
2022-01-01 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-01-01_final.stac-item
2022-01-17 11:25:08	ga_ls9c_ard_3-2-1_111071_2022-01-17_final.stac-item
2022-01-26 11:21:46	ga_ls9c_ard_3-2-1_110078_2022-01-26_final.stac-item
2022-02-02 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-02-02_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-02-18 11:25:03	ga_ls9c_ard_3-2-1_111071_2022-02-18_final.stac-item
2022-02-18 11:27:03	ga_ls9c_ard_3-2-1_111076_2022-02-18_final.stac-item
2022-02-27 11:21:33	ga_ls9c_ard_3-2-1_110078_2022-02-27_final.stac-item
2022-03-01 11:11:34	ga_ls9c_ard_3-2-1_108084_2022-03-01_final.stac-item
2022-03-06 11:24:55	ga_ls9c_ard_3-2-1_111071_2022-03-06_final.stac-item
2022-03-06 11:26:55	ga_ls9c_ard_3-2-1_111076_2022-03-06_final.stac-item
2022-03-22 11:24:52	ga_ls9c_ard_3-2-1_111071_2022-03-22_final.stac-item
2022-03-22 11:26:52	ga_ls9c_ard_3-2-1_111076_2022-03-22_final.stac-item
2022-04-07 11:24:49	ga_ls9c_ard_3-2-1_111071_2022-04-07_final.stac-item
2022-04-07 11:26:48	ga_ls9c_ard_3-2-1_111076_2022-04-07_final.stac-item
2022-04-16 11:21:20	ga_ls9c_ard_3-2-1_110078_2022-04-16_final.stac-item
2022-04-18 11:11:20	ga_ls9c_ard_3-2-1_108084_2022-04-18_final.stac-item
2022-04-23 11:24:38	ga_ls9c_ard_3-2-1_111071_2022-04-23_final.stac-item
2022-04-23 11:26:38	ga_ls9c_ard_3-2-1_111076_2022-04-23_final.stac-item
2022-05-02 11:20:26	ga_ls9c_ard_3-2-1_110076_2022-05-02_final.stac-item
2022-05-04 11:11:15	ga_ls9c_ard_3-2-1_108084_2022-05-04_final.stac-item
2022-05-09 11:24:34	ga_ls9c_ard_3-2-1_111071_2022-05-09_final.stac-item
2022-05-09 11:26:33	ga_ls9c_ard_3-2-1_111076_2022-05-09_final.stac-item
2022-05-18 11:20:15	ga_ls9c_ard_3-2-1_110076_2022-05-18_final.stac-item
2022-05-18 11:21:03	ga_ls9c_ard_3-2-1_110078_2022-05-18_final.stac-item
2022-05-25 11:24:24	ga_ls9c_ard_3-2-1_111071_2022-05-25_final.stac-item
2022-06-03 11:20:14	ga_ls9c_ard_3-2-1_110076_2022-06-03_final.stac-item
2022-06-03 11:21:02	ga_ls9c_ard_3-2-1_110078_2022-06-03_final.stac-item
2022-06-10 11:24:26	ga_ls9c_ard_3-2-1_111071_2022-06-10_final.stac-item
2022-06-10 11:26:26	ga_ls9c_ard_3-2-1_111076_2022-06-10_final.stac-item
2022-06-19 11:20:24	ga_ls9c_ard_3-2-1_110076_2022-06-19_final.stac-item
2022-06-19 11:21:12	ga_ls9c_ard_3-2-1_110078_2022-06-19_final.stac-item
2022-06-21 11:11:18	ga_ls9c_ard_3-2-1_108084_2022-06-21_final.stac-item
2022-06-26 11:24:46	ga_ls9c_ard_3-2-1_111071_2022-06-26_final.stac-item
2022-06-26 11:26:46	ga_ls9c_ard_3-2-1_111076_2022-06-26_final.stac-item
2022-07-05 11:20:34	ga_ls9c_ard_3-2-1_110076_2022-07-05_final.stac-item
2022-07-12 11:24:42	ga_ls9c_ard_3-2-1_111071_2022-07-12_final.stac-item
2022-07-21 11:20:37	ga_ls9c_ard_3-2-1_110076_2022-07-21_final.stac-item
2022-07-28 11:24:54	ga_ls9c_ard_3-2-1_111071_2022-07-28_final.stac-item
2022-07-28 11:26:54	ga_ls9c_ard_3-2-1_111076_2022-07-28_final.stac-item
2022-08-06 11:21:37	ga_ls9c_ard_3-2-1_110078_2022-08-06_final.stac-item
2022-08-13 11:25:04	ga_ls9c_ard_3-2-1_111071_2022-08-13_final.stac-item
2022-08-13 11:27:04	ga_ls9c_ard_3-2-1_111076_2022-08-13_final.stac-item
2022-08-29 11:25:07	ga_ls9c_ard_3-2-1_111071_2022-08-29_final.stac-item
2022-09-14 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-09-14_final.stac-item
2022-09-14 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-09-14_final.stac-item
2022-09-23 11:21:03	ga_ls9c_ard_3-2-1_110076_2022-09-23_final.stac-item
2022-09-23 11:21:51	ga_ls9c_ard_3-2-1_110078_2022-09-23_final.stac-item
2022-09-25 11:11:53	ga_ls9c_ard_3-2-1_108084_2022-09-25_final.stac-item
2022-09-30 11:25:15	ga_ls9c_ard_3-2-1_111071_2022-09-30_final.stac-item
2022-09-30 11:27:15	ga_ls9c_ard_3-2-1_111076_2022-09-30_final.stac-item
2022-10-16 11:25:20	ga_ls9c_ard_3-2-1_111071_2022-10-16_final.stac-item
2022-10-25 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-10-25_final.stac-item
2022-11-01 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-11-01_final.stac-item
2022-11-17 11:25:22	ga_ls9c_ard_3-2-1_111071_2022-11-17_final.stac-item
2022-11-28 11:11:58	ga_ls9c_ard_3-2-1_108084_2022-11-28_final.stac-item
2022-12-03 11:25:18	ga_ls9c_ard_3-2-1_111071_2022-12-03_final.stac-item
2022-12-14 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-14_final.stac-item
2022-12-19 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-12-19_final.stac-item
2023-01-04 11:25:21	ga_ls9c_ard_3-2-1_111071_2023-01-04_final.stac-item
2023-01-20 11:25:10	ga_ls9c_ard_3-2-1_111071_2023-01-20_final.stac-item
2023-01-20 11:27:10	ga_ls9c_ard_3-2-1_111076_2023-01-20_final.stac-item
2023-01-31 11:11:59	ga_ls9c_ard_3-2-1_108084_2023-01-31_final.stac-item
2023-02-05 11:25:23	ga_ls9c_ard_3-2-1_111071_2023-02-05_final.stac-item
2023-02-21 11:25:13	ga_ls9c_ard_3-2-1_111071_2023-02-21_final.stac-item
2023-03-09 11:25:02	ga_ls9c_ard_3-2-1_111071_2023-03-09_final.stac-item
2023-03-18 11:20:51	ga_ls9c_ard_3-2-1_110076_2023-03-18_final.stac-item
2023-03-18 11:21:38	ga_ls9c_ard_3-2-1_110078_2023-03-18_final.stac-item
2023-03-20 11:11:40	ga_ls9c_ard_3-2-1_108084_2023-03-20_final.stac-item
2023-03-25 11:24:57	ga_ls9c_ard_3-2-1_111071_2023-03-25_final.stac-item
2023-04-03 11:21:27	ga_ls9c_ard_3-2-1_110078_2023-04-03_final.stac-item
2023-04-10 11:24:48	ga_ls9c_ard_3-2-1_111071_2023-04-10_final.stac-item
2023-04-19 11:20:33	ga_ls9c_ard_3-2-1_110076_2023-04-19_final.stac-item
2023-04-19 11:20:57	ga_ls9c_ard_3-2-1_110077_2023-04-19_final.stac-item
2023-04-19 11:21:21	ga_ls9c_ard_3-2-1_110078_2023-04-19_final.stac-item
2023-04-26 11:24:41	ga_ls9c_ard_3-2-1_111071_2023-04-26_final.stac-item
2023-04-26 11:26:41	ga_ls9c_ard_3-2-1_111076_2023-04-26_final.stac-item
2023-05-05 11:20:21	ga_ls9c_ard_3-2-1_110076_2023-05-05_final.stac-item
2023-05-12 11:24:32	ga_ls9c_ard_3-2-1_111071_2023-05-12_final.stac-item
2023-05-21 11:20:14	ga_ls9c_ard_3-2-1_110076_2023-05-21_final.stac-item
2023-05-21 11:21:02	ga_ls9c_ard_3-2-1_110078_2023-05-21_final.stac-item
2023-05-28 11:24:22	ga_ls9c_ard_3-2-1_111071_2023-05-28_final.stac-item
2023-06-06 11:20:09	ga_ls9c_ard_3-2-1_110076_2023-06-06_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-06-22 11:20:02	ga_ls9c_ard_3-2-1_110076_2023-06-22_final.stac-item
2023-06-29 11:24:18	ga_ls9c_ard_3-2-1_111071_2023-06-29_final.stac-item
2023-06-29 11:26:18	ga_ls9c_ard_3-2-1_111076_2023-06-29_final.stac-item
2023-07-08 11:20:16	ga_ls9c_ard_3-2-1_110076_2023-07-08_final.stac-item
2023-07-31 11:26:34	ga_ls9c_ard_3-2-1_111076_2023-07-31_final.stac-item
2023-08-16 11:26:39	ga_ls9c_ard_3-2-1_111076_2023-08-16_final.stac-item
2023-09-01 11:24:50	ga_ls9c_ard_3-2-1_111071_2023-09-01_final.stac-item
2023-09-01 11:26:50	ga_ls9c_ard_3-2-1_111076_2023-09-01_final.stac-item
2023-10-19 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-10-19_final.stac-item
2023-12-22 11:25:14	ga_ls9c_ard_3-2-1_111071_2023-12-22_final.stac-item
2024-02-08 11:25:12	ga_ls9c_ard_3-2-1_111071_2024-02-08_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