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 11:23:52	ga_ls9c_ard_3-2-1_110079_2021-11-20_final.stac-item
2021-12-09 11:22:39	ga_ls9c_ard_3-2-1_110080_2021-12-09_final.stac-item
2021-12-16 11:26:22	ga_ls9c_ard_3-2-1_111074_2021-12-16_final.stac-item
2021-12-25 11:22:35	ga_ls9c_ard_3-2-1_110080_2021-12-25_final.stac-item
2022-01-01 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-01-01_final.stac-item
2022-01-10 11:22:09	ga_ls9c_ard_3-2-1_110079_2022-01-10_final.stac-item
2022-01-17 11:26:20	ga_ls9c_ard_3-2-1_111074_2022-01-17_final.stac-item
2022-01-26 11:22:10	ga_ls9c_ard_3-2-1_110079_2022-01-26_final.stac-item
2022-01-26 11:22:34	ga_ls9c_ard_3-2-1_110080_2022-01-26_final.stac-item
2022-02-11 11:22:08	ga_ls9c_ard_3-2-1_110079_2022-02-11_final.stac-item
2022-02-18 11:26:15	ga_ls9c_ard_3-2-1_111074_2022-02-18_final.stac-item
2022-02-27 11:21:57	ga_ls9c_ard_3-2-1_110079_2022-02-27_final.stac-item
2022-03-06 11:26:07	ga_ls9c_ard_3-2-1_111074_2022-03-06_final.stac-item
2022-03-22 11:26:04	ga_ls9c_ard_3-2-1_111074_2022-03-22_final.stac-item
2022-04-07 11:26:01	ga_ls9c_ard_3-2-1_111074_2022-04-07_final.stac-item
2022-04-23 11:25:50	ga_ls9c_ard_3-2-1_111074_2022-04-23_final.stac-item
2022-05-02 11:22:02	ga_ls9c_ard_3-2-1_110080_2022-05-02_final.stac-item
2022-05-09 11:25:45	ga_ls9c_ard_3-2-1_111074_2022-05-09_final.stac-item
2022-05-18 11:21:27	ga_ls9c_ard_3-2-1_110079_2022-05-18_final.stac-item
2022-05-25 11:25:36	ga_ls9c_ard_3-2-1_111074_2022-05-25_final.stac-item
2022-06-03 11:21:26	ga_ls9c_ard_3-2-1_110079_2022-06-03_final.stac-item
2022-06-03 11:21:50	ga_ls9c_ard_3-2-1_110080_2022-06-03_final.stac-item
2022-06-10 11:25:38	ga_ls9c_ard_3-2-1_111074_2022-06-10_final.stac-item
2022-06-19 11:22:00	ga_ls9c_ard_3-2-1_110080_2022-06-19_final.stac-item
2022-06-26 11:25:58	ga_ls9c_ard_3-2-1_111074_2022-06-26_final.stac-item
2022-07-05 11:21:46	ga_ls9c_ard_3-2-1_110079_2022-07-05_final.stac-item
2022-07-05 11:22:09	ga_ls9c_ard_3-2-1_110080_2022-07-05_final.stac-item
2022-07-12 11:25:54	ga_ls9c_ard_3-2-1_111074_2022-07-12_final.stac-item
2022-07-21 11:22:13	ga_ls9c_ard_3-2-1_110080_2022-07-21_final.stac-item
2022-07-28 11:26:06	ga_ls9c_ard_3-2-1_111074_2022-07-28_final.stac-item
2022-08-06 11:22:01	ga_ls9c_ard_3-2-1_110079_2022-08-06_final.stac-item
2022-08-06 11:22:25	ga_ls9c_ard_3-2-1_110080_2022-08-06_final.stac-item
2022-08-13 11:26:16	ga_ls9c_ard_3-2-1_111074_2022-08-13_final.stac-item
2022-08-22 11:22:08	ga_ls9c_ard_3-2-1_110079_2022-08-22_final.stac-item
2022-08-22 11:22:31	ga_ls9c_ard_3-2-1_110080_2022-08-22_final.stac-item
2022-08-29 11:26:19	ga_ls9c_ard_3-2-1_111074_2022-08-29_final.stac-item
2022-09-07 11:22:07	ga_ls9c_ard_3-2-1_110079_2022-09-07_final.stac-item
2022-09-14 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-09-14_final.stac-item
2022-09-23 11:22:15	ga_ls9c_ard_3-2-1_110079_2022-09-23_final.stac-item
2022-09-23 11:22:39	ga_ls9c_ard_3-2-1_110080_2022-09-23_final.stac-item
2022-09-30 11:26:27	ga_ls9c_ard_3-2-1_111074_2022-09-30_final.stac-item
2022-10-09 11:22:17	ga_ls9c_ard_3-2-1_110079_2022-10-09_final.stac-item
2022-10-09 11:22:41	ga_ls9c_ard_3-2-1_110080_2022-10-09_final.stac-item
2022-10-16 11:26:32	ga_ls9c_ard_3-2-1_111074_2022-10-16_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-11-10 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-10_final.stac-item
2022-11-17 11:26:33	ga_ls9c_ard_3-2-1_111074_2022-11-17_final.stac-item
2022-11-26 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-11-26_final.stac-item
2022-12-03 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-12-03_final.stac-item
2022-12-12 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-12-12_final.stac-item
2022-12-19 11:26:31	ga_ls9c_ard_3-2-1_111074_2022-12-19_final.stac-item
2022-12-28 11:22:20	ga_ls9c_ard_3-2-1_110079_2022-12-28_final.stac-item
2023-01-04 11:26:32	ga_ls9c_ard_3-2-1_111074_2023-01-04_final.stac-item
2023-01-20 11:26:22	ga_ls9c_ard_3-2-1_111074_2023-01-20_final.stac-item
2023-01-29 11:22:20	ga_ls9c_ard_3-2-1_110079_2023-01-29_final.stac-item
2023-02-05 11:26:35	ga_ls9c_ard_3-2-1_111074_2023-02-05_final.stac-item
2023-02-14 11:22:23	ga_ls9c_ard_3-2-1_110079_2023-02-14_final.stac-item
2023-02-14 11:22:46	ga_ls9c_ard_3-2-1_110080_2023-02-14_final.stac-item
2023-03-18 11:22:26	ga_ls9c_ard_3-2-1_110080_2023-03-18_final.stac-item
2023-04-03 11:22:15	ga_ls9c_ard_3-2-1_110080_2023-04-03_final.stac-item
2023-04-10 11:26:00	ga_ls9c_ard_3-2-1_111074_2023-04-10_final.stac-item
2023-04-26 11:25:53	ga_ls9c_ard_3-2-1_111074_2023-04-26_final.stac-item
2023-05-05 11:21:57	ga_ls9c_ard_3-2-1_110080_2023-05-05_final.stac-item
2023-05-12 11:25:43	ga_ls9c_ard_3-2-1_111074_2023-05-12_final.stac-item
2023-05-21 11:21:26	ga_ls9c_ard_3-2-1_110079_2023-05-21_final.stac-item
2023-05-21 11:21:50	ga_ls9c_ard_3-2-1_110080_2023-05-21_final.stac-item
2023-05-28 11:25:34	ga_ls9c_ard_3-2-1_111074_2023-05-28_final.stac-item
2023-06-06 11:21:20	ga_ls9c_ard_3-2-1_110079_2023-06-06_final.stac-item
2023-06-06 11:21:44	ga_ls9c_ard_3-2-1_110080_2023-06-06_final.stac-item
2023-06-13 11:25:26	ga_ls9c_ard_3-2-1_111074_2023-06-13_final.stac-item
2023-06-22 11:21:37	ga_ls9c_ard_3-2-1_110080_2023-06-22_final.stac-item
2023-06-29 11:25:30	ga_ls9c_ard_3-2-1_111074_2023-06-29_final.stac-item
2023-07-08 11:21:28	ga_ls9c_ard_3-2-1_110079_2023-07-08_final.stac-item
2023-07-08 11:21:52	ga_ls9c_ard_3-2-1_110080_2023-07-08_final.stac-item
2023-07-24 11:21:29	ga_ls9c_ard_3-2-1_110079_2023-07-24_final.stac-item
2023-08-09 11:21:40	ga_ls9c_ard_3-2-1_110079_2023-08-09_final.stac-item
2023-08-09 11:22:04	ga_ls9c_ard_3-2-1_110080_2023-08-09_final.stac-item
2023-08-25 11:22:11	ga_ls9c_ard_3-2-1_110080_2023-08-25_final.stac-item
2023-09-10 11:21:57	ga_ls9c_ard_3-2-1_110079_2023-09-10_final.stac-item
2023-09-10 11:22:21	ga_ls9c_ard_3-2-1_110080_2023-09-10_final.stac-item
2023-09-26 11:21:55	ga_ls9c_ard_3-2-1_110079_2023-09-26_final.stac-item
2023-09-26 11:22:19	ga_ls9c_ard_3-2-1_110080_2023-09-26_final.stac-item
2023-10-12 11:22:06	ga_ls9c_ard_3-2-1_110079_2023-10-12_final.stac-item
2023-10-12 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-12_final.stac-item
2023-10-28 11:22:06	ga_ls9c_ard_3-2-1_110079_2023-10-28_final.stac-item
2023-10-28 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-28_final.stac-item
2023-11-13 11:22:29	ga_ls9c_ard_3-2-1_110080_2023-11-13_final.stac-item
2023-11-29 11:22:37	ga_ls9c_ard_3-2-1_110080_2023-11-29_final.stac-item
2023-12-15 11:22:37	ga_ls9c_ard_3-2-1_110080_2023-12-15_final.stac-item
2023-12-31 11:22:36	ga_ls9c_ard_3-2-1_110080_2023-12-31_final.stac-item
2024-01-16 11:22:35	ga_ls9c_ard_3-2-1_110080_2024-01-16_final.stac-item
2024-02-01 11:22:36	ga_ls9c_ard_3-2-1_110080_2024-02-01_final.stac-item
2024-02-17 11:22:07	ga_ls9c_ard_3-2-1_110079_2024-02-17_final.stac-item
2024-02-17 11:22:30	ga_ls9c_ard_3-2-1_110080_2024-02-17_final.stac-item
2024-03-04 11:22:29	ga_ls9c_ard_3-2-1_110080_2024-03-04_final.stac-item
2024-03-20 11:22:03	ga_ls9c_ard_3-2-1_110079_2024-03-20_final.stac-item
2024-03-20 11:22:27	ga_ls9c_ard_3-2-1_110080_2024-03-20_final.stac-item
2024-04-05 11:21:54	ga_ls9c_ard_3-2-1_110079_2024-04-05_final.stac-item
2024-04-05 11:22:18	ga_ls9c_ard_3-2-1_110080_2024-04-05_final.stac-item
2024-04-21 11:22:02	ga_ls9c_ard_3-2-1_110080_2024-04-21_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