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
2021-12-10 10:25:02	ga_ls9c_ard_3-2-1_101075_2021-12-10_final.stac-item
2021-12-19 10:18:47	ga_ls9c_ard_3-2-1_100075_2021-12-19_final.stac-item
2021-12-24 10:37:20	ga_ls9c_ard_3-2-1_103075_2021-12-24_final.stac-item
2021-12-28 10:12:37	ga_ls9c_ard_3-2-1_099075_2021-12-28_final.stac-item
2022-01-04 10:18:47	ga_ls9c_ard_3-2-1_100075_2022-01-04_final.stac-item
2022-01-20 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-01-20_final.stac-item
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final.stac-item
2022-02-03 10:31:08	ga_ls9c_ard_3-2-1_102075_2022-02-03_final.stac-item
2022-02-05 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-02-05_final.stac-item
2022-02-10 10:37:17	ga_ls9c_ard_3-2-1_103075_2022-02-10_final.stac-item
2022-02-19 10:31:01	ga_ls9c_ard_3-2-1_102075_2022-02-19_final.stac-item
2022-03-07 10:30:53	ga_ls9c_ard_3-2-1_102075_2022-03-07_final.stac-item
2022-03-23 10:30:50	ga_ls9c_ard_3-2-1_102075_2022-03-23_final.stac-item
2022-03-25 10:18:28	ga_ls9c_ard_3-2-1_100075_2022-03-25_final.stac-item
2022-03-31 11:20:15	ga_ls9c_ard_3-2-1_110075_2022-03-31_final.stac-item
2022-04-02 11:07:53	ga_ls9c_ard_3-2-1_108075_2022-04-02_final.stac-item
2022-04-07 11:26:25	ga_ls9c_ard_3-2-1_111075_2022-04-07_final.stac-item
2022-04-08 10:30:47	ga_ls9c_ard_3-2-1_102075_2022-04-08_final.stac-item
2022-04-09 11:14:02	ga_ls9c_ard_3-2-1_109075_2022-04-09_final.stac-item
2022-04-10 10:18:24	ga_ls9c_ard_3-2-1_100075_2022-04-10_final.stac-item
2022-04-14 11:32:31	ga_ls9c_ard_3-2-1_112075_2022-04-14_final.stac-item
2022-04-15 10:36:53	ga_ls9c_ard_3-2-1_103075_2022-04-15_final.stac-item
2022-04-19 10:12:07	ga_ls9c_ard_3-2-1_099075_2022-04-19_final.stac-item
2022-04-24 10:30:37	ga_ls9c_ard_3-2-1_102075_2022-04-24_final.stac-item
2022-04-25 11:13:53	ga_ls9c_ard_3-2-1_109075_2022-04-25_final.stac-item
2022-04-26 10:18:15	ga_ls9c_ard_3-2-1_100075_2022-04-26_final.stac-item
2022-04-27 11:01:31	ga_ls9c_ard_3-2-1_107075_2022-04-27_final.stac-item
2022-04-30 11:32:25	ga_ls9c_ard_3-2-1_112075_2022-04-30_final.stac-item
2022-05-01 10:36:47	ga_ls9c_ard_3-2-1_103075_2022-05-01_final.stac-item
2022-05-03 10:24:24	ga_ls9c_ard_3-2-1_101075_2022-05-03_final.stac-item
2022-05-04 11:07:40	ga_ls9c_ard_3-2-1_108075_2022-05-04_final.stac-item
2022-05-09 11:26:09	ga_ls9c_ard_3-2-1_111075_2022-05-09_final.stac-item
2022-05-10 10:30:31	ga_ls9c_ard_3-2-1_102075_2022-05-10_final.stac-item
2022-05-15 10:49:00	ga_ls9c_ard_3-2-1_105075_2022-05-15_final.stac-item
2022-05-18 11:19:51	ga_ls9c_ard_3-2-1_110075_2022-05-18_final.stac-item
2022-05-20 11:07:27	ga_ls9c_ard_3-2-1_108075_2022-05-20_final.stac-item
2022-05-24 10:42:44	ga_ls9c_ard_3-2-1_104075_2022-05-24_final.stac-item
2022-05-28 10:18:01	ga_ls9c_ard_3-2-1_100075_2022-05-28_final.stac-item
2022-06-04 10:24:13	ga_ls9c_ard_3-2-1_101075_2022-06-04_final.stac-item
2022-06-13 10:18:05	ga_ls9c_ard_3-2-1_100075_2022-06-13_final.stac-item
2022-06-20 10:24:25	ga_ls9c_ard_3-2-1_101075_2022-06-20_final.stac-item
2022-07-06 10:24:32	ga_ls9c_ard_3-2-1_101075_2022-07-06_final.stac-item
2022-08-07 10:24:49	ga_ls9c_ard_3-2-1_101075_2022-08-07_final.stac-item
2022-08-25 10:12:33	ga_ls9c_ard_3-2-1_099075_2022-08-25_final.stac-item
2022-09-01 10:18:44	ga_ls9c_ard_3-2-1_100075_2022-09-01_final.stac-item
2022-09-15 10:31:09	ga_ls9c_ard_3-2-1_102075_2022-09-15_final.stac-item
2022-09-26 10:12:41	ga_ls9c_ard_3-2-1_099075_2022-09-26_final.stac-item
2022-10-01 10:31:13	ga_ls9c_ard_3-2-1_102075_2022-10-01_final.stac-item
2022-10-12 10:12:44	ga_ls9c_ard_3-2-1_099075_2022-10-12_final.stac-item
2022-10-17 10:31:18	ga_ls9c_ard_3-2-1_102075_2022-10-17_final.stac-item
2022-10-26 10:25:08	ga_ls9c_ard_3-2-1_101075_2022-10-26_final.stac-item
2022-10-28 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-10-28_final.stac-item
2022-11-02 10:31:17	ga_ls9c_ard_3-2-1_102075_2022-11-02_final.stac-item
2022-11-11 10:25:09	ga_ls9c_ard_3-2-1_101075_2022-11-11_final.stac-item
2022-11-13 10:12:47	ga_ls9c_ard_3-2-1_099075_2022-11-13_final.stac-item
2022-11-18 10:31:20	ga_ls9c_ard_3-2-1_102075_2022-11-18_final.stac-item
2022-11-27 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-11-27_final.stac-item
2022-12-04 10:31:17	ga_ls9c_ard_3-2-1_102075_2022-12-04_final.stac-item
2022-12-06 10:18:56	ga_ls9c_ard_3-2-1_100075_2022-12-06_final.stac-item
2022-12-06 10:18:56	ga_ls9c_ard_3-2-1_100075_2022-12-06_nrt.stac-item
2022-12-13 10:25:08	ga_ls9c_ard_3-2-1_101075_2022-12-13_final.stac-item
2022-12-15 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-12-15_final.stac-item
2022-12-20 10:31:17	ga_ls9c_ard_3-2-1_102075_2022-12-20_final.stac-item
2022-12-22 10:18:54	ga_ls9c_ard_3-2-1_100075_2022-12-22_final.stac-item
2022-12-27 10:37:28	ga_ls9c_ard_3-2-1_103075_2022-12-27_final.stac-item
2022-12-29 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-12-29_final.stac-item
2022-12-31 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-12-31_final.stac-item
2023-01-05 10:31:19	ga_ls9c_ard_3-2-1_102075_2023-01-05_final.stac-item
2023-01-12 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-12_final.stac-item
2023-01-14 10:25:05	ga_ls9c_ard_3-2-1_101075_2023-01-14_final.stac-item
2023-01-21 10:31:09	ga_ls9c_ard_3-2-1_102075_2023-01-21_final.stac-item
2023-01-23 10:18:50	ga_ls9c_ard_3-2-1_100075_2023-01-23_final.stac-item
2023-01-28 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-28_final.stac-item
2023-01-30 10:25:08	ga_ls9c_ard_3-2-1_101075_2023-01-30_final.stac-item
2023-02-15 10:25:09	ga_ls9c_ard_3-2-1_101075_2023-02-15_final.stac-item
2023-02-24 10:18:46	ga_ls9c_ard_3-2-1_100075_2023-02-24_final.stac-item
2023-03-12 10:18:39	ga_ls9c_ard_3-2-1_100075_2023-03-12_final.stac-item
2023-03-19 10:24:49	ga_ls9c_ard_3-2-1_101075_2023-03-19_final.stac-item
2023-03-21 10:12:26	ga_ls9c_ard_3-2-1_099075_2023-03-21_final.stac-item
2023-03-28 10:18:29	ga_ls9c_ard_3-2-1_100075_2023-03-28_final.stac-item
2023-04-11 10:30:46	ga_ls9c_ard_3-2-1_102075_2023-04-11_final.stac-item
2023-04-18 10:36:54	ga_ls9c_ard_3-2-1_103075_2023-04-18_final.stac-item
2023-04-20 10:24:32	ga_ls9c_ard_3-2-1_101075_2023-04-20_final.stac-item
2023-04-22 10:12:10	ga_ls9c_ard_3-2-1_099075_2023-04-22_final.stac-item
2023-04-27 10:30:39	ga_ls9c_ard_3-2-1_102075_2023-04-27_final.stac-item
2023-05-13 10:30:30	ga_ls9c_ard_3-2-1_102075_2023-05-13_final.stac-item
2023-05-29 10:30:20	ga_ls9c_ard_3-2-1_102075_2023-05-29_final.stac-item
2023-06-07 10:24:07	ga_ls9c_ard_3-2-1_101075_2023-06-07_final.stac-item
2023-06-09 10:11:44	ga_ls9c_ard_3-2-1_099075_2023-06-09_final.stac-item
2023-07-09 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-09_final.stac-item
2024-03-21 10:24:49	ga_ls9c_ard_3-2-1_101075_2024-03-21_final.stac-item
2024-03-23 10:12:27	ga_ls9c_ard_3-2-1_099075_2024-03-23_final.stac-item
2024-03-30 10:18:31	ga_ls9c_ard_3-2-1_100075_2024-03-30_final.stac-item
2024-04-06 10:24:40	ga_ls9c_ard_3-2-1_101075_2024-04-06_final.stac-item
2024-04-08 10:12:18	ga_ls9c_ard_3-2-1_099075_2024-04-08_final.stac-item
2024-04-15 10:18:23	ga_ls9c_ard_3-2-1_100075_2024-04-15_final.stac-item
2024-04-22 10:24:22	ga_ls9c_ard_3-2-1_101075_2024-04-22_final.stac-item
2024-05-01 10:18:07	ga_ls9c_ard_3-2-1_100075_2024-05-01_final.stac-item
2024-05-08 10:24:17	ga_ls9c_ard_3-2-1_101075_2024-05-08_final.stac-item
2024-05-10 10:11:55	ga_ls9c_ard_3-2-1_099075_2024-05-10_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