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
2021-11-16 10:24:18	ga_ls9c_ard_3-2-1_100083_2021-11-16_final.stac-item
2021-11-24 10:41:59	ga_ls9c_ard_3-2-1_104068_2021-11-24_final.stac-item
2021-12-17 10:33:07	ga_ls9c_ard_3-2-1_102080_2021-12-17_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2022-01-02 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-01-02_final.stac-item
2022-01-02 10:33:08	ga_ls9c_ard_3-2-1_102080_2022-01-02_final.stac-item
2022-01-11 10:26:55	ga_ls9c_ard_3-2-1_101080_2022-01-11_final.stac-item
2022-01-18 10:32:43	ga_ls9c_ard_3-2-1_102079_2022-01-18_final.stac-item
2022-01-18 10:33:07	ga_ls9c_ard_3-2-1_102080_2022-01-18_final.stac-item
2022-01-27 10:26:57	ga_ls9c_ard_3-2-1_101080_2022-01-27_final.stac-item
2022-02-03 10:33:08	ga_ls9c_ard_3-2-1_102080_2022-02-03_final.stac-item
2022-02-12 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-02-12_final.stac-item
2022-02-19 10:33:01	ga_ls9c_ard_3-2-1_102080_2022-02-19_final.stac-item
2022-02-28 10:26:43	ga_ls9c_ard_3-2-1_101080_2022-02-28_final.stac-item
2022-03-23 10:32:26	ga_ls9c_ard_3-2-1_102079_2022-03-23_final.stac-item
2022-03-23 10:32:50	ga_ls9c_ard_3-2-1_102080_2022-03-23_final.stac-item
2022-04-08 10:32:46	ga_ls9c_ard_3-2-1_102080_2022-04-08_final.stac-item
2022-05-03 10:26:24	ga_ls9c_ard_3-2-1_101080_2022-05-03_final.stac-item
2022-05-10 10:32:07	ga_ls9c_ard_3-2-1_102079_2022-05-10_final.stac-item
2022-05-10 10:32:31	ga_ls9c_ard_3-2-1_102080_2022-05-10_final.stac-item
2022-05-26 10:31:58	ga_ls9c_ard_3-2-1_102079_2022-05-26_final.stac-item
2022-06-11 10:32:25	ga_ls9c_ard_3-2-1_102080_2022-06-11_final.stac-item
2022-06-16 10:45:51	ga_ls9c_ard_3-2-1_105067_2022-06-16_final.stac-item
2022-06-20 10:26:24	ga_ls9c_ard_3-2-1_101080_2022-06-20_final.stac-item
2022-06-25 10:40:19	ga_ls9c_ard_3-2-1_104068_2022-06-25_final.stac-item
2022-06-27 10:32:44	ga_ls9c_ard_3-2-1_102080_2022-06-27_final.stac-item
2022-07-02 10:46:05	ga_ls9c_ard_3-2-1_105067_2022-07-02_final.stac-item
2022-07-13 10:32:40	ga_ls9c_ard_3-2-1_102080_2022-07-13_final.stac-item
2022-07-29 10:32:53	ga_ls9c_ard_3-2-1_102080_2022-07-29_final.stac-item
2022-08-03 10:46:18	ga_ls9c_ard_3-2-1_105067_2022-08-03_final.stac-item
2022-08-12 10:40:36	ga_ls9c_ard_3-2-1_104068_2022-08-12_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-08-23 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-08-23_final.stac-item
2022-09-04 10:46:27	ga_ls9c_ard_3-2-1_105067_2022-09-04_final.stac-item
2022-09-15 10:33:09	ga_ls9c_ard_3-2-1_102080_2022-09-15_final.stac-item
2022-09-20 10:46:32	ga_ls9c_ard_3-2-1_105067_2022-09-20_final.stac-item
2022-09-24 10:27:02	ga_ls9c_ard_3-2-1_101080_2022-09-24_final.stac-item
2022-10-01 10:33:13	ga_ls9c_ard_3-2-1_102080_2022-10-01_final.stac-item
2022-10-10 10:27:04	ga_ls9c_ard_3-2-1_101080_2022-10-10_final.stac-item
2022-10-17 10:33:18	ga_ls9c_ard_3-2-1_102080_2022-10-17_final.stac-item
2022-10-22 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-10-22_final.stac-item
2022-10-26 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-10-26_final.stac-item
2022-11-02 10:33:16	ga_ls9c_ard_3-2-1_102080_2022-11-02_final.stac-item
2022-11-07 10:46:39	ga_ls9c_ard_3-2-1_105067_2022-11-07_final.stac-item
2022-11-11 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-11-11_final.stac-item
2022-11-18 10:33:20	ga_ls9c_ard_3-2-1_102080_2022-11-18_final.stac-item
2022-11-27 10:27:07	ga_ls9c_ard_3-2-1_101080_2022-11-27_final.stac-item
2022-12-04 10:32:53	ga_ls9c_ard_3-2-1_102079_2022-12-04_final.stac-item
2022-12-04 10:33:17	ga_ls9c_ard_3-2-1_102080_2022-12-04_final.stac-item
2023-01-05 10:33:19	ga_ls9c_ard_3-2-1_102080_2023-01-05_final.stac-item
2023-01-10 10:46:39	ga_ls9c_ard_3-2-1_105067_2023-01-10_final.stac-item
2023-01-14 10:27:05	ga_ls9c_ard_3-2-1_101080_2023-01-14_final.stac-item
2023-01-21 10:32:45	ga_ls9c_ard_3-2-1_102079_2023-01-21_final.stac-item
2023-01-21 10:33:09	ga_ls9c_ard_3-2-1_102080_2023-01-21_final.stac-item
2023-01-30 10:27:07	ga_ls9c_ard_3-2-1_101080_2023-01-30_final.stac-item
2023-02-04 10:40:55	ga_ls9c_ard_3-2-1_104068_2023-02-04_final.stac-item
2023-02-06 10:32:58	ga_ls9c_ard_3-2-1_102079_2023-02-06_final.stac-item
2023-02-06 10:33:22	ga_ls9c_ard_3-2-1_102080_2023-02-06_final.stac-item
2023-02-11 10:46:43	ga_ls9c_ard_3-2-1_105067_2023-02-11_final.stac-item
2023-02-20 10:40:47	ga_ls9c_ard_3-2-1_104068_2023-02-20_final.stac-item
2023-02-22 10:33:10	ga_ls9c_ard_3-2-1_102080_2023-02-22_final.stac-item
2023-02-27 10:46:29	ga_ls9c_ard_3-2-1_105067_2023-02-27_final.stac-item
2023-03-03 10:28:07	ga_ls9c_ard_3-2-1_101083_2023-03-03_final.stac-item
2023-03-10 10:32:35	ga_ls9c_ard_3-2-1_102079_2023-03-10_final.stac-item
2023-03-26 10:32:29	ga_ls9c_ard_3-2-1_102079_2023-03-26_final.stac-item
2023-03-26 10:32:53	ga_ls9c_ard_3-2-1_102080_2023-03-26_final.stac-item
2023-04-11 10:32:21	ga_ls9c_ard_3-2-1_102079_2023-04-11_final.stac-item
2023-04-11 10:32:45	ga_ls9c_ard_3-2-1_102080_2023-04-11_final.stac-item
2023-04-16 10:46:04	ga_ls9c_ard_3-2-1_105067_2023-04-16_final.stac-item
2023-04-20 10:26:32	ga_ls9c_ard_3-2-1_101080_2023-04-20_final.stac-item
2023-04-27 10:32:15	ga_ls9c_ard_3-2-1_102079_2023-04-27_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-05-02 10:45:55	ga_ls9c_ard_3-2-1_105067_2023-05-02_final.stac-item
2023-05-06 10:26:20	ga_ls9c_ard_3-2-1_101080_2023-05-06_final.stac-item
2023-05-13 10:32:05	ga_ls9c_ard_3-2-1_102079_2023-05-13_final.stac-item
2023-05-18 10:45:47	ga_ls9c_ard_3-2-1_105067_2023-05-18_final.stac-item
2023-05-29 10:31:56	ga_ls9c_ard_3-2-1_102079_2023-05-29_final.stac-item
2023-05-29 10:32:20	ga_ls9c_ard_3-2-1_102080_2023-05-29_final.stac-item
2023-06-03 10:45:40	ga_ls9c_ard_3-2-1_105067_2023-06-03_final.stac-item
2023-06-12 10:39:48	ga_ls9c_ard_3-2-1_104068_2023-06-12_final.stac-item
2023-06-14 10:31:48	ga_ls9c_ard_3-2-1_102079_2023-06-14_final.stac-item
2023-06-19 10:45:32	ga_ls9c_ard_3-2-1_105067_2023-06-19_final.stac-item
2023-06-30 10:31:54	ga_ls9c_ard_3-2-1_102079_2023-06-30_final.stac-item
2023-06-30 10:32:18	ga_ls9c_ard_3-2-1_102080_2023-06-30_final.stac-item
2023-07-05 10:45:44	ga_ls9c_ard_3-2-1_105067_2023-07-05_final.stac-item
2023-07-09 10:26:15	ga_ls9c_ard_3-2-1_101080_2023-07-09_final.stac-item
2023-07-14 10:40:02	ga_ls9c_ard_3-2-1_104068_2023-07-14_final.stac-item
2023-07-21 10:45:49	ga_ls9c_ard_3-2-1_105067_2023-07-21_final.stac-item
2023-07-25 10:27:27	ga_ls9c_ard_3-2-1_101083_2023-07-25_final.stac-item
2023-09-16 10:40:31	ga_ls9c_ard_3-2-1_104068_2023-09-16_final.stac-item
2023-09-27 10:27:53	ga_ls9c_ard_3-2-1_101083_2023-09-27_final.stac-item
2023-10-18 10:40:41	ga_ls9c_ard_3-2-1_104068_2023-10-18_final.stac-item
2023-12-21 10:40:46	ga_ls9c_ard_3-2-1_104068_2023-12-21_final.stac-item
2024-02-07 10:40:45	ga_ls9c_ard_3-2-1_104068_2024-02-07_final.stac-item
2024-02-14 10:46:28	ga_ls9c_ard_3-2-1_105067_2024-02-14_final.stac-item
2024-03-01 10:46:22	ga_ls9c_ard_3-2-1_105067_2024-03-01_final.stac-item
2024-03-10 10:40:37	ga_ls9c_ard_3-2-1_104068_2024-03-10_final.stac-item
2024-03-17 10:46:22	ga_ls9c_ard_3-2-1_105067_2024-03-17_final.stac-item
2024-03-26 10:40:30	ga_ls9c_ard_3-2-1_104068_2024-03-26_final.stac-item
2024-04-11 10:40:23	ga_ls9c_ard_3-2-1_104068_2024-04-11_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