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
2021-11-12 09:18:45	ga_ls9c_ard_3-2-1_091072_2021-11-11_final.stac-item
2021-11-19 09:06:51	ga_ls9c_ard_3-2-1_088083_2021-11-18_final.stac-item
2021-12-31 09:07:49	ga_ls9c_ard_3-2-1_088083_2021-12-30_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-02-01 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-01-31_final.stac-item
2022-02-17 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-03-05 09:07:33	ga_ls9c_ard_3-2-1_088083_2022-03-04_final.stac-item
2022-03-21 09:07:31	ga_ls9c_ard_3-2-1_088083_2022-03-20_final.stac-item
2022-03-26 09:21:38	ga_ls9c_ard_3-2-1_091072_2022-03-25_final.stac-item
2022-04-06 09:07:28	ga_ls9c_ard_3-2-1_088083_2022-04-05_final.stac-item
2022-04-22 09:07:17	ga_ls9c_ard_3-2-1_088083_2022-04-21_final.stac-item
2022-05-08 09:07:13	ga_ls9c_ard_3-2-1_088083_2022-05-07_final.stac-item
2022-05-24 09:07:02	ga_ls9c_ard_3-2-1_088083_2022-05-23_final.stac-item
2022-05-31 09:11:14	ga_ls9c_ard_3-2-1_089078_2022-05-30_final.stac-item
2022-06-09 09:07:04	ga_ls9c_ard_3-2-1_088083_2022-06-08_final.stac-item
2022-06-16 09:11:21	ga_ls9c_ard_3-2-1_089078_2022-06-15_final.stac-item
2022-06-25 09:07:25	ga_ls9c_ard_3-2-1_088083_2022-06-24_final.stac-item
2022-07-11 09:07:21	ga_ls9c_ard_3-2-1_088083_2022-07-10_final.stac-item
2022-07-27 09:07:32	ga_ls9c_ard_3-2-1_088083_2022-07-26_final.stac-item
2022-08-01 09:21:45	ga_ls9c_ard_3-2-1_091072_2022-07-31_final.stac-item
2022-08-12 09:07:42	ga_ls9c_ard_3-2-1_088083_2022-08-11_final.stac-item
2022-08-28 09:07:46	ga_ls9c_ard_3-2-1_088083_2022-08-27_final.stac-item
2022-09-02 09:21:55	ga_ls9c_ard_3-2-1_091072_2022-09-01_final.stac-item
2022-09-13 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-09-12_final.stac-item
2022-09-18 09:22:00	ga_ls9c_ard_3-2-1_091072_2022-09-17_final.stac-item
2022-09-29 09:07:54	ga_ls9c_ard_3-2-1_088083_2022-09-28_final.stac-item
2022-10-06 09:12:04	ga_ls9c_ard_3-2-1_089078_2022-10-05_final.stac-item
2022-10-15 09:07:58	ga_ls9c_ard_3-2-1_088083_2022-10-14_final.stac-item
2022-10-22 09:12:10	ga_ls9c_ard_3-2-1_089078_2022-10-21_final.stac-item
2022-10-31 09:07:58	ga_ls9c_ard_3-2-1_088083_2022-10-30_final.stac-item
2022-11-07 09:12:09	ga_ls9c_ard_3-2-1_089078_2022-11-06_final.stac-item
2022-11-16 09:08:00	ga_ls9c_ard_3-2-1_088083_2022-11-15_final.stac-item
2022-11-23 09:12:11	ga_ls9c_ard_3-2-1_089078_2022-11-22_final.stac-item
2022-12-02 09:07:56	ga_ls9c_ard_3-2-1_088083_2022-12-01_final.stac-item
2022-12-09 09:12:10	ga_ls9c_ard_3-2-1_089078_2022-12-08_final.stac-item
2022-12-18 09:07:58	ga_ls9c_ard_3-2-1_088083_2022-12-17_final.stac-item
2022-12-25 09:12:07	ga_ls9c_ard_3-2-1_089078_2022-12-24_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-19 09:07:51	ga_ls9c_ard_3-2-1_088083_2023-01-18_final.stac-item
2023-01-26 09:12:06	ga_ls9c_ard_3-2-1_089078_2023-01-25_final.stac-item
2023-02-04 09:08:01	ga_ls9c_ard_3-2-1_088083_2023-02-03_final.stac-item
2023-02-11 09:12:13	ga_ls9c_ard_3-2-1_089078_2023-02-10_final.stac-item
2023-02-20 09:07:54	ga_ls9c_ard_3-2-1_088083_2023-02-19_final.stac-item
2023-02-25 09:21:57	ga_ls9c_ard_3-2-1_091072_2023-02-24_final.stac-item
2023-03-08 09:07:42	ga_ls9c_ard_3-2-1_088083_2023-03-07_final.stac-item
2023-03-13 09:21:50	ga_ls9c_ard_3-2-1_091072_2023-03-12_final.stac-item
2023-03-15 09:11:52	ga_ls9c_ard_3-2-1_089078_2023-03-14_final.stac-item
2023-03-24 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-03-23_final.stac-item
2023-03-29 09:21:39	ga_ls9c_ard_3-2-1_091072_2023-03-28_final.stac-item
2023-04-09 09:07:27	ga_ls9c_ard_3-2-1_088083_2023-04-08_final.stac-item
2023-04-16 09:11:34	ga_ls9c_ard_3-2-1_089078_2023-04-15_final.stac-item
2023-04-25 09:07:21	ga_ls9c_ard_3-2-1_088083_2023-04-24_final.stac-item
2023-05-02 09:11:25	ga_ls9c_ard_3-2-1_089078_2023-05-01_final.stac-item
2023-05-11 09:07:11	ga_ls9c_ard_3-2-1_088083_2023-05-10_final.stac-item
2023-05-18 09:11:18	ga_ls9c_ard_3-2-1_089078_2023-05-17_final.stac-item
2023-05-27 09:07:00	ga_ls9c_ard_3-2-1_088083_2023-05-26_final.stac-item
2023-06-12 09:06:54	ga_ls9c_ard_3-2-1_088083_2023-06-11_final.stac-item
2023-06-19 09:11:02	ga_ls9c_ard_3-2-1_089078_2023-06-18_final.stac-item
2023-06-28 09:06:55	ga_ls9c_ard_3-2-1_088083_2023-06-27_final.stac-item
2023-07-05 09:11:15	ga_ls9c_ard_3-2-1_089078_2023-07-04_final.stac-item
2023-07-14 09:07:08	ga_ls9c_ard_3-2-1_088083_2023-07-13_final.stac-item
2023-07-19 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-07-18_final.stac-item
2023-07-30 09:07:12	ga_ls9c_ard_3-2-1_088083_2023-07-29_final.stac-item
2023-08-04 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-08-03_final.stac-item
2023-08-15 09:07:18	ga_ls9c_ard_3-2-1_088083_2023-08-14_final.stac-item
2023-08-20 09:21:29	ga_ls9c_ard_3-2-1_091072_2023-08-19_final.stac-item
2023-08-31 09:07:28	ga_ls9c_ard_3-2-1_088083_2023-08-30_final.stac-item
2023-09-05 09:21:40	ga_ls9c_ard_3-2-1_091072_2023-09-04_final.stac-item
2023-09-16 09:07:37	ga_ls9c_ard_3-2-1_088083_2023-09-15_final.stac-item
2023-09-21 09:21:45	ga_ls9c_ard_3-2-1_091072_2023-09-20_final.stac-item
2023-10-02 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-10-01_final.stac-item
2023-10-07 09:21:48	ga_ls9c_ard_3-2-1_091072_2023-10-06_final.stac-item
2023-10-18 09:07:47	ga_ls9c_ard_3-2-1_088083_2023-10-17_final.stac-item
2023-10-23 09:21:56	ga_ls9c_ard_3-2-1_091072_2023-10-22_final.stac-item
2023-11-03 09:07:39	ga_ls9c_ard_3-2-1_088083_2023-11-02_final.stac-item
2023-11-08 09:21:51	ga_ls9c_ard_3-2-1_091072_2023-11-07_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-24 09:21:59	ga_ls9c_ard_3-2-1_091072_2023-11-23_final.stac-item
2023-12-05 09:07:47	ga_ls9c_ard_3-2-1_088083_2023-12-04_final.stac-item
2023-12-10 09:21:56	ga_ls9c_ard_3-2-1_091072_2023-12-09_final.stac-item
2023-12-21 09:07:52	ga_ls9c_ard_3-2-1_088083_2023-12-20_final.stac-item
2023-12-26 09:22:01	ga_ls9c_ard_3-2-1_091072_2023-12-25_final.stac-item
2024-01-11 09:21:57	ga_ls9c_ard_3-2-1_091072_2024-01-10_final.stac-item
2024-01-22 09:07:46	ga_ls9c_ard_3-2-1_088083_2024-01-21_final.stac-item
2024-01-27 09:21:56	ga_ls9c_ard_3-2-1_091072_2024-01-26_final.stac-item
2024-02-07 09:07:51	ga_ls9c_ard_3-2-1_088083_2024-02-06_final.stac-item
2024-02-12 09:21:58	ga_ls9c_ard_3-2-1_091072_2024-02-11_final.stac-item
2024-02-23 09:07:36	ga_ls9c_ard_3-2-1_088083_2024-02-22_final.stac-item
2024-02-28 09:21:49	ga_ls9c_ard_3-2-1_091072_2024-02-27_final.stac-item
2024-03-10 09:07:43	ga_ls9c_ard_3-2-1_088083_2024-03-09_final.stac-item
2024-03-15 09:21:50	ga_ls9c_ard_3-2-1_091072_2024-03-14_final.stac-item
2024-03-26 09:07:36	ga_ls9c_ard_3-2-1_088083_2024-03-25_final.stac-item
2024-03-31 09:21:42	ga_ls9c_ard_3-2-1_091072_2024-03-30_final.stac-item
2024-04-11 09:07:29	ga_ls9c_ard_3-2-1_088083_2024-04-10_final.stac-item
2024-04-16 09:21:33	ga_ls9c_ard_3-2-1_091072_2024-04-15_final.stac-item
2024-04-27 09:07:09	ga_ls9c_ard_3-2-1_088083_2024-04-26_final.stac-item
2024-05-02 09:21:17	ga_ls9c_ard_3-2-1_091072_2024-05-01_final.stac-item
2024-05-13 09:07:06	ga_ls9c_ard_3-2-1_088083_2024-05-12_final.stac-item
2024-05-18 09:21:09	ga_ls9c_ard_3-2-1_091072_2024-05-17_nrt.stac-item
2024-05-29 09:06:53	ga_ls9c_ard_3-2-1_088083_2024-05-28_nrt.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