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
2021-11-08 09:55:51	ga_ls9c_ard_3-2-1_097071_2021-11-08_final.stac-item
2021-11-13 09:58:19	ga_ls9c_ard_3-2-1_097071_2021-11-13_final.stac-item
2021-11-18 10:00:46	ga_ls9c_ard_3-2-1_097071_2021-11-18_final.stac-item
2021-11-23 10:02:50	ga_ls9c_ard_3-2-1_098070_2021-11-23_final.stac-item
2021-11-25 09:47:16	ga_ls9c_ard_3-2-1_095078_2021-11-25_final.stac-item
2021-12-16 09:49:04	ga_ls9c_ard_3-2-1_095078_2021-12-16_final.stac-item
2021-12-30 09:58:39	ga_ls9c_ard_3-2-1_097071_2021-12-30_final.stac-item
2022-01-06 10:03:37	ga_ls9c_ard_3-2-1_098068_2022-01-06_final.stac-item
2022-01-15 09:58:12	ga_ls9c_ard_3-2-1_097070_2022-01-15_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_final.stac-item
2022-01-22 10:03:37	ga_ls9c_ard_3-2-1_098068_2022-01-22_final.stac-item
2022-02-18 09:48:58	ga_ls9c_ard_3-2-1_095078_2022-02-18_final.stac-item
2022-03-20 09:58:22	ga_ls9c_ard_3-2-1_097071_2022-03-20_final.stac-item
2022-03-22 09:48:47	ga_ls9c_ard_3-2-1_095078_2022-03-22_final.stac-item
2022-03-27 10:03:17	ga_ls9c_ard_3-2-1_098068_2022-03-27_final.stac-item
2022-04-05 09:58:18	ga_ls9c_ard_3-2-1_097071_2022-04-05_final.stac-item
2022-04-07 09:48:43	ga_ls9c_ard_3-2-1_095078_2022-04-07_final.stac-item
2022-04-12 10:03:14	ga_ls9c_ard_3-2-1_098068_2022-04-12_final.stac-item
2022-04-23 09:48:33	ga_ls9c_ard_3-2-1_095078_2022-04-23_final.stac-item
2022-04-28 10:03:06	ga_ls9c_ard_3-2-1_098068_2022-04-28_final.stac-item
2022-05-09 09:48:28	ga_ls9c_ard_3-2-1_095078_2022-05-09_final.stac-item
2022-05-14 10:02:57	ga_ls9c_ard_3-2-1_098068_2022-05-14_final.stac-item
2022-05-30 10:02:52	ga_ls9c_ard_3-2-1_098068_2022-05-30_final.stac-item
2022-06-10 09:48:20	ga_ls9c_ard_3-2-1_095078_2022-06-10_final.stac-item
2022-06-15 10:02:58	ga_ls9c_ard_3-2-1_098068_2022-06-15_final.stac-item
2022-06-24 09:58:14	ga_ls9c_ard_3-2-1_097071_2022-06-24_final.stac-item
2022-06-26 09:48:41	ga_ls9c_ard_3-2-1_095078_2022-06-26_final.stac-item
2022-07-12 09:48:37	ga_ls9c_ard_3-2-1_095078_2022-07-12_final.stac-item
2022-07-28 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-07-28_final.stac-item
2022-08-11 09:58:32	ga_ls9c_ard_3-2-1_097071_2022-08-11_final.stac-item
2022-08-13 09:48:59	ga_ls9c_ard_3-2-1_095078_2022-08-13_final.stac-item
2022-08-18 10:03:34	ga_ls9c_ard_3-2-1_098068_2022-08-18_final.stac-item
2022-08-29 09:49:02	ga_ls9c_ard_3-2-1_095078_2022-08-29_final.stac-item
2022-09-03 10:03:35	ga_ls9c_ard_3-2-1_098068_2022-09-03_final.stac-item
2022-09-12 09:58:37	ga_ls9c_ard_3-2-1_097071_2022-09-12_final.stac-item
2022-09-19 10:03:40	ga_ls9c_ard_3-2-1_098068_2022-09-19_final.stac-item
2022-09-30 09:49:09	ga_ls9c_ard_3-2-1_095078_2022-09-30_final.stac-item
2022-10-05 10:03:42	ga_ls9c_ard_3-2-1_098068_2022-10-05_final.stac-item
2022-10-14 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-14_final.stac-item
2022-10-16 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-10-16_final.stac-item
2022-10-21 10:03:48	ga_ls9c_ard_3-2-1_098068_2022-10-21_final.stac-item
2022-10-30 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-30_final.stac-item
2022-11-06 10:03:46	ga_ls9c_ard_3-2-1_098068_2022-11-06_final.stac-item
2022-11-15 09:58:26	ga_ls9c_ard_3-2-1_097070_2022-11-15_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-22 10:03:49	ga_ls9c_ard_3-2-1_098068_2022-11-22_final.stac-item
2022-12-01 09:58:22	ga_ls9c_ard_3-2-1_097070_2022-12-01_final.stac-item
2022-12-01 09:58:46	ga_ls9c_ard_3-2-1_097071_2022-12-01_final.stac-item
2022-12-03 09:49:13	ga_ls9c_ard_3-2-1_095078_2022-12-03_final.stac-item
2022-12-08 10:03:48	ga_ls9c_ard_3-2-1_098068_2022-12-08_final.stac-item
2022-12-17 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-12-17_final.stac-item
2022-12-17 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-12-17_final.stac-item
2022-12-19 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-12-19_final.stac-item
2022-12-24 10:03:44	ga_ls9c_ard_3-2-1_098068_2022-12-24_final.stac-item
2023-01-02 09:58:25	ga_ls9c_ard_3-2-1_097070_2023-01-02_final.stac-item
2023-01-02 09:58:49	ga_ls9c_ard_3-2-1_097071_2023-01-02_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-09 10:03:48	ga_ls9c_ard_3-2-1_098068_2023-01-09_final.stac-item
2023-01-18 09:58:18	ga_ls9c_ard_3-2-1_097070_2023-01-18_final.stac-item
2023-01-25 10:03:43	ga_ls9c_ard_3-2-1_098068_2023-01-25_final.stac-item
2023-02-03 09:58:27	ga_ls9c_ard_3-2-1_097070_2023-02-03_final.stac-item
2023-02-03 09:58:51	ga_ls9c_ard_3-2-1_097071_2023-02-03_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-02-10 10:03:51	ga_ls9c_ard_3-2-1_098068_2023-02-10_final.stac-item
2023-02-19 09:58:21	ga_ls9c_ard_3-2-1_097070_2023-02-19_final.stac-item
2023-02-19 09:58:45	ga_ls9c_ard_3-2-1_097071_2023-02-19_final.stac-item
2023-02-26 10:03:37	ga_ls9c_ard_3-2-1_098068_2023-02-26_final.stac-item
2023-03-07 09:58:33	ga_ls9c_ard_3-2-1_097071_2023-03-07_final.stac-item
2023-03-23 09:58:03	ga_ls9c_ard_3-2-1_097070_2023-03-23_final.stac-item
2023-03-30 10:03:18	ga_ls9c_ard_3-2-1_098068_2023-03-30_final.stac-item
2023-04-08 09:57:54	ga_ls9c_ard_3-2-1_097070_2023-04-08_final.stac-item
2023-04-10 09:48:42	ga_ls9c_ard_3-2-1_095078_2023-04-10_final.stac-item
2023-04-15 10:03:11	ga_ls9c_ard_3-2-1_098068_2023-04-15_final.stac-item
2023-04-24 09:57:48	ga_ls9c_ard_3-2-1_097070_2023-04-24_final.stac-item
2023-04-26 09:48:36	ga_ls9c_ard_3-2-1_095078_2023-04-26_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-10 09:57:37	ga_ls9c_ard_3-2-1_097070_2023-05-10_final.stac-item
2023-05-12 09:48:26	ga_ls9c_ard_3-2-1_095078_2023-05-12_final.stac-item
2023-05-17 10:02:56	ga_ls9c_ard_3-2-1_098068_2023-05-17_final.stac-item
2023-05-26 09:57:26	ga_ls9c_ard_3-2-1_097070_2023-05-26_final.stac-item
2023-05-28 09:48:16	ga_ls9c_ard_3-2-1_095078_2023-05-28_final.stac-item
2023-06-02 10:02:49	ga_ls9c_ard_3-2-1_098068_2023-06-02_final.stac-item
2023-06-11 09:57:45	ga_ls9c_ard_3-2-1_097071_2023-06-11_final.stac-item
2023-06-13 09:48:09	ga_ls9c_ard_3-2-1_095078_2023-06-13_final.stac-item
2023-06-18 10:02:40	ga_ls9c_ard_3-2-1_098068_2023-06-18_final.stac-item
2023-06-27 09:57:19	ga_ls9c_ard_3-2-1_097070_2023-06-27_final.stac-item
2023-06-29 09:48:13	ga_ls9c_ard_3-2-1_095078_2023-06-29_final.stac-item
2023-07-04 10:02:52	ga_ls9c_ard_3-2-1_098068_2023-07-04_final.stac-item
2023-07-13 09:57:58	ga_ls9c_ard_3-2-1_097071_2023-07-13_final.stac-item
2023-08-30 09:58:18	ga_ls9c_ard_3-2-1_097071_2023-08-30_final.stac-item
2023-10-01 09:58:25	ga_ls9c_ard_3-2-1_097071_2023-10-01_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-18 09:58:34	ga_ls9c_ard_3-2-1_097071_2023-11-18_final.stac-item
2023-12-04 09:58:38	ga_ls9c_ard_3-2-1_097071_2023-12-04_final.stac-item
2023-12-20 09:58:42	ga_ls9c_ard_3-2-1_097071_2023-12-20_final.stac-item
2024-01-05 09:58:36	ga_ls9c_ard_3-2-1_097071_2024-01-05_final.stac-item
2024-01-21 09:58:37	ga_ls9c_ard_3-2-1_097071_2024-01-21_final.stac-item
2024-02-06 09:58:41	ga_ls9c_ard_3-2-1_097071_2024-02-06_final.stac-item
2024-02-22 09:58:27	ga_ls9c_ard_3-2-1_097071_2024-02-22_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