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
2021-11-03 11:34:01	ga_ls9c_ard_3-2-1_112076_2021-11-03_final.stac-item
2021-11-08 11:36:30	ga_ls9c_ard_3-2-1_113076_2021-11-08_final.stac-item
2021-11-10 11:20:56	ga_ls9c_ard_3-2-1_110084_2021-11-10_final.stac-item
2021-12-07 11:33:27	ga_ls9c_ard_3-2-1_112076_2021-12-07_final.stac-item
2021-12-16 11:29:57	ga_ls9c_ard_3-2-1_111083_2021-12-16_final.stac-item
2021-12-23 11:33:21	ga_ls9c_ard_3-2-1_112076_2021-12-23_final.stac-item
2021-12-25 11:23:47	ga_ls9c_ard_3-2-1_110083_2021-12-25_final.stac-item
2022-01-01 11:29:58	ga_ls9c_ard_3-2-1_111083_2022-01-01_final.stac-item
2022-01-08 11:33:19	ga_ls9c_ard_3-2-1_112076_2022-01-08_final.stac-item
2022-01-08 11:34:31	ga_ls9c_ard_3-2-1_112079_2022-01-08_final.stac-item
2022-01-24 11:33:20	ga_ls9c_ard_3-2-1_112076_2022-01-24_final.stac-item
2022-01-26 11:23:46	ga_ls9c_ard_3-2-1_110083_2022-01-26_final.stac-item
2022-02-09 11:33:19	ga_ls9c_ard_3-2-1_112076_2022-02-09_final.stac-item
2022-02-25 11:33:09	ga_ls9c_ard_3-2-1_112076_2022-02-25_final.stac-item
2022-03-06 11:29:42	ga_ls9c_ard_3-2-1_111083_2022-03-06_final.stac-item
2022-03-22 11:29:39	ga_ls9c_ard_3-2-1_111083_2022-03-22_final.stac-item
2022-03-29 11:33:00	ga_ls9c_ard_3-2-1_112076_2022-03-29_final.stac-item
2022-03-31 11:23:27	ga_ls9c_ard_3-2-1_110083_2022-03-31_final.stac-item
2022-04-07 11:29:36	ga_ls9c_ard_3-2-1_111083_2022-04-07_final.stac-item
2022-04-14 11:32:55	ga_ls9c_ard_3-2-1_112076_2022-04-14_final.stac-item
2022-04-16 11:23:20	ga_ls9c_ard_3-2-1_110083_2022-04-16_final.stac-item
2022-04-23 11:29:26	ga_ls9c_ard_3-2-1_111083_2022-04-23_final.stac-item
2022-04-30 11:32:48	ga_ls9c_ard_3-2-1_112076_2022-04-30_final.stac-item
2022-05-02 11:23:14	ga_ls9c_ard_3-2-1_110083_2022-05-02_final.stac-item
2022-05-09 11:29:21	ga_ls9c_ard_3-2-1_111083_2022-05-09_final.stac-item
2022-05-25 11:29:11	ga_ls9c_ard_3-2-1_111083_2022-05-25_final.stac-item
2022-06-01 11:32:35	ga_ls9c_ard_3-2-1_112076_2022-06-01_final.stac-item
2022-06-10 11:29:13	ga_ls9c_ard_3-2-1_111083_2022-06-10_final.stac-item
2022-06-17 11:32:42	ga_ls9c_ard_3-2-1_112076_2022-06-17_final.stac-item
2022-06-17 11:33:54	ga_ls9c_ard_3-2-1_112079_2022-06-17_final.stac-item
2022-07-03 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-03_final.stac-item
2022-07-19 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-19_final.stac-item
2022-07-21 11:23:24	ga_ls9c_ard_3-2-1_110083_2022-07-21_final.stac-item
2022-08-04 11:33:10	ga_ls9c_ard_3-2-1_112076_2022-08-04_final.stac-item
2022-08-06 11:23:37	ga_ls9c_ard_3-2-1_110083_2022-08-06_final.stac-item
2022-08-13 11:29:52	ga_ls9c_ard_3-2-1_111083_2022-08-13_final.stac-item
2022-08-20 11:33:17	ga_ls9c_ard_3-2-1_112076_2022-08-20_final.stac-item
2022-08-22 11:23:43	ga_ls9c_ard_3-2-1_110083_2022-08-22_final.stac-item
2022-08-29 11:29:55	ga_ls9c_ard_3-2-1_111083_2022-08-29_final.stac-item
2022-09-05 11:33:18	ga_ls9c_ard_3-2-1_112076_2022-09-05_final.stac-item
2022-09-07 11:23:43	ga_ls9c_ard_3-2-1_110083_2022-09-07_final.stac-item
2022-09-21 11:33:24	ga_ls9c_ard_3-2-1_112076_2022-09-21_final.stac-item
2022-09-23 11:23:50	ga_ls9c_ard_3-2-1_110083_2022-09-23_final.stac-item
2022-10-07 11:33:25	ga_ls9c_ard_3-2-1_112076_2022-10-07_final.stac-item
2022-10-07 11:34:36	ga_ls9c_ard_3-2-1_112079_2022-10-07_final.stac-item
2022-10-09 11:23:52	ga_ls9c_ard_3-2-1_110083_2022-10-09_final.stac-item
2022-10-23 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-10-23_final.stac-item
2022-10-25 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-10-25_final.stac-item
2022-11-01 11:30:06	ga_ls9c_ard_3-2-1_111083_2022-11-01_final.stac-item
2022-11-08 11:33:30	ga_ls9c_ard_3-2-1_112076_2022-11-08_final.stac-item
2022-11-08 11:34:42	ga_ls9c_ard_3-2-1_112079_2022-11-08_final.stac-item
2022-11-10 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-11-10_final.stac-item
2022-11-17 11:30:09	ga_ls9c_ard_3-2-1_111083_2022-11-17_final.stac-item
2022-11-24 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-11-24_final.stac-item
2022-11-26 11:23:56	ga_ls9c_ard_3-2-1_110083_2022-11-26_final.stac-item
2022-12-03 11:30:05	ga_ls9c_ard_3-2-1_111083_2022-12-03_final.stac-item
2022-12-10 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-12-10_final.stac-item
2022-12-10 11:34:43	ga_ls9c_ard_3-2-1_112079_2022-12-10_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-19 11:30:06	ga_ls9c_ard_3-2-1_111083_2022-12-19_final.stac-item
2022-12-26 11:33:28	ga_ls9c_ard_3-2-1_112076_2022-12-26_final.stac-item
2022-12-26 11:34:40	ga_ls9c_ard_3-2-1_112079_2022-12-26_final.stac-item
2022-12-28 11:23:55	ga_ls9c_ard_3-2-1_110083_2022-12-28_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-11 11:33:30	ga_ls9c_ard_3-2-1_112076_2023-01-11_final.stac-item
2023-01-11 11:34:41	ga_ls9c_ard_3-2-1_112079_2023-01-11_final.stac-item
2023-01-13 11:23:54	ga_ls9c_ard_3-2-1_110083_2023-01-13_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-27 11:33:28	ga_ls9c_ard_3-2-1_112076_2023-01-27_final.stac-item
2023-01-27 11:34:40	ga_ls9c_ard_3-2-1_112079_2023-01-27_final.stac-item
2023-01-29 11:23:56	ga_ls9c_ard_3-2-1_110083_2023-01-29_final.stac-item
2023-02-12 11:33:34	ga_ls9c_ard_3-2-1_112076_2023-02-12_final.stac-item
2023-02-12 11:34:45	ga_ls9c_ard_3-2-1_112079_2023-02-12_final.stac-item
2023-03-16 11:33:13	ga_ls9c_ard_3-2-1_112076_2023-03-16_final.stac-item
2023-03-16 11:34:25	ga_ls9c_ard_3-2-1_112079_2023-03-16_final.stac-item
2023-03-18 11:23:38	ga_ls9c_ard_3-2-1_110083_2023-03-18_final.stac-item
2023-03-25 11:28:32	ga_ls9c_ard_3-2-1_111080_2023-03-25_final.stac-item
2023-04-10 11:29:35	ga_ls9c_ard_3-2-1_111083_2023-04-10_final.stac-item
2023-04-17 11:32:55	ga_ls9c_ard_3-2-1_112076_2023-04-17_final.stac-item
2023-04-17 11:34:07	ga_ls9c_ard_3-2-1_112079_2023-04-17_final.stac-item
2023-04-19 11:23:21	ga_ls9c_ard_3-2-1_110083_2023-04-19_final.stac-item
2023-04-26 11:29:29	ga_ls9c_ard_3-2-1_111083_2023-04-26_final.stac-item
2023-05-03 11:32:44	ga_ls9c_ard_3-2-1_112076_2023-05-03_final.stac-item
2023-05-03 11:33:56	ga_ls9c_ard_3-2-1_112079_2023-05-03_final.stac-item
2023-05-05 11:23:09	ga_ls9c_ard_3-2-1_110083_2023-05-05_final.stac-item
2023-05-12 11:29:19	ga_ls9c_ard_3-2-1_111083_2023-05-12_final.stac-item
2023-05-19 11:32:38	ga_ls9c_ard_3-2-1_112076_2023-05-19_final.stac-item
2023-05-19 11:33:50	ga_ls9c_ard_3-2-1_112079_2023-05-19_final.stac-item
2023-05-21 11:23:02	ga_ls9c_ard_3-2-1_110083_2023-05-21_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-06-04 11:32:31	ga_ls9c_ard_3-2-1_112076_2023-06-04_final.stac-item
2023-06-04 11:33:43	ga_ls9c_ard_3-2-1_112079_2023-06-04_final.stac-item
2023-06-06 11:22:56	ga_ls9c_ard_3-2-1_110083_2023-06-06_final.stac-item
2023-06-13 11:29:02	ga_ls9c_ard_3-2-1_111083_2023-06-13_final.stac-item
2023-06-20 11:32:23	ga_ls9c_ard_3-2-1_112076_2023-06-20_final.stac-item
2023-06-20 11:33:35	ga_ls9c_ard_3-2-1_112079_2023-06-20_final.stac-item
2023-06-22 11:22:49	ga_ls9c_ard_3-2-1_110083_2023-06-22_final.stac-item
2023-07-06 11:32:36	ga_ls9c_ard_3-2-1_112076_2023-07-06_final.stac-item
2023-07-06 11:33:48	ga_ls9c_ard_3-2-1_112079_2023-07-06_final.stac-item
2023-07-08 11:23:03	ga_ls9c_ard_3-2-1_110083_2023-07-08_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