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 09:57:21	ga_ls9c_ard_3-2-1_096081_2021-11-03_final.stac-item
2021-11-08 09:59:50	ga_ls9c_ard_3-2-1_097081_2021-11-08_final.stac-item
2021-11-16 10:23:54	ga_ls9c_ard_3-2-1_100082_2021-11-16_final.stac-item
2021-12-04 11:04:58	ga_ls9c_ard_3-2-1_107082_2021-12-04_final.stac-item
2021-12-07 09:56:33	ga_ls9c_ard_3-2-1_096081_2021-12-07_final.stac-item
2021-12-12 10:15:26	ga_ls9c_ard_3-2-1_099082_2021-12-12_final.stac-item
2021-12-13 10:58:41	ga_ls9c_ard_3-2-1_106082_2021-12-13_final.stac-item
2021-12-16 09:50:16	ga_ls9c_ard_3-2-1_095081_2021-12-16_final.stac-item
2021-12-17 10:33:31	ga_ls9c_ard_3-2-1_102081_2021-12-17_final.stac-item
2021-12-21 10:09:13	ga_ls9c_ard_3-2-1_098082_2021-12-21_final.stac-item
2021-12-23 09:56:28	ga_ls9c_ard_3-2-1_096081_2021-12-23_final.stac-item
2022-01-01 11:29:34	ga_ls9c_ard_3-2-1_111082_2022-01-01_final.stac-item
2022-01-02 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-01-02_final.stac-item
2022-01-08 09:56:26	ga_ls9c_ard_3-2-1_096081_2022-01-08_final.stac-item
2022-01-15 10:02:35	ga_ls9c_ard_3-2-1_097081_2022-01-15_final.stac-item
2022-01-18 10:33:30	ga_ls9c_ard_3-2-1_102081_2022-01-18_final.stac-item
2022-01-24 09:56:27	ga_ls9c_ard_3-2-1_096081_2022-01-24_final.stac-item
2022-01-31 10:02:38	ga_ls9c_ard_3-2-1_097081_2022-01-31_final.stac-item
2022-02-01 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-02-01_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-03 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-02-03_final.stac-item
2022-02-17 10:46:12	ga_ls9c_ard_3-2-1_104082_2022-02-17_final.stac-item
2022-02-18 09:50:10	ga_ls9c_ard_3-2-1_095081_2022-02-18_final.stac-item
2022-02-19 10:33:25	ga_ls9c_ard_3-2-1_102081_2022-02-19_final.stac-item
2022-02-25 09:56:16	ga_ls9c_ard_3-2-1_096081_2022-02-25_final.stac-item
2022-03-07 10:33:17	ga_ls9c_ard_3-2-1_102081_2022-03-07_final.stac-item
2022-03-19 10:58:23	ga_ls9c_ard_3-2-1_106082_2022-03-19_final.stac-item
2022-03-20 10:02:21	ga_ls9c_ard_3-2-1_097081_2022-03-20_final.stac-item
2022-03-22 09:49:59	ga_ls9c_ard_3-2-1_095081_2022-03-22_final.stac-item
2022-03-23 10:33:14	ga_ls9c_ard_3-2-1_102081_2022-03-23_final.stac-item
2022-03-25 10:21:15	ga_ls9c_ard_3-2-1_100082_2022-03-25_final.stac-item
2022-03-29 09:56:07	ga_ls9c_ard_3-2-1_096081_2022-03-29_final.stac-item
2022-04-04 10:58:19	ga_ls9c_ard_3-2-1_106082_2022-04-04_final.stac-item
2022-04-07 09:49:55	ga_ls9c_ard_3-2-1_095081_2022-04-07_final.stac-item
2022-04-08 10:33:10	ga_ls9c_ard_3-2-1_102081_2022-04-08_final.stac-item
2022-04-24 10:33:01	ga_ls9c_ard_3-2-1_102081_2022-04-24_final.stac-item
2022-05-07 10:02:03	ga_ls9c_ard_3-2-1_097081_2022-05-07_final.stac-item
2022-05-09 09:49:40	ga_ls9c_ard_3-2-1_095081_2022-05-09_final.stac-item
2022-05-10 10:32:55	ga_ls9c_ard_3-2-1_102081_2022-05-10_final.stac-item
2022-05-16 09:55:45	ga_ls9c_ard_3-2-1_096081_2022-05-16_final.stac-item
2022-05-29 11:04:04	ga_ls9c_ard_3-2-1_107082_2022-05-29_final.stac-item
2022-06-08 10:01:53	ga_ls9c_ard_3-2-1_097081_2022-06-08_final.stac-item
2022-06-10 09:49:32	ga_ls9c_ard_3-2-1_095081_2022-06-10_final.stac-item
2022-06-10 11:28:49	ga_ls9c_ard_3-2-1_111082_2022-06-10_final.stac-item
2022-06-11 10:32:49	ga_ls9c_ard_3-2-1_102081_2022-06-11_final.stac-item
2022-06-15 10:08:33	ga_ls9c_ard_3-2-1_098082_2022-06-15_final.stac-item
2022-06-26 09:49:53	ga_ls9c_ard_3-2-1_095081_2022-06-26_final.stac-item
2022-06-30 11:04:26	ga_ls9c_ard_3-2-1_107082_2022-06-30_final.stac-item
2022-07-03 09:56:03	ga_ls9c_ard_3-2-1_096081_2022-07-03_final.stac-item
2022-07-12 09:49:49	ga_ls9c_ard_3-2-1_095081_2022-07-12_final.stac-item
2022-07-12 11:29:06	ga_ls9c_ard_3-2-1_111082_2022-07-12_final.stac-item
2022-07-17 10:08:46	ga_ls9c_ard_3-2-1_098082_2022-07-17_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-25 10:58:21	ga_ls9c_ard_3-2-1_106082_2022-07-25_final.stac-item
2022-07-27 10:46:01	ga_ls9c_ard_3-2-1_104082_2022-07-27_final.stac-item
2022-07-28 09:50:00	ga_ls9c_ard_3-2-1_095081_2022-07-28_final.stac-item
2022-08-14 10:33:27	ga_ls9c_ard_3-2-1_102081_2022-08-14_final.stac-item
2022-08-17 11:04:46	ga_ls9c_ard_3-2-1_107082_2022-08-17_final.stac-item
2022-08-20 09:56:24	ga_ls9c_ard_3-2-1_096081_2022-08-20_final.stac-item
2022-09-03 10:09:10	ga_ls9c_ard_3-2-1_098082_2022-09-03_final.stac-item
2022-09-05 09:56:24	ga_ls9c_ard_3-2-1_096081_2022-09-05_final.stac-item
2022-09-06 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-09-06_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-15 10:33:33	ga_ls9c_ard_3-2-1_102081_2022-09-15_final.stac-item
2022-09-19 10:09:15	ga_ls9c_ard_3-2-1_098082_2022-09-19_final.stac-item
2022-09-22 10:40:10	ga_ls9c_ard_3-2-1_103082_2022-09-22_final.stac-item
2022-09-28 10:02:43	ga_ls9c_ard_3-2-1_097081_2022-09-28_final.stac-item
2022-09-30 09:50:21	ga_ls9c_ard_3-2-1_095081_2022-09-30_final.stac-item
2022-10-07 09:56:31	ga_ls9c_ard_3-2-1_096081_2022-10-07_final.stac-item
2022-10-12 10:15:32	ga_ls9c_ard_3-2-1_099082_2022-10-12_final.stac-item
2022-10-13 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-10-13_final.stac-item
2022-10-14 10:02:47	ga_ls9c_ard_3-2-1_097081_2022-10-14_final.stac-item
2022-10-24 10:40:18	ga_ls9c_ard_3-2-1_103082_2022-10-24_final.stac-item
2022-10-29 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-10-29_final.stac-item
2022-10-31 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-10-31_final.stac-item
2022-11-02 10:33:40	ga_ls9c_ard_3-2-1_102081_2022-11-02_final.stac-item
2022-11-05 11:04:58	ga_ls9c_ard_3-2-1_107082_2022-11-05_final.stac-item
2022-11-16 10:46:29	ga_ls9c_ard_3-2-1_104082_2022-11-16_final.stac-item
2022-11-21 11:05:01	ga_ls9c_ard_3-2-1_107082_2022-11-21_final.stac-item
2022-11-30 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-11-30_final.stac-item
2022-12-02 10:46:25	ga_ls9c_ard_3-2-1_104082_2022-12-02_final.stac-item
2022-12-04 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-04_final.stac-item
2022-12-07 11:05:00	ga_ls9c_ard_3-2-1_107082_2022-12-07_final.stac-item
2022-12-18 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-12-18_final.stac-item
2022-12-20 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-20_final.stac-item
2022-12-23 11:04:57	ga_ls9c_ard_3-2-1_107082_2022-12-23_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-05 10:33:43	ga_ls9c_ard_3-2-1_102081_2023-01-05_final.stac-item
2023-01-21 10:33:33	ga_ls9c_ard_3-2-1_102081_2023-01-21_final.stac-item
2023-03-26 10:33:17	ga_ls9c_ard_3-2-1_102081_2023-03-26_final.stac-item
2023-04-11 10:33:09	ga_ls9c_ard_3-2-1_102081_2023-04-11_final.stac-item
2023-04-27 10:33:03	ga_ls9c_ard_3-2-1_102081_2023-04-27_final.stac-item
2023-05-08 10:14:46	ga_ls9c_ard_3-2-1_099082_2023-05-08_final.stac-item
2023-05-13 10:32:53	ga_ls9c_ard_3-2-1_102081_2023-05-13_final.stac-item
2023-05-15 10:20:55	ga_ls9c_ard_3-2-1_100082_2023-05-15_final.stac-item
2023-05-29 10:32:44	ga_ls9c_ard_3-2-1_102081_2023-05-29_final.stac-item
2023-06-14 10:32:36	ga_ls9c_ard_3-2-1_102081_2023-06-14_final.stac-item
2023-06-25 10:14:26	ga_ls9c_ard_3-2-1_099082_2023-06-25_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-06-30 10:32:42	ga_ls9c_ard_3-2-1_102081_2023-06-30_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