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
2021-11-10 11:16:57	ga_ls9c_ard_3-2-1_110074_2021-11-10_final.stac-item
2021-11-16 10:20:19	ga_ls9c_ard_3-2-1_100073_2021-11-16_final.stac-item
2021-12-06 09:10:31	ga_ls9c_ard_3-2-1_089074_2021-12-05_final.stac-item
2021-12-10 10:24:14	ga_ls9c_ard_3-2-1_101073_2021-12-10_final.stac-item
2021-12-12 11:51:08	ga_ls9c_ard_3-2-1_115074_2021-12-12_final.stac-item
2021-12-17 10:30:20	ga_ls9c_ard_3-2-1_102073_2021-12-17_final.stac-item
2021-12-18 11:14:00	ga_ls9c_ard_3-2-1_109074_2021-12-18_final.stac-item
2021-12-19 10:17:59	ga_ls9c_ard_3-2-1_100073_2021-12-19_final.stac-item
2021-12-22 09:10:24	ga_ls9c_ard_3-2-1_089074_2021-12-21_final.stac-item
2021-12-25 11:20:12	ga_ls9c_ard_3-2-1_110074_2021-12-25_final.stac-item
2021-12-26 10:24:10	ga_ls9c_ard_3-2-1_101073_2021-12-26_final.stac-item
2022-01-01 11:25:58	ga_ls9c_ard_3-2-1_111073_2022-01-01_final.stac-item
2022-01-04 10:17:59	ga_ls9c_ard_3-2-1_100073_2022-01-04_final.stac-item
2022-01-07 09:10:23	ga_ls9c_ard_3-2-1_089074_2022-01-06_final.stac-item
2022-01-18 10:30:19	ga_ls9c_ard_3-2-1_102073_2022-01-18_final.stac-item
2022-02-03 10:30:20	ga_ls9c_ard_3-2-1_102073_2022-02-03_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-18 11:25:51	ga_ls9c_ard_3-2-1_111073_2022-02-18_final.stac-item
2022-03-23 10:30:02	ga_ls9c_ard_3-2-1_102073_2022-03-23_final.stac-item
2022-04-07 11:25:37	ga_ls9c_ard_3-2-1_111073_2022-04-07_final.stac-item
2022-04-10 10:17:36	ga_ls9c_ard_3-2-1_100073_2022-04-10_final.stac-item
2022-04-17 10:23:42	ga_ls9c_ard_3-2-1_101073_2022-04-17_final.stac-item
2022-04-23 11:25:26	ga_ls9c_ard_3-2-1_111073_2022-04-23_final.stac-item
2022-05-03 10:23:37	ga_ls9c_ard_3-2-1_101073_2022-05-03_final.stac-item
2022-05-09 11:25:21	ga_ls9c_ard_3-2-1_111073_2022-05-09_final.stac-item
2022-05-10 10:29:43	ga_ls9c_ard_3-2-1_102073_2022-05-10_final.stac-item
2022-05-19 10:23:24	ga_ls9c_ard_3-2-1_101073_2022-05-19_final.stac-item
2022-05-25 11:25:12	ga_ls9c_ard_3-2-1_111073_2022-05-25_final.stac-item
2022-05-26 10:29:34	ga_ls9c_ard_3-2-1_102073_2022-05-26_final.stac-item
2022-05-27 11:13:14	ga_ls9c_ard_3-2-1_109074_2022-05-27_final.stac-item
2022-06-04 10:23:25	ga_ls9c_ard_3-2-1_101073_2022-06-04_final.stac-item
2022-06-20 10:23:37	ga_ls9c_ard_3-2-1_101073_2022-06-20_final.stac-item
2022-06-22 11:50:36	ga_ls9c_ard_3-2-1_115074_2022-06-22_final.stac-item
2022-06-27 10:29:57	ga_ls9c_ard_3-2-1_102073_2022-06-27_final.stac-item
2022-06-29 10:17:35	ga_ls9c_ard_3-2-1_100073_2022-06-29_final.stac-item
2022-07-06 10:23:44	ga_ls9c_ard_3-2-1_101073_2022-07-06_final.stac-item
2022-07-16 11:01:11	ga_ls9c_ard_3-2-1_107074_2022-07-16_final.stac-item
2022-07-22 10:23:49	ga_ls9c_ard_3-2-1_101073_2022-07-22_final.stac-item
2022-07-30 11:13:46	ga_ls9c_ard_3-2-1_109074_2022-07-30_final.stac-item
2022-08-03 09:10:12	ga_ls9c_ard_3-2-1_089074_2022-08-02_final.stac-item
2022-08-07 10:24:01	ga_ls9c_ard_3-2-1_101073_2022-08-07_final.stac-item
2022-08-09 11:50:57	ga_ls9c_ard_3-2-1_115074_2022-08-09_final.stac-item
2022-08-13 11:25:52	ga_ls9c_ard_3-2-1_111073_2022-08-13_final.stac-item
2022-08-19 09:10:20	ga_ls9c_ard_3-2-1_089074_2022-08-18_final.stac-item
2022-08-22 11:20:08	ga_ls9c_ard_3-2-1_110074_2022-08-22_final.stac-item
2022-08-23 10:24:07	ga_ls9c_ard_3-2-1_101073_2022-08-23_final.stac-item
2022-08-25 11:51:02	ga_ls9c_ard_3-2-1_115074_2022-08-25_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-09-01 10:17:56	ga_ls9c_ard_3-2-1_100073_2022-09-01_final.stac-item
2022-09-04 09:10:21	ga_ls9c_ard_3-2-1_089074_2022-09-03_final.stac-item
2022-09-08 10:24:06	ga_ls9c_ard_3-2-1_101073_2022-09-08_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-17 10:18:01	ga_ls9c_ard_3-2-1_100073_2022-09-17_final.stac-item
2022-09-24 10:24:14	ga_ls9c_ard_3-2-1_101073_2022-09-24_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-01 10:30:25	ga_ls9c_ard_3-2-1_102073_2022-10-01_final.stac-item
2022-10-06 09:10:28	ga_ls9c_ard_3-2-1_089074_2022-10-05_final.stac-item
2022-10-10 10:24:16	ga_ls9c_ard_3-2-1_101073_2022-10-10_final.stac-item
2022-10-15 10:43:15	ga_ls9c_ard_3-2-1_104074_2022-10-15_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-17 10:30:31	ga_ls9c_ard_3-2-1_102073_2022-10-17_final.stac-item
2022-10-20 11:01:49	ga_ls9c_ard_3-2-1_107074_2022-10-20_final.stac-item
2022-10-26 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-10-26_final.stac-item
2022-10-28 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-10-28_final.stac-item
2022-11-02 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-11-02_final.stac-item
2022-11-05 11:01:47	ga_ls9c_ard_3-2-1_107074_2022-11-05_final.stac-item
2022-11-11 10:24:21	ga_ls9c_ard_3-2-1_101073_2022-11-11_final.stac-item
2022-11-17 11:26:10	ga_ls9c_ard_3-2-1_111073_2022-11-17_final.stac-item
2022-11-18 10:30:32	ga_ls9c_ard_3-2-1_102073_2022-11-18_final.stac-item
2022-11-27 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-11-27_final.stac-item
2022-12-04 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-04_final.stac-item
2022-12-05 11:14:09	ga_ls9c_ard_3-2-1_109074_2022-12-05_final.stac-item
2022-12-09 09:10:34	ga_ls9c_ard_3-2-1_089074_2022-12-08_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-15 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-12-15_final.stac-item
2022-12-25 09:10:31	ga_ls9c_ard_3-2-1_089074_2022-12-24_final.stac-item
2022-12-29 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-12-29_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-14 10:24:17	ga_ls9c_ard_3-2-1_101073_2023-01-14_final.stac-item
2023-01-30 10:24:20	ga_ls9c_ard_3-2-1_101073_2023-01-30_final.stac-item
2023-02-05 11:26:11	ga_ls9c_ard_3-2-1_111073_2023-02-05_final.stac-item
2023-02-15 10:24:21	ga_ls9c_ard_3-2-1_101073_2023-02-15_final.stac-item
2023-02-23 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-02-23_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-19 10:24:01	ga_ls9c_ard_3-2-1_101073_2023-03-19_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-04-10 11:25:36	ga_ls9c_ard_3-2-1_111073_2023-04-10_final.stac-item
2023-04-20 10:23:44	ga_ls9c_ard_3-2-1_101073_2023-04-20_final.stac-item
2023-05-06 10:23:32	ga_ls9c_ard_3-2-1_101073_2023-05-06_final.stac-item
2023-05-22 10:23:24	ga_ls9c_ard_3-2-1_101073_2023-05-22_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-06-07 10:23:19	ga_ls9c_ard_3-2-1_101073_2023-06-07_final.stac-item
2023-06-13 11:25:02	ga_ls9c_ard_3-2-1_111073_2023-06-13_final.stac-item
2023-06-22 11:19:14	ga_ls9c_ard_3-2-1_110074_2023-06-22_final.stac-item
2023-06-23 10:23:12	ga_ls9c_ard_3-2-1_101073_2023-06-23_final.stac-item
2023-06-25 11:50:07	ga_ls9c_ard_3-2-1_115074_2023-06-25_final.stac-item
2023-07-01 11:13:12	ga_ls9c_ard_3-2-1_109074_2023-07-01_final.stac-item
2023-07-09 10:23:27	ga_ls9c_ard_3-2-1_101073_2023-07-09_final.stac-item
2023-07-11 11:50:23	ga_ls9c_ard_3-2-1_115074_2023-07-11_final.stac-item
2023-09-21 11:01:26	ga_ls9c_ard_3-2-1_107074_2023-09-21_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