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
2021-11-05 09:37:49	ga_ls9c_ard_3-2-1_093079_2021-11-05_final.stac-item
2021-11-07 09:19:04	ga_ls9c_ard_3-2-1_090079_2021-11-06_final.stac-item
2021-11-07 10:57:44	ga_ls9c_ard_3-2-1_106079_2021-11-07_final.stac-item
2021-11-10 09:40:17	ga_ls9c_ard_3-2-1_094079_2021-11-10_final.stac-item
2021-11-12 09:21:32	ga_ls9c_ard_3-2-1_091079_2021-11-11_final.stac-item
2021-11-12 11:00:12	ga_ls9c_ard_3-2-1_106079_2021-11-12_final.stac-item
2021-11-17 09:24:04	ga_ls9c_ard_3-2-1_091079_2021-11-16_final.stac-item
2021-11-22 09:26:27	ga_ls9c_ard_3-2-1_091079_2021-11-21_final.stac-item
2021-12-06 09:12:30	ga_ls9c_ard_3-2-1_089079_2021-12-05_final.stac-item
2021-12-16 11:28:21	ga_ls9c_ard_3-2-1_111079_2021-12-16_final.stac-item
2021-12-20 11:03:38	ga_ls9c_ard_3-2-1_107079_2021-12-20_final.stac-item
2021-12-22 09:12:24	ga_ls9c_ard_3-2-1_089079_2021-12-21_final.stac-item
2021-12-29 09:18:35	ga_ls9c_ard_3-2-1_090079_2021-12-28_final.stac-item
2022-01-03 09:37:07	ga_ls9c_ard_3-2-1_093079_2022-01-03_final.stac-item
2022-01-30 09:18:34	ga_ls9c_ard_3-2-1_090079_2022-01-29_final.stac-item
2022-01-30 10:57:27	ga_ls9c_ard_3-2-1_106079_2022-01-30_final.stac-item
2022-02-08 09:12:22	ga_ls9c_ard_3-2-1_089079_2022-02-07_final.stac-item
2022-02-24 09:12:13	ga_ls9c_ard_3-2-1_089079_2022-02-23_final.stac-item
2022-03-01 09:30:41	ga_ls9c_ard_3-2-1_092079_2022-03-01_final.stac-item
2022-04-13 09:11:59	ga_ls9c_ard_3-2-1_089079_2022-04-12_final.stac-item
2022-05-31 09:11:38	ga_ls9c_ard_3-2-1_089079_2022-05-30_final.stac-item
2022-06-07 09:17:50	ga_ls9c_ard_3-2-1_090079_2022-06-06_final.stac-item
2022-06-12 09:36:25	ga_ls9c_ard_3-2-1_093079_2022-06-12_final.stac-item
2022-06-16 09:11:45	ga_ls9c_ard_3-2-1_089079_2022-06-15_final.stac-item
2022-06-21 09:30:25	ga_ls9c_ard_3-2-1_092079_2022-06-21_final.stac-item
2022-06-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2022-06-22_final.stac-item
2022-06-28 09:36:43	ga_ls9c_ard_3-2-1_093079_2022-06-28_final.stac-item
2022-07-02 09:11:59	ga_ls9c_ard_3-2-1_089079_2022-07-01_final.stac-item
2022-07-05 11:21:46	ga_ls9c_ard_3-2-1_110079_2022-07-05_final.stac-item
2022-07-09 09:18:08	ga_ls9c_ard_3-2-1_090079_2022-07-08_final.stac-item
2022-07-09 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-07-09_final.stac-item
2022-07-18 09:11:58	ga_ls9c_ard_3-2-1_089079_2022-07-17_final.stac-item
2022-07-23 09:30:36	ga_ls9c_ard_3-2-1_092079_2022-07-23_final.stac-item
2022-07-25 09:18:16	ga_ls9c_ard_3-2-1_090079_2022-07-24_final.stac-item
2022-08-01 11:03:25	ga_ls9c_ard_3-2-1_107079_2022-08-01_final.stac-item
2022-08-03 09:12:12	ga_ls9c_ard_3-2-1_089079_2022-08-02_final.stac-item
2022-08-10 09:18:27	ga_ls9c_ard_3-2-1_090079_2022-08-09_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-08-13 11:28:16	ga_ls9c_ard_3-2-1_111079_2022-08-13_final.stac-item
2022-08-15 09:37:02	ga_ls9c_ard_3-2-1_093079_2022-08-15_final.stac-item
2022-08-19 09:12:20	ga_ls9c_ard_3-2-1_089079_2022-08-18_final.stac-item
2022-08-22 11:22:08	ga_ls9c_ard_3-2-1_110079_2022-08-22_final.stac-item
2022-08-26 09:18:32	ga_ls9c_ard_3-2-1_090079_2022-08-25_final.stac-item
2022-08-29 11:28:19	ga_ls9c_ard_3-2-1_111079_2022-08-29_final.stac-item
2022-08-31 09:37:04	ga_ls9c_ard_3-2-1_093079_2022-08-31_final.stac-item
2022-09-02 11:03:36	ga_ls9c_ard_3-2-1_107079_2022-09-02_final.stac-item
2022-09-04 09:12:21	ga_ls9c_ard_3-2-1_089079_2022-09-03_final.stac-item
2022-09-07 11:22:07	ga_ls9c_ard_3-2-1_110079_2022-09-07_final.stac-item
2022-09-11 09:18:32	ga_ls9c_ard_3-2-1_090079_2022-09-10_final.stac-item
2022-09-20 09:12:27	ga_ls9c_ard_3-2-1_089079_2022-09-19_final.stac-item
2022-10-02 09:37:12	ga_ls9c_ard_3-2-1_093079_2022-10-02_final.stac-item
2022-10-06 09:12:28	ga_ls9c_ard_3-2-1_089079_2022-10-05_final.stac-item
2022-10-13 09:18:43	ga_ls9c_ard_3-2-1_090079_2022-10-12_final.stac-item
2022-10-16 11:28:31	ga_ls9c_ard_3-2-1_111079_2022-10-16_final.stac-item
2022-10-20 11:03:49	ga_ls9c_ard_3-2-1_107079_2022-10-20_final.stac-item
2022-10-22 09:12:34	ga_ls9c_ard_3-2-1_089079_2022-10-21_final.stac-item
2022-11-03 09:37:14	ga_ls9c_ard_3-2-1_093079_2022-11-03_final.stac-item
2022-11-07 09:12:33	ga_ls9c_ard_3-2-1_089079_2022-11-06_final.stac-item
2022-11-17 11:28:33	ga_ls9c_ard_3-2-1_111079_2022-11-17_final.stac-item
2022-11-19 11:16:11	ga_ls9c_ard_3-2-1_109079_2022-11-19_final.stac-item
2022-12-05 09:37:16	ga_ls9c_ard_3-2-1_093079_2022-12-05_final.stac-item
2022-12-16 09:18:44	ga_ls9c_ard_3-2-1_090079_2022-12-15_final.stac-item
2023-01-10 09:12:33	ga_ls9c_ard_3-2-1_089079_2023-01-09_final.stac-item
2023-01-29 11:22:20	ga_ls9c_ard_3-2-1_110079_2023-01-29_final.stac-item
2023-02-09 11:03:52	ga_ls9c_ard_3-2-1_107079_2023-02-09_final.stac-item
2023-06-03 09:11:35	ga_ls9c_ard_3-2-1_089079_2023-06-02_final.stac-item
2023-06-19 09:11:26	ga_ls9c_ard_3-2-1_089079_2023-06-18_final.stac-item
2023-06-26 09:17:37	ga_ls9c_ard_3-2-1_090079_2023-06-25_final.stac-item
2023-06-26 10:56:30	ga_ls9c_ard_3-2-1_106079_2023-06-26_final.stac-item
2023-06-29 11:27:30	ga_ls9c_ard_3-2-1_111079_2023-06-29_final.stac-item
2023-07-03 11:02:52	ga_ls9c_ard_3-2-1_107079_2023-07-03_final.stac-item
2023-07-05 09:11:38	ga_ls9c_ard_3-2-1_089079_2023-07-04_final.stac-item
2023-07-08 11:21:28	ga_ls9c_ard_3-2-1_110079_2023-07-08_final.stac-item
2023-07-12 09:17:53	ga_ls9c_ard_3-2-1_090079_2023-07-11_final.stac-item
2023-07-12 10:56:46	ga_ls9c_ard_3-2-1_106079_2023-07-12_final.stac-item
2023-07-15 11:27:41	ga_ls9c_ard_3-2-1_111079_2023-07-15_final.stac-item
2023-07-19 11:02:58	ga_ls9c_ard_3-2-1_107079_2023-07-19_final.stac-item
2023-07-21 09:11:43	ga_ls9c_ard_3-2-1_089079_2023-07-20_final.stac-item
2023-07-24 11:21:29	ga_ls9c_ard_3-2-1_110079_2023-07-24_final.stac-item
2023-07-26 09:30:15	ga_ls9c_ard_3-2-1_092079_2023-07-26_final.stac-item
2023-07-28 09:17:56	ga_ls9c_ard_3-2-1_090079_2023-07-27_final.stac-item
2023-07-28 10:56:49	ga_ls9c_ard_3-2-1_106079_2023-07-28_final.stac-item
2023-07-31 11:27:46	ga_ls9c_ard_3-2-1_111079_2023-07-31_final.stac-item
2023-08-06 09:11:52	ga_ls9c_ard_3-2-1_089079_2023-08-05_final.stac-item
2023-08-09 11:21:40	ga_ls9c_ard_3-2-1_110079_2023-08-09_final.stac-item
2023-08-13 09:18:04	ga_ls9c_ard_3-2-1_090079_2023-08-12_final.stac-item
2023-08-13 10:56:57	ga_ls9c_ard_3-2-1_106079_2023-08-13_final.stac-item
2023-08-16 11:27:51	ga_ls9c_ard_3-2-1_111079_2023-08-16_final.stac-item
2023-08-20 11:03:10	ga_ls9c_ard_3-2-1_107079_2023-08-20_final.stac-item
2023-08-22 09:11:57	ga_ls9c_ard_3-2-1_089079_2023-08-21_final.stac-item
2023-08-29 10:57:06	ga_ls9c_ard_3-2-1_106079_2023-08-29_final.stac-item
2023-09-07 09:12:08	ga_ls9c_ard_3-2-1_089079_2023-09-06_final.stac-item
2023-09-14 09:18:22	ga_ls9c_ard_3-2-1_090079_2023-09-13_final.stac-item
2023-09-23 09:12:10	ga_ls9c_ard_3-2-1_089079_2023-09-22_final.stac-item
2023-09-30 09:18:20	ga_ls9c_ard_3-2-1_090079_2023-09-29_final.stac-item
2023-10-09 09:12:15	ga_ls9c_ard_3-2-1_089079_2023-10-08_final.stac-item
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-11-10 09:12:18	ga_ls9c_ard_3-2-1_089079_2023-11-09_final.stac-item
2024-03-01 09:12:16	ga_ls9c_ard_3-2-1_089079_2024-02-29_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