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
2021-12-04 09:22:30	ga_ls9c_ard_3-2-1_091073_2021-12-03_final.stac-item
2021-12-08 10:36:37	ga_ls9c_ard_3-2-1_103073_2021-12-08_final.stac-item
2021-12-10 10:24:14	ga_ls9c_ard_3-2-1_101073_2021-12-10_final.stac-item
2021-12-24 10:36:32	ga_ls9c_ard_3-2-1_103073_2021-12-24_final.stac-item
2021-12-26 10:24:10	ga_ls9c_ard_3-2-1_101073_2021-12-26_final.stac-item
2022-01-02 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-01-02_final.stac-item
2022-01-05 09:22:21	ga_ls9c_ard_3-2-1_091073_2022-01-04_final.stac-item
2022-01-21 09:22:21	ga_ls9c_ard_3-2-1_091073_2022-01-20_final.stac-item
2022-01-25 10:36:31	ga_ls9c_ard_3-2-1_103073_2022-01-25_final.stac-item
2022-02-06 09:22:20	ga_ls9c_ard_3-2-1_091073_2022-02-05_final.stac-item
2022-02-10 10:36:29	ga_ls9c_ard_3-2-1_103073_2022-02-10_final.stac-item
2022-02-19 10:30:13	ga_ls9c_ard_3-2-1_102073_2022-02-19_final.stac-item
2022-03-30 10:36:11	ga_ls9c_ard_3-2-1_103073_2022-03-30_final.stac-item
2022-04-02 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-04-02_final.stac-item
2022-04-13 10:48:29	ga_ls9c_ard_3-2-1_105073_2022-04-13_final.stac-item
2022-04-27 09:21:50	ga_ls9c_ard_3-2-1_091073_2022-04-26_final.stac-item
2022-05-11 11:12:58	ga_ls9c_ard_3-2-1_109073_2022-05-11_final.stac-item
2022-05-13 09:21:42	ga_ls9c_ard_3-2-1_091073_2022-05-12_final.stac-item
2022-05-15 10:48:12	ga_ls9c_ard_3-2-1_105073_2022-05-15_final.stac-item
2022-05-29 09:21:36	ga_ls9c_ard_3-2-1_091073_2022-05-28_final.stac-item
2022-06-02 10:35:46	ga_ls9c_ard_3-2-1_103073_2022-06-02_final.stac-item
2022-06-14 09:21:41	ga_ls9c_ard_3-2-1_091073_2022-06-13_final.stac-item
2022-06-18 10:35:54	ga_ls9c_ard_3-2-1_103073_2022-06-18_final.stac-item
2022-06-22 10:11:19	ga_ls9c_ard_3-2-1_099073_2022-06-22_final.stac-item
2022-06-30 09:21:58	ga_ls9c_ard_3-2-1_091073_2022-06-29_final.stac-item
2022-07-16 09:21:54	ga_ls9c_ard_3-2-1_091073_2022-07-15_final.stac-item
2022-07-24 10:11:29	ga_ls9c_ard_3-2-1_099073_2022-07-24_final.stac-item
2022-08-01 09:22:09	ga_ls9c_ard_3-2-1_091073_2022-07-31_final.stac-item
2022-08-05 10:36:21	ga_ls9c_ard_3-2-1_103073_2022-08-05_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 10:11:40	ga_ls9c_ard_3-2-1_099073_2022-08-09_final.stac-item
2022-08-17 09:22:17	ga_ls9c_ard_3-2-1_091073_2022-08-16_final.stac-item
2022-08-21 10:36:28	ga_ls9c_ard_3-2-1_103073_2022-08-21_final.stac-item
2022-08-23 10:24:07	ga_ls9c_ard_3-2-1_101073_2022-08-23_final.stac-item
2022-08-30 10:30:18	ga_ls9c_ard_3-2-1_102073_2022-08-30_final.stac-item
2022-09-02 09:22:19	ga_ls9c_ard_3-2-1_091073_2022-09-01_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-18 09:22:24	ga_ls9c_ard_3-2-1_091073_2022-09-17_final.stac-item
2022-09-26 10:11:53	ga_ls9c_ard_3-2-1_099073_2022-09-26_final.stac-item
2022-10-01 10:30:25	ga_ls9c_ard_3-2-1_102073_2022-10-01_final.stac-item
2022-10-03 10:18:04	ga_ls9c_ard_3-2-1_100073_2022-10-03_final.stac-item
2022-10-04 09:22:26	ga_ls9c_ard_3-2-1_091073_2022-10-03_final.stac-item
2022-10-08 10:36:36	ga_ls9c_ard_3-2-1_103073_2022-10-08_final.stac-item
2022-10-10 10:24:16	ga_ls9c_ard_3-2-1_101073_2022-10-10_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 09:22:32	ga_ls9c_ard_3-2-1_091073_2022-10-19_final.stac-item
2022-10-24 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-10-24_final.stac-item
2022-11-02 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-11-02_final.stac-item
2022-11-04 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-11-04_final.stac-item
2022-11-05 09:22:30	ga_ls9c_ard_3-2-1_091073_2022-11-04_interim.stac-item
2022-11-13 10:11:59	ga_ls9c_ard_3-2-1_099073_2022-11-13_final.stac-item
2022-11-18 10:30:32	ga_ls9c_ard_3-2-1_102073_2022-11-18_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-11-25 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-11-25_final.stac-item
2022-12-04 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-04_final.stac-item
2022-12-06 10:18:08	ga_ls9c_ard_3-2-1_100073_2022-12-06_nrt.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_nrt.stac-item
2022-12-11 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-12-11_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-29 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-12-29_final.stac-item
2023-01-05 10:30:31	ga_ls9c_ard_3-2-1_102073_2023-01-05_final.stac-item
2023-01-08 09:22:32	ga_ls9c_ard_3-2-1_091073_2023-01-07_final.stac-item
2023-01-12 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-12_final.stac-item
2023-02-01 10:11:59	ga_ls9c_ard_3-2-1_099073_2023-02-01_final.stac-item
2023-02-06 10:30:34	ga_ls9c_ard_3-2-1_102073_2023-02-06_final.stac-item
2023-02-09 09:22:36	ga_ls9c_ard_3-2-1_091073_2023-02-08_final.stac-item
2023-03-01 10:36:30	ga_ls9c_ard_3-2-1_103073_2023-03-01_final.stac-item
2023-03-17 10:36:23	ga_ls9c_ard_3-2-1_103073_2023-03-17_final.stac-item
2023-03-19 10:24:01	ga_ls9c_ard_3-2-1_101073_2023-03-19_final.stac-item
2023-03-29 09:22:02	ga_ls9c_ard_3-2-1_091073_2023-03-28_final.stac-item
2023-04-13 10:17:34	ga_ls9c_ard_3-2-1_100073_2023-04-13_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-04-18 10:36:06	ga_ls9c_ard_3-2-1_103073_2023-04-18_final.stac-item
2023-04-22 10:11:22	ga_ls9c_ard_3-2-1_099073_2023-04-22_final.stac-item
2023-06-01 09:21:33	ga_ls9c_ard_3-2-1_091073_2023-05-31_final.stac-item
2023-06-17 09:21:24	ga_ls9c_ard_3-2-1_091073_2023-06-16_final.stac-item
2023-07-03 09:21:35	ga_ls9c_ard_3-2-1_091073_2023-07-02_final.stac-item
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-07-17 09:34:03	ga_ls9c_ard_3-2-1_093073_2023-07-17_final.stac-item
2023-08-09 09:40:23	ga_ls9c_ard_3-2-1_094073_2023-08-09_final.stac-item
2023-08-11 09:28:02	ga_ls9c_ard_3-2-1_092073_2023-08-10_final.stac-item
2023-08-25 09:40:30	ga_ls9c_ard_3-2-1_094073_2023-08-25_final.stac-item
2023-08-27 09:28:10	ga_ls9c_ard_3-2-1_092073_2023-08-26_final.stac-item
2023-09-03 09:34:24	ga_ls9c_ard_3-2-1_093073_2023-09-03_final.stac-item
2023-09-05 09:22:04	ga_ls9c_ard_3-2-1_091073_2023-09-04_final.stac-item
2023-09-21 09:22:09	ga_ls9c_ard_3-2-1_091073_2023-09-20_final.stac-item
2023-10-23 09:22:19	ga_ls9c_ard_3-2-1_091073_2023-10-22_final.stac-item
2023-11-08 09:22:15	ga_ls9c_ard_3-2-1_091073_2023-11-07_final.stac-item
2023-11-24 09:22:22	ga_ls9c_ard_3-2-1_091073_2023-11-23_final.stac-item
2024-01-11 09:22:21	ga_ls9c_ard_3-2-1_091073_2024-01-10_final.stac-item
2024-01-27 09:22:20	ga_ls9c_ard_3-2-1_091073_2024-01-26_final.stac-item
2024-02-10 09:34:45	ga_ls9c_ard_3-2-1_093073_2024-02-10_final.stac-item
2024-02-12 09:22:22	ga_ls9c_ard_3-2-1_091073_2024-02-11_final.stac-item
2024-02-17 09:40:50	ga_ls9c_ard_3-2-1_094073_2024-02-17_final.stac-item
2024-02-28 09:22:13	ga_ls9c_ard_3-2-1_091073_2024-02-27_final.stac-item
2024-03-15 11:01:07	ga_ls9c_ard_3-2-1_107073_2024-03-15_final.stac-item
2024-03-29 09:34:27	ga_ls9c_ard_3-2-1_093073_2024-03-29_final.stac-item
2024-04-05 09:40:37	ga_ls9c_ard_3-2-1_094073_2024-04-05_final.stac-item
2024-04-07 09:28:15	ga_ls9c_ard_3-2-1_092073_2024-04-06_interim.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