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 09:54:34	ga_ls9c_ard_3-2-1_096074_2021-11-03_final.stac-item
2021-11-05 09:35:49	ga_ls9c_ard_3-2-1_093074_2021-11-05_final.stac-item
2021-11-10 09:38:18	ga_ls9c_ard_3-2-1_094074_2021-11-10_final.stac-item
2021-12-05 10:06:09	ga_ls9c_ard_3-2-1_098074_2021-12-05_final.stac-item
2021-12-09 09:41:23	ga_ls9c_ard_3-2-1_094074_2021-12-09_final.stac-item
2021-12-11 11:07:53	ga_ls9c_ard_3-2-1_108074_2021-12-11_final.stac-item
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-18 11:14:00	ga_ls9c_ard_3-2-1_109074_2021-12-18_final.stac-item
2021-12-25 11:20:12	ga_ls9c_ard_3-2-1_110074_2021-12-25_final.stac-item
2021-12-27 11:07:50	ga_ls9c_ard_3-2-1_108074_2021-12-27_final.stac-item
2021-12-30 09:59:51	ga_ls9c_ard_3-2-1_097074_2021-12-30_final.stac-item
2022-01-01 09:47:29	ga_ls9c_ard_3-2-1_095074_2022-01-01_final.stac-item
2022-01-12 11:07:47	ga_ls9c_ard_3-2-1_108074_2022-01-12_final.stac-item
2022-05-30 10:05:16	ga_ls9c_ard_3-2-1_098074_2022-05-30_final.stac-item
2022-06-03 09:40:33	ga_ls9c_ard_3-2-1_094074_2022-06-03_final.stac-item
2022-06-05 11:07:05	ga_ls9c_ard_3-2-1_108074_2022-06-05_final.stac-item
2022-06-10 09:46:45	ga_ls9c_ard_3-2-1_095074_2022-06-10_final.stac-item
2022-06-12 09:34:25	ga_ls9c_ard_3-2-1_093074_2022-06-12_final.stac-item
2022-06-17 09:53:01	ga_ls9c_ard_3-2-1_096074_2022-06-17_final.stac-item
2022-06-19 09:40:43	ga_ls9c_ard_3-2-1_094074_2022-06-19_final.stac-item
2022-06-26 09:47:05	ga_ls9c_ard_3-2-1_095074_2022-06-26_final.stac-item
2022-06-30 09:22:21	ga_ls9c_ard_3-2-1_091074_2022-06-29_final.stac-item
2022-07-09 10:55:01	ga_ls9c_ard_3-2-1_106074_2022-07-09_final.stac-item
2022-07-10 09:59:23	ga_ls9c_ard_3-2-1_097074_2022-07-10_final.stac-item
2022-07-14 11:13:31	ga_ls9c_ard_3-2-1_109074_2022-07-14_final.stac-item
2022-07-16 09:22:18	ga_ls9c_ard_3-2-1_091074_2022-07-15_final.stac-item
2022-07-28 09:47:13	ga_ls9c_ard_3-2-1_095074_2022-07-28_final.stac-item
2022-07-30 09:34:53	ga_ls9c_ard_3-2-1_093074_2022-07-30_final.stac-item
2022-08-02 10:05:49	ga_ls9c_ard_3-2-1_098074_2022-08-02_final.stac-item
2022-08-04 09:53:29	ga_ls9c_ard_3-2-1_096074_2022-08-04_final.stac-item
2022-08-11 09:59:44	ga_ls9c_ard_3-2-1_097074_2022-08-11_final.stac-item
2022-08-13 09:47:23	ga_ls9c_ard_3-2-1_095074_2022-08-13_final.stac-item
2022-08-15 09:35:02	ga_ls9c_ard_3-2-1_093074_2022-08-15_final.stac-item
2022-08-17 09:22:41	ga_ls9c_ard_3-2-1_091074_2022-08-16_final.stac-item
2022-08-17 11:01:34	ga_ls9c_ard_3-2-1_107074_2022-08-17_final.stac-item
2022-08-20 09:53:36	ga_ls9c_ard_3-2-1_096074_2022-08-20_final.stac-item
2022-08-22 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-08-22_final.stac-item
2022-09-12 09:59:49	ga_ls9c_ard_3-2-1_097074_2022-09-12_final.stac-item
2022-09-18 09:22:48	ga_ls9c_ard_3-2-1_091074_2022-09-17_final.stac-item
2022-09-19 10:06:04	ga_ls9c_ard_3-2-1_098074_2022-09-19_final.stac-item
2022-09-23 09:41:22	ga_ls9c_ard_3-2-1_094074_2022-09-23_final.stac-item
2022-09-23 11:20:15	ga_ls9c_ard_3-2-1_110074_2022-09-23_final.stac-item
2022-09-25 11:07:54	ga_ls9c_ard_3-2-1_108074_2022-09-25_final.stac-item
2022-10-02 09:35:12	ga_ls9c_ard_3-2-1_093074_2022-10-02_final.stac-item
2022-10-04 09:22:50	ga_ls9c_ard_3-2-1_091074_2022-10-03_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-11 11:07:57	ga_ls9c_ard_3-2-1_108074_2022-10-11_final.stac-item
2022-10-14 09:59:59	ga_ls9c_ard_3-2-1_097074_2022-10-14_final.stac-item
2022-10-16 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-10-16_final.stac-item
2022-10-21 10:06:12	ga_ls9c_ard_3-2-1_098074_2022-10-21_final.stac-item
2022-10-25 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-10-25_final.stac-item
2022-11-05 09:22:54	ga_ls9c_ard_3-2-1_091074_2022-11-04_final.stac-item
2022-11-17 09:47:40	ga_ls9c_ard_3-2-1_095074_2022-11-17_final.stac-item
2022-11-19 11:14:12	ga_ls9c_ard_3-2-1_109074_2022-11-19_final.stac-item
2022-11-22 10:06:12	ga_ls9c_ard_3-2-1_098074_2022-11-22_final.stac-item
2022-12-14 11:08:00	ga_ls9c_ard_3-2-1_108074_2022-12-14_final.stac-item
2022-12-19 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-12-19_final.stac-item
2022-12-21 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-12-21_final.stac-item
2023-01-06 11:14:11	ga_ls9c_ard_3-2-1_109074_2023-01-06_final.stac-item
2023-01-08 09:22:56	ga_ls9c_ard_3-2-1_091074_2023-01-07_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-13 11:20:19	ga_ls9c_ard_3-2-1_110074_2023-01-13_final.stac-item
2023-02-23 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-02-23_final.stac-item
2023-02-26 10:06:01	ga_ls9c_ard_3-2-1_098074_2023-02-26_final.stac-item
2023-06-18 10:05:04	ga_ls9c_ard_3-2-1_098074_2023-06-18_final.stac-item
2023-06-19 10:48:20	ga_ls9c_ard_3-2-1_105074_2023-06-19_final.stac-item
2023-06-20 09:52:42	ga_ls9c_ard_3-2-1_096074_2023-06-20_final.stac-item
2023-06-26 10:54:30	ga_ls9c_ard_3-2-1_106074_2023-06-26_final.stac-item
2023-06-27 09:58:55	ga_ls9c_ard_3-2-1_097074_2023-06-27_final.stac-item
2023-06-29 09:46:37	ga_ls9c_ard_3-2-1_095074_2023-06-29_final.stac-item
2023-07-03 09:21:59	ga_ls9c_ard_3-2-1_091074_2023-07-02_final.stac-item
2023-07-04 10:05:15	ga_ls9c_ard_3-2-1_098074_2023-07-04_final.stac-item
2023-07-05 10:48:32	ga_ls9c_ard_3-2-1_105074_2023-07-05_final.stac-item
2023-07-06 09:52:55	ga_ls9c_ard_3-2-1_096074_2023-07-06_final.stac-item
2023-07-08 09:40:35	ga_ls9c_ard_3-2-1_094074_2023-07-08_final.stac-item
2023-07-13 09:59:09	ga_ls9c_ard_3-2-1_097074_2023-07-13_final.stac-item
2023-07-31 09:46:53	ga_ls9c_ard_3-2-1_095074_2023-07-31_final.stac-item
2023-08-05 10:05:29	ga_ls9c_ard_3-2-1_098074_2023-08-05_final.stac-item
2023-08-18 09:34:36	ga_ls9c_ard_3-2-1_093074_2023-08-18_final.stac-item
2023-08-21 10:05:34	ga_ls9c_ard_3-2-1_098074_2023-08-21_final.stac-item
2023-08-25 09:40:54	ga_ls9c_ard_3-2-1_094074_2023-08-25_final.stac-item
2023-08-30 09:59:30	ga_ls9c_ard_3-2-1_097074_2023-08-30_final.stac-item
2023-09-03 09:34:48	ga_ls9c_ard_3-2-1_093074_2023-09-03_final.stac-item
2023-09-06 10:05:44	ga_ls9c_ard_3-2-1_098074_2023-09-06_final.stac-item
2023-09-08 09:53:24	ga_ls9c_ard_3-2-1_096074_2023-09-08_final.stac-item
2023-09-10 09:41:04	ga_ls9c_ard_3-2-1_094074_2023-09-10_final.stac-item
2023-09-15 09:59:38	ga_ls9c_ard_3-2-1_097074_2023-09-15_final.stac-item
2023-09-19 09:34:55	ga_ls9c_ard_3-2-1_093074_2023-09-19_final.stac-item
2023-10-05 09:34:57	ga_ls9c_ard_3-2-1_093074_2023-10-05_final.stac-item
2023-10-12 09:41:13	ga_ls9c_ard_3-2-1_094074_2023-10-12_final.stac-item
2023-10-21 09:35:05	ga_ls9c_ard_3-2-1_093074_2023-10-21_final.stac-item
2023-10-28 09:41:14	ga_ls9c_ard_3-2-1_094074_2023-10-28_final.stac-item
2023-11-06 09:35:00	ga_ls9c_ard_3-2-1_093074_2023-11-06_final.stac-item
2023-11-29 09:41:20	ga_ls9c_ard_3-2-1_094074_2023-11-29_final.stac-item
2023-12-08 09:35:04	ga_ls9c_ard_3-2-1_093074_2023-12-08_final.stac-item
2023-12-15 09:41:20	ga_ls9c_ard_3-2-1_094074_2023-12-15_final.stac-item
2023-12-24 09:35:11	ga_ls9c_ard_3-2-1_093074_2023-12-24_final.stac-item
2024-01-25 09:35:03	ga_ls9c_ard_3-2-1_093074_2024-01-25_final.stac-item
2024-01-25 09:35:03	ga_ls9c_ard_3-2-1_093074_2024-01-25_nrt.stac-item
2024-02-01 09:41:19	ga_ls9c_ard_3-2-1_094074_2024-02-01_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years