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 09:53:22	ga_ls9c_ard_3-2-1_096071_2021-11-03_final.stac-item
2021-11-12 10:57:01	ga_ls9c_ard_3-2-1_106071_2021-11-12_final.stac-item
2021-11-16 10:19:31	ga_ls9c_ard_3-2-1_100071_2021-11-16_final.stac-item
2021-12-07 09:52:34	ga_ls9c_ard_3-2-1_096071_2021-12-07_final.stac-item
2021-12-08 10:35:49	ga_ls9c_ard_3-2-1_103071_2021-12-08_final.stac-item
2021-12-14 09:58:40	ga_ls9c_ard_3-2-1_097071_2021-12-14_final.stac-item
2021-12-17 10:29:32	ga_ls9c_ard_3-2-1_102071_2021-12-17_final.stac-item
2021-12-20 11:00:27	ga_ls9c_ard_3-2-1_107071_2021-12-20_final.stac-item
2022-01-02 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-01-02_final.stac-item
2022-01-05 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-01-05_final.stac-item
2022-01-08 09:52:27	ga_ls9c_ard_3-2-1_096071_2022-01-08_final.stac-item
2022-01-12 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-01-12_final.stac-item
2022-01-19 11:12:47	ga_ls9c_ard_3-2-1_109071_2022-01-19_final.stac-item
2022-01-23 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-23_final.stac-item
2022-01-28 11:06:37	ga_ls9c_ard_3-2-1_108071_2022-01-28_final.stac-item
2022-02-08 10:48:03	ga_ls9c_ard_3-2-1_105071_2022-02-08_final.stac-item
2022-02-11 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-02-11_final.stac-item
2022-02-19 10:29:25	ga_ls9c_ard_3-2-1_102071_2022-02-19_final.stac-item
2022-02-24 10:47:54	ga_ls9c_ard_3-2-1_105071_2022-02-24_final.stac-item
2022-02-27 11:18:46	ga_ls9c_ard_3-2-1_110071_2022-02-27_final.stac-item
2022-03-04 09:58:23	ga_ls9c_ard_3-2-1_097071_2022-03-04_final.stac-item
2022-03-28 10:47:45	ga_ls9c_ard_3-2-1_105071_2022-03-28_final.stac-item
2022-03-29 09:52:08	ga_ls9c_ard_3-2-1_096071_2022-03-29_final.stac-item
2022-04-22 10:41:23	ga_ls9c_ard_3-2-1_104071_2022-04-22_final.stac-item
2022-05-03 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-05-03_final.stac-item
2022-05-07 09:58:03	ga_ls9c_ard_3-2-1_097071_2022-05-07_final.stac-item
2022-05-10 10:28:56	ga_ls9c_ard_3-2-1_102071_2022-05-10_final.stac-item
2022-05-23 09:57:52	ga_ls9c_ard_3-2-1_097071_2022-05-23_final.stac-item
2022-06-01 09:51:43	ga_ls9c_ard_3-2-1_096071_2022-06-01_final.stac-item
2022-06-08 09:57:54	ga_ls9c_ard_3-2-1_097071_2022-06-08_final.stac-item
2022-06-11 10:28:50	ga_ls9c_ard_3-2-1_102071_2022-06-11_final.stac-item
2022-06-20 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-06-20_final.stac-item
2022-06-21 11:06:07	ga_ls9c_ard_3-2-1_108071_2022-06-21_final.stac-item
2022-07-03 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-03_final.stac-item
2022-07-06 10:22:56	ga_ls9c_ard_3-2-1_101071_2022-07-06_final.stac-item
2022-07-10 09:58:12	ga_ls9c_ard_3-2-1_097071_2022-07-10_final.stac-item
2022-07-19 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-19_final.stac-item
2022-07-21 11:18:37	ga_ls9c_ard_3-2-1_110071_2022-07-21_final.stac-item
2022-07-26 09:58:21	ga_ls9c_ard_3-2-1_097071_2022-07-26_final.stac-item
2022-08-04 09:52:17	ga_ls9c_ard_3-2-1_096071_2022-08-04_final.stac-item
2022-08-12 10:41:48	ga_ls9c_ard_3-2-1_104071_2022-08-12_final.stac-item
2022-08-14 10:29:27	ga_ls9c_ard_3-2-1_102071_2022-08-14_final.stac-item
2022-08-15 11:12:43	ga_ls9c_ard_3-2-1_109071_2022-08-15_final.stac-item
2022-08-19 10:48:01	ga_ls9c_ard_3-2-1_105071_2022-08-19_final.stac-item
2022-08-20 09:52:24	ga_ls9c_ard_3-2-1_096071_2022-08-20_final.stac-item
2022-08-21 10:35:40	ga_ls9c_ard_3-2-1_103071_2022-08-21_final.stac-item
2022-08-27 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-08-27_final.stac-item
2022-09-05 09:52:25	ga_ls9c_ard_3-2-1_096071_2022-09-05_final.stac-item
2022-09-09 11:06:34	ga_ls9c_ard_3-2-1_108071_2022-09-09_final.stac-item
2022-09-15 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-09-15_final.stac-item
2022-09-16 11:12:50	ga_ls9c_ard_3-2-1_109071_2022-09-16_final.stac-item
2022-09-18 11:00:29	ga_ls9c_ard_3-2-1_107071_2022-09-18_final.stac-item
2022-09-28 09:58:43	ga_ls9c_ard_3-2-1_097071_2022-09-28_final.stac-item
2022-10-01 10:29:38	ga_ls9c_ard_3-2-1_102071_2022-10-01_final.stac-item
2022-10-04 11:00:31	ga_ls9c_ard_3-2-1_107071_2022-10-04_final.stac-item
2022-10-07 09:52:32	ga_ls9c_ard_3-2-1_096071_2022-10-07_final.stac-item
2022-10-11 11:06:45	ga_ls9c_ard_3-2-1_108071_2022-10-11_final.stac-item
2022-10-14 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-10-14_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-10-18 11:12:59	ga_ls9c_ard_3-2-1_109071_2022-10-18_final.stac-item
2022-10-20 11:00:37	ga_ls9c_ard_3-2-1_107071_2022-10-20_final.stac-item
2022-10-25 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-10-25_final.stac-item
2022-10-30 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-10-30_final.stac-item
2022-10-31 10:42:03	ga_ls9c_ard_3-2-1_104071_2022-10-31_final.stac-item
2022-11-12 11:06:49	ga_ls9c_ard_3-2-1_108071_2022-11-12_final.stac-item
2022-11-19 11:13:00	ga_ls9c_ard_3-2-1_109071_2022-11-19_final.stac-item
2022-11-26 11:19:09	ga_ls9c_ard_3-2-1_110071_2022-11-26_final.stac-item
2022-12-07 11:00:36	ga_ls9c_ard_3-2-1_107071_2022-12-07_nrt.stac-item
2022-12-10 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-12-10_final.stac-item
2022-12-14 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-12-14_final.stac-item
2022-12-21 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-12-21_final.stac-item
2022-12-26 09:52:36	ga_ls9c_ard_3-2-1_096071_2022-12-26_final.stac-item
2023-01-06 11:12:59	ga_ls9c_ard_3-2-1_109071_2023-01-06_final.stac-item
2023-01-08 11:00:37	ga_ls9c_ard_3-2-1_107071_2023-01-08_final.stac-item
2023-01-15 11:06:44	ga_ls9c_ard_3-2-1_108071_2023-01-15_final.stac-item
2023-01-18 09:58:42	ga_ls9c_ard_3-2-1_097071_2023-01-18_final.stac-item
2023-02-11 10:48:19	ga_ls9c_ard_3-2-1_105071_2023-02-11_final.stac-item
2023-02-12 09:52:41	ga_ls9c_ard_3-2-1_096071_2023-02-12_final.stac-item
2023-02-16 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-02-16_final.stac-item
2023-03-18 11:18:51	ga_ls9c_ard_3-2-1_110071_2023-03-18_final.stac-item
2023-03-22 10:54:05	ga_ls9c_ard_3-2-1_106071_2023-03-22_final.stac-item
2023-03-23 09:58:27	ga_ls9c_ard_3-2-1_097071_2023-03-23_final.stac-item
2023-04-16 10:47:39	ga_ls9c_ard_3-2-1_105071_2023-04-16_final.stac-item
2023-04-19 11:18:34	ga_ls9c_ard_3-2-1_110071_2023-04-19_final.stac-item
2023-05-10 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-05-10_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-07-06 09:51:43	ga_ls9c_ard_3-2-1_096071_2023-07-06_final.stac-item
2023-07-12 10:53:35	ga_ls9c_ard_3-2-1_106071_2023-07-12_final.stac-item
2023-07-16 10:28:52	ga_ls9c_ard_3-2-1_102071_2023-07-16_final.stac-item
2023-07-21 10:47:24	ga_ls9c_ard_3-2-1_105071_2023-07-21_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-08-06 10:47:33	ga_ls9c_ard_3-2-1_105071_2023-08-06_final.stac-item
2023-08-13 10:53:46	ga_ls9c_ard_3-2-1_106071_2023-08-13_final.stac-item
2023-08-14 09:58:08	ga_ls9c_ard_3-2-1_097071_2023-08-14_final.stac-item
2023-08-23 09:52:02	ga_ls9c_ard_3-2-1_096071_2023-08-23_final.stac-item
2023-09-08 09:52:12	ga_ls9c_ard_3-2-1_096071_2023-09-08_final.stac-item
2023-09-15 09:58:27	ga_ls9c_ard_3-2-1_097071_2023-09-15_final.stac-item
2024-03-18 09:52:20	ga_ls9c_ard_3-2-1_096071_2024-03-18_final.stac-item
2024-04-03 09:52:11	ga_ls9c_ard_3-2-1_096071_2024-04-03_final.stac-item
2024-04-19 09:51:59	ga_ls9c_ard_3-2-1_096071_2024-04-19_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