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
2021-11-11 10:22:14	ga_ls9c_ard_3-2-1_100084_2021-11-11_final.stac-item
2021-11-16 10:24:42	ga_ls9c_ard_3-2-1_100084_2021-11-16_final.stac-item
2021-12-15 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-15_final.stac-item
2021-12-15 10:41:55	ga_ls9c_ard_3-2-1_104071_2021-12-15_final.stac-item
2021-12-31 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-31_final.stac-item
2021-12-31 10:41:07	ga_ls9c_ard_3-2-1_104069_2021-12-31_final.stac-item
2022-01-04 10:22:22	ga_ls9c_ard_3-2-1_100084_2022-01-04_final.stac-item
2022-01-07 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-01-07_final.stac-item
2022-01-16 10:40:40	ga_ls9c_ard_3-2-1_104068_2022-01-16_final.stac-item
2022-01-16 10:41:04	ga_ls9c_ard_3-2-1_104069_2022-01-16_final.stac-item
2022-01-16 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-01-16_final.stac-item
2022-01-20 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-01-20_final.stac-item
2022-01-25 10:37:43	ga_ls9c_ard_3-2-1_103076_2022-01-25_final.stac-item
2022-02-01 10:40:42	ga_ls9c_ard_3-2-1_104068_2022-02-01_final.stac-item
2022-02-01 10:41:06	ga_ls9c_ard_3-2-1_104069_2022-02-01_final.stac-item
2022-02-03 10:31:32	ga_ls9c_ard_3-2-1_102076_2022-02-03_final.stac-item
2022-02-05 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-02-05_final.stac-item
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final.stac-item
2022-02-17 10:40:37	ga_ls9c_ard_3-2-1_104068_2022-02-17_final.stac-item
2022-02-17 10:41:48	ga_ls9c_ard_3-2-1_104071_2022-02-17_final.stac-item
2022-03-05 10:40:51	ga_ls9c_ard_3-2-1_104069_2022-03-05_final.stac-item
2022-03-05 10:41:39	ga_ls9c_ard_3-2-1_104071_2022-03-05_final.stac-item
2022-03-09 10:22:07	ga_ls9c_ard_3-2-1_100084_2022-03-09_final.stac-item
2022-03-12 10:46:38	ga_ls9c_ard_3-2-1_105068_2022-03-12_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-21 10:41:37	ga_ls9c_ard_3-2-1_104071_2022-03-21_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-03-28 10:46:33	ga_ls9c_ard_3-2-1_105068_2022-03-28_final.stac-item
2022-04-06 10:40:22	ga_ls9c_ard_3-2-1_104068_2022-04-06_final.stac-item
2022-04-06 10:40:46	ga_ls9c_ard_3-2-1_104069_2022-04-06_final.stac-item
2022-04-06 10:41:33	ga_ls9c_ard_3-2-1_104071_2022-04-06_final.stac-item
2022-04-10 10:22:00	ga_ls9c_ard_3-2-1_100084_2022-04-10_final.stac-item
2022-04-15 10:37:17	ga_ls9c_ard_3-2-1_103076_2022-04-15_final.stac-item
2022-04-22 10:41:23	ga_ls9c_ard_3-2-1_104071_2022-04-22_final.stac-item
2022-05-10 10:30:55	ga_ls9c_ard_3-2-1_102076_2022-05-10_final.stac-item
2022-05-17 10:37:00	ga_ls9c_ard_3-2-1_103076_2022-05-17_final.stac-item
2022-05-24 10:39:56	ga_ls9c_ard_3-2-1_104068_2022-05-24_final.stac-item
2022-05-24 10:40:20	ga_ls9c_ard_3-2-1_104069_2022-05-24_final.stac-item
2022-05-31 10:46:08	ga_ls9c_ard_3-2-1_105068_2022-05-31_final.stac-item
2022-06-02 10:36:58	ga_ls9c_ard_3-2-1_103076_2022-06-02_final.stac-item
2022-06-09 10:40:22	ga_ls9c_ard_3-2-1_104069_2022-06-09_final.stac-item
2022-06-18 10:37:06	ga_ls9c_ard_3-2-1_103076_2022-06-18_final.stac-item
2022-06-25 10:40:19	ga_ls9c_ard_3-2-1_104068_2022-06-25_final.stac-item
2022-06-29 10:21:58	ga_ls9c_ard_3-2-1_100084_2022-06-29_final.stac-item
2022-07-02 10:46:29	ga_ls9c_ard_3-2-1_105068_2022-07-02_final.stac-item
2022-07-15 10:21:53	ga_ls9c_ard_3-2-1_100084_2022-07-15_final.stac-item
2022-08-12 10:40:36	ga_ls9c_ard_3-2-1_104068_2022-08-12_final.stac-item
2022-08-12 10:41:48	ga_ls9c_ard_3-2-1_104071_2022-08-12_final.stac-item
2022-08-16 10:22:18	ga_ls9c_ard_3-2-1_100084_2022-08-16_final.stac-item
2022-08-28 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-08-28_final.stac-item
2022-09-13 10:40:42	ga_ls9c_ard_3-2-1_104068_2022-09-13_final.stac-item
2022-09-17 10:22:24	ga_ls9c_ard_3-2-1_100084_2022-09-17_final.stac-item
2022-09-20 10:46:56	ga_ls9c_ard_3-2-1_105068_2022-09-20_final.stac-item
2022-10-03 10:22:27	ga_ls9c_ard_3-2-1_100084_2022-10-03_final.stac-item
2022-10-06 10:46:57	ga_ls9c_ard_3-2-1_105068_2022-10-06_final.stac-item
2022-10-15 10:41:16	ga_ls9c_ard_3-2-1_104069_2022-10-15_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-10-24 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-10-24_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-10-31 10:42:03	ga_ls9c_ard_3-2-1_104071_2022-10-31_final.stac-item
2022-11-16 10:42:06	ga_ls9c_ard_3-2-1_104071_2022-11-16_final.stac-item
2022-11-20 10:22:34	ga_ls9c_ard_3-2-1_100084_2022-11-20_final.stac-item
2022-12-02 10:40:50	ga_ls9c_ard_3-2-1_104068_2022-12-02_final.stac-item
2022-12-02 10:41:14	ga_ls9c_ard_3-2-1_104069_2022-12-02_final.stac-item
2022-12-09 10:47:03	ga_ls9c_ard_3-2-1_105068_2022-12-09_final.stac-item
2022-12-18 10:41:16	ga_ls9c_ard_3-2-1_104069_2022-12-18_final.stac-item
2022-12-22 10:22:30	ga_ls9c_ard_3-2-1_100084_2022-12-22_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2023-01-03 10:40:53	ga_ls9c_ard_3-2-1_104068_2023-01-03_final.stac-item
2023-01-07 10:22:33	ga_ls9c_ard_3-2-1_100084_2023-01-07_final.stac-item
2023-01-19 10:40:44	ga_ls9c_ard_3-2-1_104068_2023-01-19_final.stac-item
2023-01-19 10:41:08	ga_ls9c_ard_3-2-1_104069_2023-01-19_final.stac-item
2023-01-23 10:22:25	ga_ls9c_ard_3-2-1_100084_2023-01-23_final.stac-item
2023-02-04 10:41:19	ga_ls9c_ard_3-2-1_104069_2023-02-04_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-11 10:47:07	ga_ls9c_ard_3-2-1_105068_2023-02-11_final.stac-item
2023-02-20 10:40:47	ga_ls9c_ard_3-2-1_104068_2023-02-20_final.stac-item
2023-02-20 10:41:11	ga_ls9c_ard_3-2-1_104069_2023-02-20_final.stac-item
2023-02-20 10:41:59	ga_ls9c_ard_3-2-1_104071_2023-02-20_final.stac-item
2023-02-24 10:22:21	ga_ls9c_ard_3-2-1_100084_2023-02-24_final.stac-item
2023-03-08 10:40:36	ga_ls9c_ard_3-2-1_104068_2023-03-08_final.stac-item
2023-03-08 10:41:48	ga_ls9c_ard_3-2-1_104071_2023-03-08_final.stac-item
2023-03-24 10:40:30	ga_ls9c_ard_3-2-1_104068_2023-03-24_final.stac-item
2023-03-24 10:40:54	ga_ls9c_ard_3-2-1_104069_2023-03-24_final.stac-item
2023-03-28 10:22:05	ga_ls9c_ard_3-2-1_100084_2023-03-28_final.stac-item
2023-03-31 10:46:34	ga_ls9c_ard_3-2-1_105068_2023-03-31_final.stac-item
2023-04-16 10:46:27	ga_ls9c_ard_3-2-1_105068_2023-04-16_final.stac-item
2023-04-25 10:40:15	ga_ls9c_ard_3-2-1_104068_2023-04-25_final.stac-item
2023-05-11 10:40:04	ga_ls9c_ard_3-2-1_104068_2023-05-11_final.stac-item
2023-05-18 10:46:11	ga_ls9c_ard_3-2-1_105068_2023-05-18_final.stac-item
2023-06-16 10:21:24	ga_ls9c_ard_3-2-1_100084_2023-06-16_final.stac-item
2023-06-28 10:39:49	ga_ls9c_ard_3-2-1_104068_2023-06-28_final.stac-item
2023-07-02 10:21:35	ga_ls9c_ard_3-2-1_100084_2023-07-02_final.stac-item
2023-09-04 10:22:04	ga_ls9c_ard_3-2-1_100084_2023-09-04_final.stac-item
2023-09-20 10:22:10	ga_ls9c_ard_3-2-1_100084_2023-09-20_final.stac-item
2023-10-06 10:22:13	ga_ls9c_ard_3-2-1_100084_2023-10-06_final.stac-item
2023-10-22 10:22:20	ga_ls9c_ard_3-2-1_100084_2023-10-22_final.stac-item
2023-11-07 10:22:16	ga_ls9c_ard_3-2-1_100084_2023-11-07_final.stac-item
2023-11-23 10:22:23	ga_ls9c_ard_3-2-1_100084_2023-11-23_final.stac-item
2024-03-17 10:46:46	ga_ls9c_ard_3-2-1_105068_2024-03-17_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