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
2021-12-15 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-15_final.stac-item
2021-12-28 10:16:36	ga_ls9c_ard_3-2-1_099085_2021-12-28_final.stac-item
2021-12-31 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-31_final.stac-item
2022-01-09 10:34:30	ga_ls9c_ard_3-2-1_103068_2022-01-09_final.stac-item
2022-01-16 10:40:40	ga_ls9c_ard_3-2-1_104068_2022-01-16_final.stac-item
2022-01-25 10:34:31	ga_ls9c_ard_3-2-1_103068_2022-01-25_final.stac-item
2022-01-25 10:34:55	ga_ls9c_ard_3-2-1_103069_2022-01-25_final.stac-item
2022-01-25 10:35:19	ga_ls9c_ard_3-2-1_103070_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
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-17 10:40:37	ga_ls9c_ard_3-2-1_104068_2022-02-17_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-30 10:34:12	ga_ls9c_ard_3-2-1_103068_2022-03-30_final.stac-item
2022-03-30 10:35:23	ga_ls9c_ard_3-2-1_103071_2022-03-30_final.stac-item
2022-04-06 10:40:22	ga_ls9c_ard_3-2-1_104068_2022-04-06_final.stac-item
2022-04-15 10:34:06	ga_ls9c_ard_3-2-1_103068_2022-04-15_final.stac-item
2022-05-01 10:33:59	ga_ls9c_ard_3-2-1_103068_2022-05-01_final.stac-item
2022-05-01 10:34:47	ga_ls9c_ard_3-2-1_103070_2022-05-01_final.stac-item
2022-05-01 10:35:11	ga_ls9c_ard_3-2-1_103071_2022-05-01_final.stac-item
2022-05-17 10:33:49	ga_ls9c_ard_3-2-1_103068_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
2022-06-02 10:33:47	ga_ls9c_ard_3-2-1_103068_2022-06-02_final.stac-item
2022-06-25 10:40:19	ga_ls9c_ard_3-2-1_104068_2022-06-25_final.stac-item
2022-07-04 10:34:31	ga_ls9c_ard_3-2-1_103069_2022-07-04_final.stac-item
2022-07-11 10:40:39	ga_ls9c_ard_3-2-1_104069_2022-07-11_final.stac-item
2022-07-20 10:34:08	ga_ls9c_ard_3-2-1_103068_2022-07-20_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-08-05 10:34:45	ga_ls9c_ard_3-2-1_103069_2022-08-05_final.stac-item
2022-08-05 10:35:09	ga_ls9c_ard_3-2-1_103070_2022-08-05_final.stac-item
2022-08-05 10:35:33	ga_ls9c_ard_3-2-1_103071_2022-08-05_final.stac-item
2022-08-12 10:40:36	ga_ls9c_ard_3-2-1_104068_2022-08-12_final.stac-item
2022-08-21 10:34:28	ga_ls9c_ard_3-2-1_103068_2022-08-21_final.stac-item
2022-08-21 10:34:52	ga_ls9c_ard_3-2-1_103069_2022-08-21_final.stac-item
2022-09-06 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-09-06_final.stac-item
2022-09-13 10:40:42	ga_ls9c_ard_3-2-1_104068_2022-09-13_final.stac-item
2022-10-08 10:35:25	ga_ls9c_ard_3-2-1_103070_2022-10-08_final.stac-item
2022-10-08 10:35:49	ga_ls9c_ard_3-2-1_103071_2022-10-08_final.stac-item
2022-10-24 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-10-24_final.stac-item
2022-10-28 10:16:46	ga_ls9c_ard_3-2-1_099085_2022-10-28_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-13 10:16:47	ga_ls9c_ard_3-2-1_099085_2022-11-13_final.stac-item
2022-11-25 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-11-25_final.stac-item
2022-11-29 10:16:44	ga_ls9c_ard_3-2-1_099085_2022-11-29_final.stac-item
2022-12-02 10:40:50	ga_ls9c_ard_3-2-1_104068_2022-12-02_final.stac-item
2022-12-11 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-12-11_final.stac-item
2022-12-11 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-12-11_final.stac-item
2022-12-11 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-12-11_final.stac-item
2022-12-15 10:16:46	ga_ls9c_ard_3-2-1_099085_2022-12-15_final.stac-item
2023-01-03 10:40:53	ga_ls9c_ard_3-2-1_104068_2023-01-03_final.stac-item
2023-01-12 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-12_final.stac-item
2023-01-16 10:16:41	ga_ls9c_ard_3-2-1_099085_2023-01-16_final.stac-item
2023-01-19 10:40:44	ga_ls9c_ard_3-2-1_104068_2023-01-19_final.stac-item
2023-01-28 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-28_final.stac-item
2023-01-28 10:35:28	ga_ls9c_ard_3-2-1_103070_2023-01-28_final.stac-item
2023-02-17 10:16:44	ga_ls9c_ard_3-2-1_099085_2023-02-17_final.stac-item
2023-02-20 10:40:47	ga_ls9c_ard_3-2-1_104068_2023-02-20_final.stac-item
2023-03-08 10:40:36	ga_ls9c_ard_3-2-1_104068_2023-03-08_final.stac-item
2023-03-17 10:34:24	ga_ls9c_ard_3-2-1_103068_2023-03-17_final.stac-item
2023-03-17 10:35:12	ga_ls9c_ard_3-2-1_103070_2023-03-17_final.stac-item
2023-03-24 10:40:30	ga_ls9c_ard_3-2-1_104068_2023-03-24_final.stac-item
2023-04-18 10:34:06	ga_ls9c_ard_3-2-1_103068_2023-04-18_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-25 10:40:15	ga_ls9c_ard_3-2-1_104068_2023-04-25_final.stac-item
2023-05-04 10:35:06	ga_ls9c_ard_3-2-1_103071_2023-05-04_final.stac-item
2023-05-08 10:15:58	ga_ls9c_ard_3-2-1_099085_2023-05-08_final.stac-item
2023-05-11 10:40:04	ga_ls9c_ard_3-2-1_104068_2023-05-11_final.stac-item
2023-05-20 10:35:00	ga_ls9c_ard_3-2-1_103071_2023-05-20_final.stac-item
2023-05-24 10:15:48	ga_ls9c_ard_3-2-1_099085_2023-05-24_final.stac-item
2023-06-05 10:33:42	ga_ls9c_ard_3-2-1_103068_2023-06-05_final.stac-item
2023-06-05 10:34:54	ga_ls9c_ard_3-2-1_103071_2023-06-05_final.stac-item
2023-06-21 10:33:35	ga_ls9c_ard_3-2-1_103068_2023-06-21_final.stac-item
2023-06-25 10:15:38	ga_ls9c_ard_3-2-1_099085_2023-06-25_final.stac-item
2023-06-28 10:39:49	ga_ls9c_ard_3-2-1_104068_2023-06-28_final.stac-item
2023-07-07 10:35:00	ga_ls9c_ard_3-2-1_103071_2023-07-07_final.stac-item
2023-07-11 10:15:54	ga_ls9c_ard_3-2-1_099085_2023-07-11_final.stac-item
2023-07-23 10:35:02	ga_ls9c_ard_3-2-1_103071_2023-07-23_final.stac-item
2023-08-08 10:34:25	ga_ls9c_ard_3-2-1_103069_2023-08-08_final.stac-item
2023-08-08 10:34:49	ga_ls9c_ard_3-2-1_103070_2023-08-08_final.stac-item
2023-08-08 10:35:13	ga_ls9c_ard_3-2-1_103071_2023-08-08_final.stac-item
2023-09-09 10:35:05	ga_ls9c_ard_3-2-1_103070_2023-09-09_final.stac-item
2023-09-09 10:35:29	ga_ls9c_ard_3-2-1_103071_2023-09-09_final.stac-item
2023-09-25 10:35:05	ga_ls9c_ard_3-2-1_103070_2023-09-25_final.stac-item
2023-10-11 10:35:13	ga_ls9c_ard_3-2-1_103070_2023-10-11_final.stac-item
2023-10-27 10:35:16	ga_ls9c_ard_3-2-1_103070_2023-10-27_final.stac-item
2023-11-12 10:35:14	ga_ls9c_ard_3-2-1_103070_2023-11-12_final.stac-item
2024-01-15 10:35:44	ga_ls9c_ard_3-2-1_103071_2024-01-15_final.stac-item
2024-01-31 10:35:44	ga_ls9c_ard_3-2-1_103071_2024-01-31_final.stac-item
2024-03-03 10:35:13	ga_ls9c_ard_3-2-1_103070_2024-03-03_final.stac-item
2024-03-03 10:35:37	ga_ls9c_ard_3-2-1_103071_2024-03-03_final.stac-item
2024-03-19 10:34:48	ga_ls9c_ard_3-2-1_103069_2024-03-19_final.stac-item
2024-03-19 10:35:12	ga_ls9c_ard_3-2-1_103070_2024-03-19_final.stac-item
2024-04-04 10:34:39	ga_ls9c_ard_3-2-1_103069_2024-04-04_final.stac-item
2024-04-04 10:35:03	ga_ls9c_ard_3-2-1_103070_2024-04-04_final.stac-item
2024-04-11 10:40:47	ga_ls9c_ard_3-2-1_104069_2024-04-11_final.stac-item
2024-04-20 10:34:49	ga_ls9c_ard_3-2-1_103070_2024-04-20_final.stac-item
2024-04-27 10:40:27	ga_ls9c_ard_3-2-1_104069_2024-04-27_final.stac-item
2024-05-06 10:33:51	ga_ls9c_ard_3-2-1_103068_2024-05-06_final.stac-item
2024-05-06 10:34:39	ga_ls9c_ard_3-2-1_103070_2024-05-06_final.stac-item
2024-05-13 10:39:59	ga_ls9c_ard_3-2-1_104068_2024-05-13_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