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
2021-11-08 09:54:39	ga_ls9c_ard_3-2-1_097068_2021-11-08_final.stac-item
2021-11-13 09:57:07	ga_ls9c_ard_3-2-1_097068_2021-11-13_final.stac-item
2021-12-08 10:35:01	ga_ls9c_ard_3-2-1_103069_2021-12-08_final.stac-item
2021-12-14 09:57:28	ga_ls9c_ard_3-2-1_097068_2021-12-14_final.stac-item
2021-12-15 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-15_final.stac-item
2021-12-30 09:57:27	ga_ls9c_ard_3-2-1_097068_2021-12-30_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
2022-01-02 10:28:45	ga_ls9c_ard_3-2-1_102069_2022-01-02_final.stac-item
2022-01-07 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-01-07_final.stac-item
2022-01-15 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-01-15_final.stac-item
2022-01-31 09:57:27	ga_ls9c_ard_3-2-1_097068_2022-01-31_final.stac-item
2022-02-01 10:40:42	ga_ls9c_ard_3-2-1_104068_2022-02-01_final.stac-item
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final.stac-item
2022-02-16 09:57:22	ga_ls9c_ard_3-2-1_097068_2022-02-16_final.stac-item
2022-03-04 09:57:11	ga_ls9c_ard_3-2-1_097068_2022-03-04_final.stac-item
2022-03-12 10:46:38	ga_ls9c_ard_3-2-1_105068_2022-03-12_final.stac-item
2022-03-20 09:57:10	ga_ls9c_ard_3-2-1_097068_2022-03-20_final.stac-item
2022-03-28 10:46:33	ga_ls9c_ard_3-2-1_105068_2022-03-28_final.stac-item
2022-04-05 09:57:06	ga_ls9c_ard_3-2-1_097068_2022-04-05_final.stac-item
2022-04-21 09:56:56	ga_ls9c_ard_3-2-1_097068_2022-04-21_final.stac-item
2022-05-07 09:56:52	ga_ls9c_ard_3-2-1_097068_2022-05-07_final.stac-item
2022-05-23 09:56:41	ga_ls9c_ard_3-2-1_097068_2022-05-23_final.stac-item
2022-05-24 10:39:56	ga_ls9c_ard_3-2-1_104068_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
2022-06-08 09:56:42	ga_ls9c_ard_3-2-1_097068_2022-06-08_final.stac-item
2022-06-18 10:34:18	ga_ls9c_ard_3-2-1_103069_2022-06-18_final.stac-item
2022-06-24 09:57:02	ga_ls9c_ard_3-2-1_097068_2022-06-24_final.stac-item
2022-06-25 10:40:19	ga_ls9c_ard_3-2-1_104068_2022-06-25_final.stac-item
2022-07-02 10:46:29	ga_ls9c_ard_3-2-1_105068_2022-07-02_final.stac-item
2022-07-10 09:57:00	ga_ls9c_ard_3-2-1_097068_2022-07-10_final.stac-item
2022-07-26 09:57:09	ga_ls9c_ard_3-2-1_097068_2022-07-26_final.stac-item
2022-08-11 09:57:20	ga_ls9c_ard_3-2-1_097068_2022-08-11_final.stac-item
2022-08-27 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-08-27_final.stac-item
2022-09-12 09:57:26	ga_ls9c_ard_3-2-1_097068_2022-09-12_final.stac-item
2022-09-13 10:40:42	ga_ls9c_ard_3-2-1_104068_2022-09-13_final.stac-item
2022-09-20 10:46:56	ga_ls9c_ard_3-2-1_105068_2022-09-20_final.stac-item
2022-09-28 09:57:32	ga_ls9c_ard_3-2-1_097068_2022-09-28_final.stac-item
2022-10-06 10:46:57	ga_ls9c_ard_3-2-1_105068_2022-10-06_final.stac-item
2022-10-14 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-14_final.stac-item
2022-10-30 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-30_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-15 09:57:38	ga_ls9c_ard_3-2-1_097068_2022-11-15_final.stac-item
2022-12-01 09:57:35	ga_ls9c_ard_3-2-1_097068_2022-12-01_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
2022-12-16 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-12-16_final.stac-item
2022-12-17 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-12-17_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2023-01-02 09:57:37	ga_ls9c_ard_3-2-1_097068_2023-01-02_final.stac-item
2023-01-03 10:40:53	ga_ls9c_ard_3-2-1_104068_2023-01-03_final.stac-item
2023-01-18 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-01-18_final.stac-item
2023-01-19 10:40:44	ga_ls9c_ard_3-2-1_104068_2023-01-19_final.stac-item
2023-02-03 09:57:39	ga_ls9c_ard_3-2-1_097068_2023-02-03_final.stac-item
2023-02-11 10:47:07	ga_ls9c_ard_3-2-1_105068_2023-02-11_final.stac-item
2023-02-19 09:57:33	ga_ls9c_ard_3-2-1_097068_2023-02-19_final.stac-item
2023-03-07 09:57:21	ga_ls9c_ard_3-2-1_097068_2023-03-07_final.stac-item
2023-03-22 10:52:54	ga_ls9c_ard_3-2-1_106068_2023-03-22_final.stac-item
2023-03-23 09:57:15	ga_ls9c_ard_3-2-1_097068_2023-03-23_final.stac-item
2023-03-24 10:40:30	ga_ls9c_ard_3-2-1_104068_2023-03-24_final.stac-item
2023-04-08 09:57:06	ga_ls9c_ard_3-2-1_097068_2023-04-08_final.stac-item
2023-04-16 10:46:27	ga_ls9c_ard_3-2-1_105068_2023-04-16_final.stac-item
2023-04-23 10:52:38	ga_ls9c_ard_3-2-1_106068_2023-04-23_final.stac-item
2023-04-24 09:57:00	ga_ls9c_ard_3-2-1_097068_2023-04-24_final.stac-item
2023-04-25 10:40:15	ga_ls9c_ard_3-2-1_104068_2023-04-25_final.stac-item
2023-05-09 10:52:26	ga_ls9c_ard_3-2-1_106068_2023-05-09_final.stac-item
2023-05-10 09:56:49	ga_ls9c_ard_3-2-1_097068_2023-05-10_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
2023-05-25 10:52:16	ga_ls9c_ard_3-2-1_106068_2023-05-25_final.stac-item
2023-05-26 09:56:39	ga_ls9c_ard_3-2-1_097068_2023-05-26_final.stac-item
2023-06-11 09:56:33	ga_ls9c_ard_3-2-1_097068_2023-06-11_final.stac-item
2023-06-26 10:52:07	ga_ls9c_ard_3-2-1_106068_2023-06-26_final.stac-item
2023-06-27 09:56:31	ga_ls9c_ard_3-2-1_097068_2023-06-27_final.stac-item
2023-06-28 10:39:49	ga_ls9c_ard_3-2-1_104068_2023-06-28_final.stac-item
2023-07-13 09:56:46	ga_ls9c_ard_3-2-1_097068_2023-07-13_final.stac-item
2023-07-16 10:28:04	ga_ls9c_ard_3-2-1_102069_2023-07-16_final.stac-item
2023-07-23 10:34:14	ga_ls9c_ard_3-2-1_103069_2023-07-23_final.stac-item
2023-07-29 09:56:49	ga_ls9c_ard_3-2-1_097068_2023-07-29_final.stac-item
2023-08-01 10:28:10	ga_ls9c_ard_3-2-1_102069_2023-08-01_final.stac-item
2023-08-14 09:56:56	ga_ls9c_ard_3-2-1_097068_2023-08-14_final.stac-item
2023-08-17 10:28:14	ga_ls9c_ard_3-2-1_102069_2023-08-17_final.stac-item
2023-08-24 10:34:31	ga_ls9c_ard_3-2-1_103069_2023-08-24_final.stac-item
2023-08-30 09:57:06	ga_ls9c_ard_3-2-1_097068_2023-08-30_final.stac-item
2023-09-02 10:28:25	ga_ls9c_ard_3-2-1_102069_2023-09-02_final.stac-item
2023-09-15 09:57:15	ga_ls9c_ard_3-2-1_097068_2023-09-15_final.stac-item
2023-10-01 09:57:13	ga_ls9c_ard_3-2-1_097068_2023-10-01_final.stac-item
2023-10-17 09:57:25	ga_ls9c_ard_3-2-1_097068_2023-10-17_final.stac-item
2023-11-02 09:57:18	ga_ls9c_ard_3-2-1_097068_2023-11-02_final.stac-item
2023-11-18 09:57:22	ga_ls9c_ard_3-2-1_097068_2023-11-18_final.stac-item
2023-12-04 09:57:26	ga_ls9c_ard_3-2-1_097068_2023-12-04_final.stac-item
2023-12-20 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-12-20_final.stac-item
2024-01-05 09:57:24	ga_ls9c_ard_3-2-1_097068_2024-01-05_final.stac-item
2024-01-21 09:57:25	ga_ls9c_ard_3-2-1_097068_2024-01-21_final.stac-item
2024-02-06 09:57:29	ga_ls9c_ard_3-2-1_097068_2024-02-06_final.stac-item
2024-02-22 09:57:15	ga_ls9c_ard_3-2-1_097068_2024-02-22_final.stac-item
2024-03-09 09:57:21	ga_ls9c_ard_3-2-1_097068_2024-03-09_final.stac-item
2024-03-25 09:57:16	ga_ls9c_ard_3-2-1_097068_2024-03-25_final.stac-item
2024-04-10 09:57:08	ga_ls9c_ard_3-2-1_097068_2024-04-10_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