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
2021-12-09 09:43:46	ga_ls9c_ard_3-2-1_094080_2021-12-09_final.stac-item
2021-12-23 09:53:40	ga_ls9c_ard_3-2-1_096074_2021-12-23_final.stac-item
2022-01-10 09:43:40	ga_ls9c_ard_3-2-1_094080_2022-01-10_final.stac-item
2022-01-24 09:53:39	ga_ls9c_ard_3-2-1_096074_2022-01-24_final.stac-item
2022-01-26 09:43:41	ga_ls9c_ard_3-2-1_094080_2022-01-26_final.stac-item
2022-02-02 09:47:28	ga_ls9c_ard_3-2-1_095074_2022-02-02_final.stac-item
2022-02-11 09:43:39	ga_ls9c_ard_3-2-1_094080_2022-02-11_final.stac-item
2022-02-25 09:53:28	ga_ls9c_ard_3-2-1_096074_2022-02-25_final.stac-item
2022-03-22 09:47:11	ga_ls9c_ard_3-2-1_095074_2022-03-22_final.stac-item
2022-04-23 09:46:57	ga_ls9c_ard_3-2-1_095074_2022-04-23_final.stac-item
2022-04-30 09:53:08	ga_ls9c_ard_3-2-1_096074_2022-04-30_final.stac-item
2022-05-16 09:52:58	ga_ls9c_ard_3-2-1_096074_2022-05-16_final.stac-item
2022-05-25 09:46:42	ga_ls9c_ard_3-2-1_095074_2022-05-25_final.stac-item
2022-06-03 09:42:57	ga_ls9c_ard_3-2-1_094080_2022-06-03_final.stac-item
2022-06-19 09:43:06	ga_ls9c_ard_3-2-1_094080_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
2022-07-03 09:53:15	ga_ls9c_ard_3-2-1_096074_2022-07-03_final.stac-item
2022-07-05 09:43:16	ga_ls9c_ard_3-2-1_094080_2022-07-05_final.stac-item
2022-07-12 09:47:01	ga_ls9c_ard_3-2-1_095074_2022-07-12_final.stac-item
2022-07-19 09:52:51	ga_ls9c_ard_3-2-1_096073_2022-07-19_final.stac-item
2022-07-21 09:43:19	ga_ls9c_ard_3-2-1_094080_2022-07-21_final.stac-item
2022-08-04 09:53:05	ga_ls9c_ard_3-2-1_096073_2022-08-04_final.stac-item
2022-08-13 09:47:23	ga_ls9c_ard_3-2-1_095074_2022-08-13_final.stac-item
2022-08-13 09:49:23	ga_ls9c_ard_3-2-1_095079_2022-08-13_final.stac-item
2022-08-22 09:43:38	ga_ls9c_ard_3-2-1_094080_2022-08-22_final.stac-item
2022-08-29 09:47:26	ga_ls9c_ard_3-2-1_095074_2022-08-29_final.stac-item
2022-09-05 09:53:13	ga_ls9c_ard_3-2-1_096073_2022-09-05_final.stac-item
2022-09-07 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-09-07_final.stac-item
2022-09-14 09:47:29	ga_ls9c_ard_3-2-1_095074_2022-09-14_final.stac-item
2022-09-30 09:49:33	ga_ls9c_ard_3-2-1_095079_2022-09-30_final.stac-item
2022-10-07 09:53:20	ga_ls9c_ard_3-2-1_096073_2022-10-07_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-09 09:43:47	ga_ls9c_ard_3-2-1_094080_2022-10-09_final.stac-item
2022-10-25 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-10-25_final.stac-item
2022-10-25 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-10-25_final.stac-item
2022-11-08 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-08_final.stac-item
2022-11-10 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-11-10_final.stac-item
2022-11-17 09:49:40	ga_ls9c_ard_3-2-1_095079_2022-11-17_final.stac-item
2022-11-24 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-24_final.stac-item
2022-11-26 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-11-26_final.stac-item
2022-12-03 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-12-03_final.stac-item
2022-12-10 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-12-10_final.stac-item
2022-12-12 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-12-12_final.stac-item
2022-12-26 09:53:24	ga_ls9c_ard_3-2-1_096073_2022-12-26_final.stac-item
2022-12-28 09:43:27	ga_ls9c_ard_3-2-1_094079_2022-12-28_final.stac-item
2022-12-28 09:43:51	ga_ls9c_ard_3-2-1_094080_2022-12-28_final.stac-item
2023-01-04 09:49:39	ga_ls9c_ard_3-2-1_095079_2023-01-04_final.stac-item
2023-01-13 09:43:26	ga_ls9c_ard_3-2-1_094079_2023-01-13_final.stac-item
2023-01-13 09:43:50	ga_ls9c_ard_3-2-1_094080_2023-01-13_final.stac-item
2023-01-20 09:49:29	ga_ls9c_ard_3-2-1_095079_2023-01-20_final.stac-item
2023-01-27 09:53:23	ga_ls9c_ard_3-2-1_096073_2023-01-27_final.stac-item
2023-01-29 09:43:27	ga_ls9c_ard_3-2-1_094079_2023-01-29_final.stac-item
2023-01-29 09:43:51	ga_ls9c_ard_3-2-1_094080_2023-01-29_final.stac-item
2023-02-05 09:49:42	ga_ls9c_ard_3-2-1_095079_2023-02-05_final.stac-item
2023-02-12 09:53:29	ga_ls9c_ard_3-2-1_096073_2023-02-12_final.stac-item
2023-02-14 09:43:30	ga_ls9c_ard_3-2-1_094079_2023-02-14_final.stac-item
2023-02-14 09:43:54	ga_ls9c_ard_3-2-1_094080_2023-02-14_final.stac-item
2023-02-21 09:49:32	ga_ls9c_ard_3-2-1_095079_2023-02-21_final.stac-item
2023-03-02 09:43:40	ga_ls9c_ard_3-2-1_094080_2023-03-02_final.stac-item
2023-03-09 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-03-09_final.stac-item
2023-03-18 09:43:09	ga_ls9c_ard_3-2-1_094079_2023-03-18_final.stac-item
2023-03-18 09:43:33	ga_ls9c_ard_3-2-1_094080_2023-03-18_final.stac-item
2023-03-25 09:49:15	ga_ls9c_ard_3-2-1_095079_2023-03-25_final.stac-item
2023-04-10 09:49:06	ga_ls9c_ard_3-2-1_095079_2023-04-10_final.stac-item
2023-04-17 09:52:50	ga_ls9c_ard_3-2-1_096073_2023-04-17_final.stac-item
2023-04-19 09:42:52	ga_ls9c_ard_3-2-1_094079_2023-04-19_final.stac-item
2023-04-19 09:43:16	ga_ls9c_ard_3-2-1_094080_2023-04-19_final.stac-item
2023-04-26 09:49:00	ga_ls9c_ard_3-2-1_095079_2023-04-26_final.stac-item
2023-05-03 09:52:40	ga_ls9c_ard_3-2-1_096073_2023-05-03_final.stac-item
2023-05-05 09:42:40	ga_ls9c_ard_3-2-1_094079_2023-05-05_final.stac-item
2023-05-05 09:43:04	ga_ls9c_ard_3-2-1_094080_2023-05-05_final.stac-item
2023-05-12 09:48:50	ga_ls9c_ard_3-2-1_095079_2023-05-12_final.stac-item
2023-05-19 09:52:33	ga_ls9c_ard_3-2-1_096073_2023-05-19_final.stac-item
2023-05-21 09:42:33	ga_ls9c_ard_3-2-1_094079_2023-05-21_final.stac-item
2023-05-21 09:42:57	ga_ls9c_ard_3-2-1_094080_2023-05-21_final.stac-item
2023-05-28 09:48:40	ga_ls9c_ard_3-2-1_095079_2023-05-28_final.stac-item
2023-06-04 09:52:26	ga_ls9c_ard_3-2-1_096073_2023-06-04_final.stac-item
2023-06-06 09:42:27	ga_ls9c_ard_3-2-1_094079_2023-06-06_final.stac-item
2023-06-13 09:48:33	ga_ls9c_ard_3-2-1_095079_2023-06-13_final.stac-item
2023-06-20 09:52:19	ga_ls9c_ard_3-2-1_096073_2023-06-20_final.stac-item
2023-06-22 09:42:21	ga_ls9c_ard_3-2-1_094079_2023-06-22_final.stac-item
2023-06-22 09:42:44	ga_ls9c_ard_3-2-1_094080_2023-06-22_final.stac-item
2023-06-29 09:48:37	ga_ls9c_ard_3-2-1_095079_2023-06-29_final.stac-item
2023-07-06 09:52:31	ga_ls9c_ard_3-2-1_096073_2023-07-06_final.stac-item
2023-07-08 09:42:35	ga_ls9c_ard_3-2-1_094079_2023-07-08_final.stac-item
2023-07-08 09:42:58	ga_ls9c_ard_3-2-1_094080_2023-07-08_final.stac-item
2023-09-24 09:53:25	ga_ls9c_ard_3-2-1_096074_2023-09-24_final.stac-item
2023-10-10 09:53:32	ga_ls9c_ard_3-2-1_096074_2023-10-10_final.stac-item
2023-10-26 09:53:36	ga_ls9c_ard_3-2-1_096074_2023-10-26_final.stac-item
2023-11-11 09:53:34	ga_ls9c_ard_3-2-1_096074_2023-11-11_final.stac-item
2023-11-27 09:53:42	ga_ls9c_ard_3-2-1_096074_2023-11-27_final.stac-item
2023-12-13 09:53:40	ga_ls9c_ard_3-2-1_096074_2023-12-13_final.stac-item
2023-12-29 09:53:42	ga_ls9c_ard_3-2-1_096074_2023-12-29_final.stac-item
2024-01-14 09:53:40	ga_ls9c_ard_3-2-1_096074_2024-01-14_final.stac-item
2024-01-30 09:53:40	ga_ls9c_ard_3-2-1_096074_2024-01-30_final.stac-item
2024-02-15 09:53:38	ga_ls9c_ard_3-2-1_096074_2024-02-15_final.stac-item
2024-03-02 09:53:33	ga_ls9c_ard_3-2-1_096074_2024-03-02_final.stac-item
2024-03-18 09:53:32	ga_ls9c_ard_3-2-1_096074_2024-03-18_final.stac-item
2024-04-03 09:53:23	ga_ls9c_ard_3-2-1_096074_2024-04-03_final.stac-item
2024-04-19 09:53:11	ga_ls9c_ard_3-2-1_096074_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years