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
2021-12-07 09:55:45	ga_ls9c_ard_3-2-1_096079_2021-12-07_final.stac-item
2021-12-09 09:45:22	ga_ls9c_ard_3-2-1_094084_2021-12-09_final.stac-item
2021-12-25 09:45:18	ga_ls9c_ard_3-2-1_094084_2021-12-25_final.stac-item
2022-01-01 09:51:05	ga_ls9c_ard_3-2-1_095083_2022-01-01_final.stac-item
2022-01-10 09:45:16	ga_ls9c_ard_3-2-1_094084_2022-01-10_final.stac-item
2022-01-17 09:51:02	ga_ls9c_ard_3-2-1_095083_2022-01-17_final.stac-item
2022-01-24 09:55:39	ga_ls9c_ard_3-2-1_096079_2022-01-24_final.stac-item
2022-01-26 09:45:17	ga_ls9c_ard_3-2-1_094084_2022-01-26_final.stac-item
2022-02-02 09:51:04	ga_ls9c_ard_3-2-1_095083_2022-02-02_final.stac-item
2022-02-09 09:55:37	ga_ls9c_ard_3-2-1_096079_2022-02-09_final.stac-item
2022-02-11 09:45:15	ga_ls9c_ard_3-2-1_094084_2022-02-11_final.stac-item
2022-02-25 09:55:28	ga_ls9c_ard_3-2-1_096079_2022-02-25_final.stac-item
2022-02-27 09:45:04	ga_ls9c_ard_3-2-1_094084_2022-02-27_final.stac-item
2022-03-06 09:50:49	ga_ls9c_ard_3-2-1_095083_2022-03-06_final.stac-item
2022-03-29 09:55:19	ga_ls9c_ard_3-2-1_096079_2022-03-29_final.stac-item
2022-03-31 09:44:57	ga_ls9c_ard_3-2-1_094084_2022-03-31_final.stac-item
2022-04-16 09:44:51	ga_ls9c_ard_3-2-1_094084_2022-04-16_final.stac-item
2022-05-25 09:50:18	ga_ls9c_ard_3-2-1_095083_2022-05-25_final.stac-item
2022-06-01 09:54:54	ga_ls9c_ard_3-2-1_096079_2022-06-01_final.stac-item
2022-06-03 09:44:33	ga_ls9c_ard_3-2-1_094084_2022-06-03_final.stac-item
2022-06-19 09:44:42	ga_ls9c_ard_3-2-1_094084_2022-06-19_final.stac-item
2022-06-26 09:50:41	ga_ls9c_ard_3-2-1_095083_2022-06-26_final.stac-item
2022-07-03 09:55:15	ga_ls9c_ard_3-2-1_096079_2022-07-03_final.stac-item
2022-07-05 09:44:52	ga_ls9c_ard_3-2-1_094084_2022-07-05_final.stac-item
2022-07-19 09:55:15	ga_ls9c_ard_3-2-1_096079_2022-07-19_final.stac-item
2022-07-21 09:44:55	ga_ls9c_ard_3-2-1_094084_2022-07-21_final.stac-item
2022-07-28 09:50:48	ga_ls9c_ard_3-2-1_095083_2022-07-28_final.stac-item
2022-08-04 09:55:29	ga_ls9c_ard_3-2-1_096079_2022-08-04_final.stac-item
2022-08-06 09:45:08	ga_ls9c_ard_3-2-1_094084_2022-08-06_final.stac-item
2022-08-13 09:49:23	ga_ls9c_ard_3-2-1_095079_2022-08-13_final.stac-item
2022-08-13 09:50:59	ga_ls9c_ard_3-2-1_095083_2022-08-13_final.stac-item
2022-08-20 09:55:36	ga_ls9c_ard_3-2-1_096079_2022-08-20_final.stac-item
2022-08-22 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-08-22_final.stac-item
2022-08-29 09:51:02	ga_ls9c_ard_3-2-1_095083_2022-08-29_final.stac-item
2022-09-07 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-09-07_final.stac-item
2022-09-21 09:55:43	ga_ls9c_ard_3-2-1_096079_2022-09-21_final.stac-item
2022-09-23 09:45:21	ga_ls9c_ard_3-2-1_094084_2022-09-23_final.stac-item
2022-09-30 09:49:33	ga_ls9c_ard_3-2-1_095079_2022-09-30_final.stac-item
2022-09-30 09:51:09	ga_ls9c_ard_3-2-1_095083_2022-09-30_final.stac-item
2022-10-09 09:45:23	ga_ls9c_ard_3-2-1_094084_2022-10-09_final.stac-item
2022-10-23 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-10-23_final.stac-item
2022-10-25 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-10-25_final.stac-item
2022-11-08 09:55:49	ga_ls9c_ard_3-2-1_096079_2022-11-08_final.stac-item
2022-11-10 09:45:28	ga_ls9c_ard_3-2-1_094084_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
2022-11-17 09:51:16	ga_ls9c_ard_3-2-1_095083_2022-11-17_final.stac-item
2022-11-26 09:45:27	ga_ls9c_ard_3-2-1_094084_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
2022-12-03 09:51:12	ga_ls9c_ard_3-2-1_095083_2022-12-03_final.stac-item
2022-12-10 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-12-10_final.stac-item
2022-12-12 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-12-12_final.stac-item
2022-12-26 09:55:47	ga_ls9c_ard_3-2-1_096079_2022-12-26_final.stac-item
2022-12-28 09:45:26	ga_ls9c_ard_3-2-1_094084_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
2023-01-04 09:51:15	ga_ls9c_ard_3-2-1_095083_2023-01-04_final.stac-item
2023-01-11 09:55:48	ga_ls9c_ard_3-2-1_096079_2023-01-11_final.stac-item
2023-01-13 09:45:25	ga_ls9c_ard_3-2-1_094084_2023-01-13_final.stac-item
2023-01-20 09:51:05	ga_ls9c_ard_3-2-1_095083_2023-01-20_final.stac-item
2023-01-27 09:55:47	ga_ls9c_ard_3-2-1_096079_2023-01-27_final.stac-item
2023-01-29 09:45:27	ga_ls9c_ard_3-2-1_094084_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 09:55:52	ga_ls9c_ard_3-2-1_096079_2023-02-12_final.stac-item
2023-02-21 09:49:32	ga_ls9c_ard_3-2-1_095079_2023-02-21_final.stac-item
2023-02-21 09:51:08	ga_ls9c_ard_3-2-1_095083_2023-02-21_final.stac-item
2023-03-02 09:45:16	ga_ls9c_ard_3-2-1_094084_2023-03-02_final.stac-item
2023-03-09 09:50:56	ga_ls9c_ard_3-2-1_095083_2023-03-09_final.stac-item
2023-03-16 09:55:32	ga_ls9c_ard_3-2-1_096079_2023-03-16_final.stac-item
2023-03-18 09:45:09	ga_ls9c_ard_3-2-1_094084_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
2023-03-25 09:50:51	ga_ls9c_ard_3-2-1_095083_2023-03-25_final.stac-item
2023-04-01 09:55:20	ga_ls9c_ard_3-2-1_096079_2023-04-01_final.stac-item
2023-04-10 09:51:06	ga_ls9c_ard_3-2-1_095084_2023-04-10_final.stac-item
2023-04-17 09:55:14	ga_ls9c_ard_3-2-1_096079_2023-04-17_final.stac-item
2023-04-19 09:44:52	ga_ls9c_ard_3-2-1_094084_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
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-05-03 09:55:03	ga_ls9c_ard_3-2-1_096079_2023-05-03_final.stac-item
2023-05-05 09:44:39	ga_ls9c_ard_3-2-1_094084_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
2023-05-12 09:50:26	ga_ls9c_ard_3-2-1_095083_2023-05-12_final.stac-item
2023-05-12 09:50:50	ga_ls9c_ard_3-2-1_095084_2023-05-12_final.stac-item
2023-05-19 09:54:57	ga_ls9c_ard_3-2-1_096079_2023-05-19_final.stac-item
2023-05-21 09:44:33	ga_ls9c_ard_3-2-1_094084_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 09:54:50	ga_ls9c_ard_3-2-1_096079_2023-06-04_final.stac-item
2023-06-06 09:44:27	ga_ls9c_ard_3-2-1_094084_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 09:54:42	ga_ls9c_ard_3-2-1_096079_2023-06-20_final.stac-item
2023-06-22 09:44:20	ga_ls9c_ard_3-2-1_094084_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
2023-06-29 09:50:37	ga_ls9c_ard_3-2-1_095084_2023-06-29_final.stac-item
2023-07-06 09:54:55	ga_ls9c_ard_3-2-1_096079_2023-07-06_final.stac-item
2023-07-08 09:44:34	ga_ls9c_ard_3-2-1_094084_2023-07-08_final.stac-item
2023-07-15 09:50:24	ga_ls9c_ard_3-2-1_095083_2023-07-15_final.stac-item
2023-07-31 09:50:29	ga_ls9c_ard_3-2-1_095083_2023-07-31_final.stac-item
2023-08-16 09:50:34	ga_ls9c_ard_3-2-1_095083_2023-08-16_final.stac-item
2024-04-21 09:44:45	ga_ls9c_ard_3-2-1_094084_2024-04-21_final.stac-item
2024-05-05 09:54:59	ga_ls9c_ard_3-2-1_096079_2024-05-05_final.stac-item
2024-05-07 09:44:37	ga_ls9c_ard_3-2-1_094084_2024-05-07_final.stac-item
2024-05-21 09:54:50	ga_ls9c_ard_3-2-1_096079_2024-05-21_nrt.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