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
2021-11-05 11:13:17	ga_ls9c_ard_3-2-1_109071_2021-11-05_final.stac-item
2021-11-07 10:59:20	ga_ls9c_ard_3-2-1_106083_2021-11-07_final.stac-item
2021-11-10 11:14:58	ga_ls9c_ard_3-2-1_110069_2021-11-10_final.stac-item
2021-11-10 11:15:46	ga_ls9c_ard_3-2-1_110071_2021-11-10_final.stac-item
2021-11-12 11:01:48	ga_ls9c_ard_3-2-1_106083_2021-11-12_final.stac-item
2021-11-15 11:18:14	ga_ls9c_ard_3-2-1_110071_2021-11-15_final.stac-item
2021-11-20 11:19:54	ga_ls9c_ard_3-2-1_110069_2021-11-20_final.stac-item
2021-11-22 11:06:43	ga_ls9c_ard_3-2-1_107083_2021-11-22_final.stac-item
2021-12-09 11:18:16	ga_ls9c_ard_3-2-1_110069_2021-12-09_final.stac-item
2021-12-09 11:19:04	ga_ls9c_ard_3-2-1_110071_2021-12-09_final.stac-item
2021-12-13 10:59:05	ga_ls9c_ard_3-2-1_106083_2021-12-13_final.stac-item
2021-12-20 11:05:38	ga_ls9c_ard_3-2-1_107084_2021-12-20_final.stac-item
2021-12-25 11:18:12	ga_ls9c_ard_3-2-1_110069_2021-12-25_final.stac-item
2021-12-25 11:19:00	ga_ls9c_ard_3-2-1_110071_2021-12-25_final.stac-item
2021-12-29 10:59:04	ga_ls9c_ard_3-2-1_106083_2021-12-29_final.stac-item
2022-01-03 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-01-03_final.stac-item
2022-01-10 11:18:57	ga_ls9c_ard_3-2-1_110071_2022-01-10_final.stac-item
2022-01-14 10:59:00	ga_ls9c_ard_3-2-1_106083_2022-01-14_final.stac-item
2022-01-26 11:18:11	ga_ls9c_ard_3-2-1_110069_2022-01-26_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-02-06 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-02-06_final.stac-item
2022-02-11 11:18:09	ga_ls9c_ard_3-2-1_110069_2022-02-11_final.stac-item
2022-02-15 10:58:58	ga_ls9c_ard_3-2-1_106083_2022-02-15_final.stac-item
2022-02-27 11:17:58	ga_ls9c_ard_3-2-1_110069_2022-02-27_final.stac-item
2022-03-03 10:58:48	ga_ls9c_ard_3-2-1_106083_2022-03-03_final.stac-item
2022-03-08 11:12:33	ga_ls9c_ard_3-2-1_109071_2022-03-08_final.stac-item
2022-03-19 10:58:47	ga_ls9c_ard_3-2-1_106083_2022-03-19_final.stac-item
2022-03-24 11:12:30	ga_ls9c_ard_3-2-1_109071_2022-03-24_final.stac-item
2022-03-31 11:17:51	ga_ls9c_ard_3-2-1_110069_2022-03-31_final.stac-item
2022-04-04 10:58:43	ga_ls9c_ard_3-2-1_106083_2022-04-04_final.stac-item
2022-04-16 11:18:33	ga_ls9c_ard_3-2-1_110071_2022-04-16_final.stac-item
2022-04-20 10:58:33	ga_ls9c_ard_3-2-1_106083_2022-04-20_final.stac-item
2022-04-27 11:05:06	ga_ls9c_ard_3-2-1_107084_2022-04-27_final.stac-item
2022-05-06 10:58:29	ga_ls9c_ard_3-2-1_106083_2022-05-06_final.stac-item
2022-05-13 11:04:59	ga_ls9c_ard_3-2-1_107084_2022-05-13_final.stac-item
2022-05-18 11:17:27	ga_ls9c_ard_3-2-1_110069_2022-05-18_final.stac-item
2022-05-22 10:58:17	ga_ls9c_ard_3-2-1_106083_2022-05-22_final.stac-item
2022-05-27 11:12:02	ga_ls9c_ard_3-2-1_109071_2022-05-27_final.stac-item
2022-06-03 11:17:26	ga_ls9c_ard_3-2-1_110069_2022-06-03_final.stac-item
2022-06-07 10:58:19	ga_ls9c_ard_3-2-1_106083_2022-06-07_final.stac-item
2022-06-19 11:18:24	ga_ls9c_ard_3-2-1_110071_2022-06-19_final.stac-item
2022-06-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-06-23_final.stac-item
2022-06-28 11:12:25	ga_ls9c_ard_3-2-1_109071_2022-06-28_final.stac-item
2022-07-05 11:17:46	ga_ls9c_ard_3-2-1_110069_2022-07-05_final.stac-item
2022-07-09 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-07-09_final.stac-item
2022-07-14 11:12:19	ga_ls9c_ard_3-2-1_109071_2022-07-14_final.stac-item
2022-07-16 11:05:10	ga_ls9c_ard_3-2-1_107084_2022-07-16_final.stac-item
2022-07-25 10:58:45	ga_ls9c_ard_3-2-1_106083_2022-07-25_final.stac-item
2022-07-30 11:12:34	ga_ls9c_ard_3-2-1_109071_2022-07-30_final.stac-item
2022-08-06 11:18:02	ga_ls9c_ard_3-2-1_110069_2022-08-06_final.stac-item
2022-08-10 10:58:56	ga_ls9c_ard_3-2-1_106083_2022-08-10_final.stac-item
2022-08-17 11:05:34	ga_ls9c_ard_3-2-1_107084_2022-08-17_final.stac-item
2022-08-22 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-08-22_final.stac-item
2022-08-26 10:59:01	ga_ls9c_ard_3-2-1_106083_2022-08-26_final.stac-item
2022-08-31 11:12:46	ga_ls9c_ard_3-2-1_109071_2022-08-31_final.stac-item
2022-09-07 11:18:08	ga_ls9c_ard_3-2-1_110069_2022-09-07_final.stac-item
2022-09-07 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-09-07_final.stac-item
2022-09-23 11:18:15	ga_ls9c_ard_3-2-1_110069_2022-09-23_final.stac-item
2022-09-23 11:19:03	ga_ls9c_ard_3-2-1_110071_2022-09-23_final.stac-item
2022-09-27 10:59:08	ga_ls9c_ard_3-2-1_106083_2022-09-27_final.stac-item
2022-10-04 11:05:43	ga_ls9c_ard_3-2-1_107084_2022-10-04_final.stac-item
2022-10-09 11:18:17	ga_ls9c_ard_3-2-1_110069_2022-10-09_final.stac-item
2022-10-20 11:05:49	ga_ls9c_ard_3-2-1_107084_2022-10-20_final.stac-item
2022-10-25 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-10-25_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-11-05 11:05:46	ga_ls9c_ard_3-2-1_107084_2022-11-05_final.stac-item
2022-12-05 11:12:57	ga_ls9c_ard_3-2-1_109071_2022-12-05_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_nrt.stac-item
2023-01-13 11:19:07	ga_ls9c_ard_3-2-1_110071_2023-01-13_final.stac-item
2023-01-22 11:12:50	ga_ls9c_ard_3-2-1_109071_2023-01-22_final.stac-item
2023-02-18 10:59:11	ga_ls9c_ard_3-2-1_106083_2023-02-18_final.stac-item
2023-03-22 10:58:53	ga_ls9c_ard_3-2-1_106083_2023-03-22_final.stac-item
2023-04-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2023-04-23_final.stac-item
2023-04-28 11:12:18	ga_ls9c_ard_3-2-1_109071_2023-04-28_final.stac-item
2023-05-05 11:18:21	ga_ls9c_ard_3-2-1_110071_2023-05-05_final.stac-item
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-14 11:12:09	ga_ls9c_ard_3-2-1_109071_2023-05-14_final.stac-item
2023-05-21 11:18:15	ga_ls9c_ard_3-2-1_110071_2023-05-21_final.stac-item
2023-05-25 10:58:15	ga_ls9c_ard_3-2-1_106083_2023-05-25_final.stac-item
2023-06-06 11:18:09	ga_ls9c_ard_3-2-1_110071_2023-06-06_final.stac-item
2023-06-15 11:11:51	ga_ls9c_ard_3-2-1_109071_2023-06-15_final.stac-item
2023-06-22 11:18:02	ga_ls9c_ard_3-2-1_110071_2023-06-22_final.stac-item
2023-06-26 10:58:06	ga_ls9c_ard_3-2-1_106083_2023-06-26_final.stac-item
2023-07-01 11:12:00	ga_ls9c_ard_3-2-1_109071_2023-07-01_final.stac-item
2023-07-08 11:18:16	ga_ls9c_ard_3-2-1_110071_2023-07-08_final.stac-item
2023-07-17 11:12:08	ga_ls9c_ard_3-2-1_109071_2023-07-17_final.stac-item
2023-07-24 11:17:29	ga_ls9c_ard_3-2-1_110069_2023-07-24_final.stac-item
2023-07-24 11:18:17	ga_ls9c_ard_3-2-1_110071_2023-07-24_final.stac-item
2023-08-02 11:12:14	ga_ls9c_ard_3-2-1_109071_2023-08-02_final.stac-item
2023-08-09 11:17:41	ga_ls9c_ard_3-2-1_110069_2023-08-09_final.stac-item
2023-08-09 11:18:29	ga_ls9c_ard_3-2-1_110071_2023-08-09_final.stac-item
2023-09-03 11:12:29	ga_ls9c_ard_3-2-1_109071_2023-09-03_final.stac-item
2023-09-10 11:18:45	ga_ls9c_ard_3-2-1_110071_2023-09-10_final.stac-item
2024-02-17 11:18:07	ga_ls9c_ard_3-2-1_110069_2024-02-17_final.stac-item
2024-03-04 11:18:05	ga_ls9c_ard_3-2-1_110069_2024-03-04_final.stac-item
2024-03-15 11:04:43	ga_ls9c_ard_3-2-1_107082_2024-03-15_final.stac-item
2024-03-20 11:18:03	ga_ls9c_ard_3-2-1_110069_2024-03-20_final.stac-item
2024-03-31 11:04:34	ga_ls9c_ard_3-2-1_107082_2024-03-31_final.stac-item
2024-04-16 11:04:26	ga_ls9c_ard_3-2-1_107082_2024-04-16_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