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 09:57:50	ga_ls9c_ard_3-2-1_097076_2021-11-08_final.stac-item
2021-11-08 09:58:14	ga_ls9c_ard_3-2-1_097077_2021-11-08_final.stac-item
2021-11-18 10:02:46	ga_ls9c_ard_3-2-1_097076_2021-11-18_final.stac-item
2021-11-25 09:50:50	ga_ls9c_ard_3-2-1_095087_2021-11-25_final.stac-item
2021-12-07 09:54:57	ga_ls9c_ard_3-2-1_096077_2021-12-07_final.stac-item
2021-12-18 09:40:42	ga_ls9c_ard_3-2-1_093088_2021-12-18_final.stac-item
2021-12-23 09:54:52	ga_ls9c_ard_3-2-1_096077_2021-12-23_final.stac-item
2021-12-30 10:00:39	ga_ls9c_ard_3-2-1_097076_2021-12-30_final.stac-item
2022-01-03 09:40:42	ga_ls9c_ard_3-2-1_093088_2022-01-03_final.stac-item
2022-01-15 10:01:00	ga_ls9c_ard_3-2-1_097077_2022-01-15_final.stac-item
2022-01-19 09:40:41	ga_ls9c_ard_3-2-1_093088_2022-01-19_final.stac-item
2022-01-31 10:01:02	ga_ls9c_ard_3-2-1_097077_2022-01-31_final.stac-item
2022-02-04 09:40:42	ga_ls9c_ard_3-2-1_093088_2022-02-04_final.stac-item
2022-02-09 09:54:49	ga_ls9c_ard_3-2-1_096077_2022-02-09_final.stac-item
2022-02-16 10:00:57	ga_ls9c_ard_3-2-1_097077_2022-02-16_final.stac-item
2022-04-05 10:00:42	ga_ls9c_ard_3-2-1_097077_2022-04-05_final.stac-item
2022-04-09 09:40:20	ga_ls9c_ard_3-2-1_093088_2022-04-09_final.stac-item
2022-05-07 10:00:03	ga_ls9c_ard_3-2-1_097076_2022-05-07_final.stac-item
2022-05-07 10:00:27	ga_ls9c_ard_3-2-1_097077_2022-05-07_final.stac-item
2022-05-11 09:40:05	ga_ls9c_ard_3-2-1_093088_2022-05-11_final.stac-item
2022-05-16 09:54:09	ga_ls9c_ard_3-2-1_096077_2022-05-16_final.stac-item
2022-05-23 09:59:52	ga_ls9c_ard_3-2-1_097076_2022-05-23_final.stac-item
2022-06-08 09:59:54	ga_ls9c_ard_3-2-1_097076_2022-06-08_final.stac-item
2022-06-24 10:00:13	ga_ls9c_ard_3-2-1_097076_2022-06-24_final.stac-item
2022-06-24 10:00:37	ga_ls9c_ard_3-2-1_097077_2022-06-24_final.stac-item
2022-06-28 09:40:19	ga_ls9c_ard_3-2-1_093088_2022-06-28_final.stac-item
2022-07-03 09:54:27	ga_ls9c_ard_3-2-1_096077_2022-07-03_final.stac-item
2022-07-10 10:00:11	ga_ls9c_ard_3-2-1_097076_2022-07-10_final.stac-item
2022-07-10 10:00:35	ga_ls9c_ard_3-2-1_097077_2022-07-10_final.stac-item
2022-07-19 09:54:27	ga_ls9c_ard_3-2-1_096077_2022-07-19_final.stac-item
2022-07-26 10:00:45	ga_ls9c_ard_3-2-1_097077_2022-07-26_final.stac-item
2022-08-11 10:00:32	ga_ls9c_ard_3-2-1_097076_2022-08-11_final.stac-item
2022-08-11 10:00:56	ga_ls9c_ard_3-2-1_097077_2022-08-11_final.stac-item
2022-08-27 10:00:36	ga_ls9c_ard_3-2-1_097076_2022-08-27_final.stac-item
2022-08-31 09:40:40	ga_ls9c_ard_3-2-1_093088_2022-08-31_final.stac-item
2022-09-05 09:54:48	ga_ls9c_ard_3-2-1_096077_2022-09-05_final.stac-item
2022-09-12 10:00:37	ga_ls9c_ard_3-2-1_097076_2022-09-12_final.stac-item
2022-09-12 10:01:01	ga_ls9c_ard_3-2-1_097077_2022-09-12_final.stac-item
2022-09-21 09:54:55	ga_ls9c_ard_3-2-1_096077_2022-09-21_final.stac-item
2022-09-28 10:00:43	ga_ls9c_ard_3-2-1_097076_2022-09-28_final.stac-item
2022-09-28 10:01:07	ga_ls9c_ard_3-2-1_097077_2022-09-28_final.stac-item
2022-09-30 09:51:57	ga_ls9c_ard_3-2-1_095085_2022-09-30_final.stac-item
2022-10-14 10:00:47	ga_ls9c_ard_3-2-1_097076_2022-10-14_final.stac-item
2022-10-14 10:01:11	ga_ls9c_ard_3-2-1_097077_2022-10-14_final.stac-item
2022-10-30 10:00:48	ga_ls9c_ard_3-2-1_097076_2022-10-30_final.stac-item
2022-11-08 09:55:01	ga_ls9c_ard_3-2-1_096077_2022-11-08_final.stac-item
2022-11-15 10:00:50	ga_ls9c_ard_3-2-1_097076_2022-11-15_final.stac-item
2022-11-15 10:01:14	ga_ls9c_ard_3-2-1_097077_2022-11-15_final.stac-item
2022-11-24 09:55:02	ga_ls9c_ard_3-2-1_096077_2022-11-24_final.stac-item
2022-12-01 10:00:46	ga_ls9c_ard_3-2-1_097076_2022-12-01_final.stac-item
2022-12-01 10:01:10	ga_ls9c_ard_3-2-1_097077_2022-12-01_final.stac-item
2022-12-10 09:55:02	ga_ls9c_ard_3-2-1_096077_2022-12-10_final.stac-item
2022-12-17 10:00:48	ga_ls9c_ard_3-2-1_097076_2022-12-17_final.stac-item
2022-12-17 10:01:12	ga_ls9c_ard_3-2-1_097077_2022-12-17_final.stac-item
2023-01-02 10:00:49	ga_ls9c_ard_3-2-1_097076_2023-01-02_final.stac-item
2023-01-18 10:00:41	ga_ls9c_ard_3-2-1_097076_2023-01-18_final.stac-item
2023-01-27 09:54:59	ga_ls9c_ard_3-2-1_096077_2023-01-27_final.stac-item
2023-02-03 10:00:51	ga_ls9c_ard_3-2-1_097076_2023-02-03_final.stac-item
2023-02-12 09:55:05	ga_ls9c_ard_3-2-1_096077_2023-02-12_final.stac-item
2023-02-19 10:01:09	ga_ls9c_ard_3-2-1_097077_2023-02-19_final.stac-item
2023-03-07 10:00:33	ga_ls9c_ard_3-2-1_097076_2023-03-07_final.stac-item
2023-03-18 09:46:21	ga_ls9c_ard_3-2-1_094087_2023-03-18_final.stac-item
2023-03-23 10:00:27	ga_ls9c_ard_3-2-1_097076_2023-03-23_final.stac-item
2023-04-08 10:00:17	ga_ls9c_ard_3-2-1_097076_2023-04-08_final.stac-item
2023-04-08 10:00:41	ga_ls9c_ard_3-2-1_097077_2023-04-08_final.stac-item
2023-04-19 09:46:04	ga_ls9c_ard_3-2-1_094087_2023-04-19_final.stac-item
2023-04-24 10:00:11	ga_ls9c_ard_3-2-1_097076_2023-04-24_final.stac-item
2023-04-24 10:00:35	ga_ls9c_ard_3-2-1_097077_2023-04-24_final.stac-item
2023-05-03 09:54:15	ga_ls9c_ard_3-2-1_096077_2023-05-03_final.stac-item
2023-05-10 10:00:00	ga_ls9c_ard_3-2-1_097076_2023-05-10_final.stac-item
2023-05-10 10:00:24	ga_ls9c_ard_3-2-1_097077_2023-05-10_final.stac-item
2023-05-19 09:54:09	ga_ls9c_ard_3-2-1_096077_2023-05-19_final.stac-item
2023-05-26 09:59:50	ga_ls9c_ard_3-2-1_097076_2023-05-26_final.stac-item
2023-05-26 10:00:14	ga_ls9c_ard_3-2-1_097077_2023-05-26_final.stac-item
2023-06-11 09:59:45	ga_ls9c_ard_3-2-1_097076_2023-06-11_final.stac-item
2023-06-11 10:00:09	ga_ls9c_ard_3-2-1_097077_2023-06-11_final.stac-item
2023-06-27 09:59:43	ga_ls9c_ard_3-2-1_097076_2023-06-27_final.stac-item
2023-07-13 09:59:57	ga_ls9c_ard_3-2-1_097076_2023-07-13_final.stac-item
2023-08-02 09:40:08	ga_ls9c_ard_3-2-1_093088_2023-08-02_final.stac-item
2023-08-07 09:54:20	ga_ls9c_ard_3-2-1_096077_2023-08-07_final.stac-item
2023-08-30 10:00:41	ga_ls9c_ard_3-2-1_097077_2023-08-30_final.stac-item
2023-09-03 09:40:23	ga_ls9c_ard_3-2-1_093088_2023-09-03_final.stac-item
2023-09-08 09:54:36	ga_ls9c_ard_3-2-1_096077_2023-09-08_final.stac-item
2023-09-15 10:00:26	ga_ls9c_ard_3-2-1_097076_2023-09-15_final.stac-item
2023-09-24 09:54:37	ga_ls9c_ard_3-2-1_096077_2023-09-24_final.stac-item
2023-10-01 10:00:25	ga_ls9c_ard_3-2-1_097076_2023-10-01_final.stac-item
2023-10-10 09:54:44	ga_ls9c_ard_3-2-1_096077_2023-10-10_final.stac-item
2023-10-17 10:00:36	ga_ls9c_ard_3-2-1_097076_2023-10-17_final.stac-item
2023-10-26 09:54:48	ga_ls9c_ard_3-2-1_096077_2023-10-26_final.stac-item
2023-11-11 09:54:45	ga_ls9c_ard_3-2-1_096077_2023-11-11_final.stac-item
2023-11-27 09:54:53	ga_ls9c_ard_3-2-1_096077_2023-11-27_final.stac-item
2023-12-13 09:54:52	ga_ls9c_ard_3-2-1_096077_2023-12-13_final.stac-item
2023-12-20 10:01:06	ga_ls9c_ard_3-2-1_097077_2023-12-20_final.stac-item
2024-01-21 10:01:00	ga_ls9c_ard_3-2-1_097077_2024-01-21_final.stac-item
2024-01-30 09:54:51	ga_ls9c_ard_3-2-1_096077_2024-01-30_final.stac-item
2024-02-10 09:40:44	ga_ls9c_ard_3-2-1_093088_2024-02-10_final.stac-item
2024-02-26 09:40:32	ga_ls9c_ard_3-2-1_093088_2024-02-26_final.stac-item
2024-03-13 09:40:35	ga_ls9c_ard_3-2-1_093088_2024-03-13_final.stac-item
2024-03-29 09:40:26	ga_ls9c_ard_3-2-1_093088_2024-03-29_final.stac-item
2024-04-14 09:40:20	ga_ls9c_ard_3-2-1_093088_2024-04-14_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