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
2021-11-03 09:58:56	ga_ls9c_ard_3-2-1_096085_2021-11-03_final.stac-item
2021-12-05 10:10:32	ga_ls9c_ard_3-2-1_098085_2021-12-05_final.stac-item
2021-12-12 10:16:38	ga_ls9c_ard_3-2-1_099085_2021-12-12_final.stac-item
2021-12-16 09:51:52	ga_ls9c_ard_3-2-1_095085_2021-12-16_final.stac-item
2021-12-22 09:14:48	ga_ls9c_ard_3-2-1_089085_2021-12-21_final.stac-item
2022-01-07 09:14:46	ga_ls9c_ard_3-2-1_089085_2022-01-06_final.stac-item
2022-01-26 11:24:34	ga_ls9c_ard_3-2-1_110085_2022-01-26_final.stac-item
2022-02-07 10:10:23	ga_ls9c_ard_3-2-1_098085_2022-02-07_final.stac-item
2022-02-08 09:14:46	ga_ls9c_ard_3-2-1_089085_2022-02-07_final.stac-item
2022-02-14 10:16:31	ga_ls9c_ard_3-2-1_099085_2022-02-14_final.stac-item
2022-02-24 09:14:37	ga_ls9c_ard_3-2-1_089085_2022-02-23_final.stac-item
2022-02-27 11:24:21	ga_ls9c_ard_3-2-1_110085_2022-02-27_final.stac-item
2022-03-11 10:10:10	ga_ls9c_ard_3-2-1_098085_2022-03-11_final.stac-item
2022-03-12 09:14:32	ga_ls9c_ard_3-2-1_089085_2022-03-11_final.stac-item
2022-03-22 09:51:34	ga_ls9c_ard_3-2-1_095085_2022-03-22_final.stac-item
2022-03-27 10:10:04	ga_ls9c_ard_3-2-1_098085_2022-03-27_final.stac-item
2022-03-28 09:14:27	ga_ls9c_ard_3-2-1_089085_2022-03-27_final.stac-item
2022-04-03 10:16:15	ga_ls9c_ard_3-2-1_099085_2022-04-03_final.stac-item
2022-04-05 10:03:53	ga_ls9c_ard_3-2-1_097085_2022-04-05_final.stac-item
2022-04-13 09:14:23	ga_ls9c_ard_3-2-1_089085_2022-04-12_final.stac-item
2022-04-19 10:16:06	ga_ls9c_ard_3-2-1_099085_2022-04-19_final.stac-item
2022-04-21 10:03:43	ga_ls9c_ard_3-2-1_097085_2022-04-21_final.stac-item
2022-04-28 10:09:53	ga_ls9c_ard_3-2-1_098085_2022-04-28_final.stac-item
2022-04-29 09:14:16	ga_ls9c_ard_3-2-1_089085_2022-04-28_final.stac-item
2022-05-02 11:24:02	ga_ls9c_ard_3-2-1_110085_2022-05-02_final.stac-item
2022-05-06 09:20:24	ga_ls9c_ard_3-2-1_090085_2022-05-05_final.stac-item
2022-05-13 09:26:30	ga_ls9c_ard_3-2-1_091085_2022-05-12_final.stac-item
2022-05-14 10:09:44	ga_ls9c_ard_3-2-1_098085_2022-05-14_final.stac-item
2022-05-15 09:14:06	ga_ls9c_ard_3-2-1_089085_2022-05-14_final.stac-item
2022-05-22 09:20:12	ga_ls9c_ard_3-2-1_090085_2022-05-21_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-05-31 09:14:02	ga_ls9c_ard_3-2-1_089085_2022-05-30_final.stac-item
2022-06-19 11:23:59	ga_ls9c_ard_3-2-1_110085_2022-06-19_final.stac-item
2022-06-26 09:51:29	ga_ls9c_ard_3-2-1_095085_2022-06-26_final.stac-item
2022-07-17 10:09:58	ga_ls9c_ard_3-2-1_098085_2022-07-17_final.stac-item
2022-07-18 09:14:22	ga_ls9c_ard_3-2-1_089085_2022-07-17_final.stac-item
2022-07-19 09:57:39	ga_ls9c_ard_3-2-1_096085_2022-07-19_final.stac-item
2022-07-21 11:24:12	ga_ls9c_ard_3-2-1_110085_2022-07-21_final.stac-item
2022-08-04 09:57:52	ga_ls9c_ard_3-2-1_096085_2022-08-04_final.stac-item
2022-08-06 11:24:25	ga_ls9c_ard_3-2-1_110085_2022-08-06_final.stac-item
2022-08-11 10:04:07	ga_ls9c_ard_3-2-1_097085_2022-08-11_final.stac-item
2022-08-18 10:10:21	ga_ls9c_ard_3-2-1_098085_2022-08-18_final.stac-item
2022-08-25 10:16:33	ga_ls9c_ard_3-2-1_099085_2022-08-25_final.stac-item
2022-09-07 11:24:31	ga_ls9c_ard_3-2-1_110085_2022-09-07_final.stac-item
2022-09-10 10:16:33	ga_ls9c_ard_3-2-1_099085_2022-09-10_final.stac-item
2022-09-19 10:10:27	ga_ls9c_ard_3-2-1_098085_2022-09-19_final.stac-item
2022-09-26 10:16:40	ga_ls9c_ard_3-2-1_099085_2022-09-26_final.stac-item
2022-10-05 10:10:29	ga_ls9c_ard_3-2-1_098085_2022-10-05_final.stac-item
2022-10-12 10:16:43	ga_ls9c_ard_3-2-1_099085_2022-10-12_final.stac-item
2022-10-22 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-10-21_final.stac-item
2022-11-01 09:52:01	ga_ls9c_ard_3-2-1_095085_2022-11-01_final.stac-item
2022-11-06 10:10:33	ga_ls9c_ard_3-2-1_098085_2022-11-06_final.stac-item
2022-11-06 10:10:33	ga_ls9c_ard_3-2-1_098085_2022-11-06_nrt.stac-item
2022-11-10 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-11-10_final.stac-item
2022-11-17 09:52:04	ga_ls9c_ard_3-2-1_095085_2022-11-17_final.stac-item
2022-11-22 10:10:36	ga_ls9c_ard_3-2-1_098085_2022-11-22_final.stac-item
2022-11-26 11:24:44	ga_ls9c_ard_3-2-1_110085_2022-11-26_final.stac-item
2022-12-09 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-12-08_final.stac-item
2022-12-12 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-12-12_final.stac-item
2022-12-17 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-12-17_final.stac-item
2022-12-26 09:58:11	ga_ls9c_ard_3-2-1_096085_2022-12-26_final.stac-item
2022-12-28 11:24:43	ga_ls9c_ard_3-2-1_110085_2022-12-28_final.stac-item
2022-12-31 10:16:45	ga_ls9c_ard_3-2-1_099085_2022-12-31_final.stac-item
2023-01-09 10:10:35	ga_ls9c_ard_3-2-1_098085_2023-01-09_final.stac-item
2023-01-10 09:14:57	ga_ls9c_ard_3-2-1_089085_2023-01-09_final.stac-item
2023-01-13 11:24:42	ga_ls9c_ard_3-2-1_110085_2023-01-13_final.stac-item
2023-01-18 10:04:17	ga_ls9c_ard_3-2-1_097085_2023-01-18_final.stac-item
2023-01-25 10:10:30	ga_ls9c_ard_3-2-1_098085_2023-01-25_final.stac-item
2023-01-26 09:14:54	ga_ls9c_ard_3-2-1_089085_2023-01-25_final.stac-item
2023-01-29 11:24:44	ga_ls9c_ard_3-2-1_110085_2023-01-29_final.stac-item
2023-02-01 10:16:47	ga_ls9c_ard_3-2-1_099085_2023-02-01_final.stac-item
2023-02-11 09:15:01	ga_ls9c_ard_3-2-1_089085_2023-02-10_final.stac-item
2023-02-12 09:58:16	ga_ls9c_ard_3-2-1_096085_2023-02-12_final.stac-item
2023-02-14 11:24:46	ga_ls9c_ard_3-2-1_110085_2023-02-14_final.stac-item
2023-02-19 10:04:20	ga_ls9c_ard_3-2-1_097085_2023-02-19_final.stac-item
2023-02-21 09:51:56	ga_ls9c_ard_3-2-1_095085_2023-02-21_final.stac-item
2023-02-26 10:10:24	ga_ls9c_ard_3-2-1_098085_2023-02-26_final.stac-item
2023-02-27 09:14:47	ga_ls9c_ard_3-2-1_089085_2023-02-26_final.stac-item
2023-03-07 10:04:08	ga_ls9c_ard_3-2-1_097085_2023-03-07_final.stac-item
2023-03-09 09:51:44	ga_ls9c_ard_3-2-1_095085_2023-03-09_final.stac-item
2023-03-15 09:14:40	ga_ls9c_ard_3-2-1_089085_2023-03-14_final.stac-item
2023-03-16 09:57:55	ga_ls9c_ard_3-2-1_096085_2023-03-16_final.stac-item
2023-03-18 11:24:26	ga_ls9c_ard_3-2-1_110085_2023-03-18_final.stac-item
2023-03-21 10:16:26	ga_ls9c_ard_3-2-1_099085_2023-03-21_final.stac-item
2023-03-25 09:51:39	ga_ls9c_ard_3-2-1_095085_2023-03-25_final.stac-item
2023-03-29 09:26:50	ga_ls9c_ard_3-2-1_091085_2023-03-28_final.stac-item
2023-03-31 09:14:28	ga_ls9c_ard_3-2-1_089085_2023-03-30_final.stac-item
2023-04-01 09:57:44	ga_ls9c_ard_3-2-1_096085_2023-04-01_final.stac-item
2023-04-16 09:14:21	ga_ls9c_ard_3-2-1_089085_2023-04-15_final.stac-item
2023-04-17 09:57:37	ga_ls9c_ard_3-2-1_096085_2023-04-17_final.stac-item
2023-04-19 11:24:09	ga_ls9c_ard_3-2-1_110085_2023-04-19_final.stac-item
2023-05-02 09:14:13	ga_ls9c_ard_3-2-1_089085_2023-05-01_final.stac-item
2023-05-18 09:14:05	ga_ls9c_ard_3-2-1_089085_2023-05-17_final.stac-item
2023-06-09 10:15:43	ga_ls9c_ard_3-2-1_099085_2023-06-09_final.stac-item
2023-06-19 09:13:50	ga_ls9c_ard_3-2-1_089085_2023-06-18_final.stac-item
2023-07-08 11:23:51	ga_ls9c_ard_3-2-1_110085_2023-07-08_final.stac-item
2023-07-20 10:09:44	ga_ls9c_ard_3-2-1_098085_2023-07-20_final.stac-item
2023-07-24 11:23:52	ga_ls9c_ard_3-2-1_110085_2023-07-24_final.stac-item
2024-05-02 09:26:28	ga_ls9c_ard_3-2-1_091085_2024-05-01_final.stac-item
2024-05-04 09:14:07	ga_ls9c_ard_3-2-1_089085_2024-05-03_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