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 09:57:45	ga_ls9c_ard_3-2-1_096082_2021-11-03_final.stac-item
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final.stac-item
2021-11-11 10:21:26	ga_ls9c_ard_3-2-1_100082_2021-11-11_final.stac-item
2021-11-16 10:23:54	ga_ls9c_ard_3-2-1_100082_2021-11-16_final.stac-item
2021-12-14 10:03:03	ga_ls9c_ard_3-2-1_097082_2021-12-14_final.stac-item
2021-12-16 09:50:40	ga_ls9c_ard_3-2-1_095082_2021-12-16_final.stac-item
2021-12-19 10:21:34	ga_ls9c_ard_3-2-1_100082_2021-12-19_final.stac-item
2021-12-23 09:56:52	ga_ls9c_ard_3-2-1_096082_2021-12-23_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-01-11 10:27:43	ga_ls9c_ard_3-2-1_101082_2022-01-11_final.stac-item
2022-01-17 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-01-17_final.stac-item
2022-01-20 10:21:33	ga_ls9c_ard_3-2-1_100082_2022-01-20_final.stac-item
2022-01-27 10:27:45	ga_ls9c_ard_3-2-1_101082_2022-01-27_final.stac-item
2022-02-05 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-02-05_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-12 10:27:42	ga_ls9c_ard_3-2-1_101082_2022-02-12_final.stac-item
2022-02-25 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-02-25_final.stac-item
2022-03-04 10:02:47	ga_ls9c_ard_3-2-1_097082_2022-03-04_final.stac-item
2022-03-22 09:50:23	ga_ls9c_ard_3-2-1_095082_2022-03-22_final.stac-item
2022-04-05 10:02:41	ga_ls9c_ard_3-2-1_097082_2022-04-05_final.stac-item
2022-04-10 10:21:12	ga_ls9c_ard_3-2-1_100082_2022-04-10_final.stac-item
2022-05-03 10:27:12	ga_ls9c_ard_3-2-1_101082_2022-05-03_final.stac-item
2022-05-07 10:02:27	ga_ls9c_ard_3-2-1_097082_2022-05-07_final.stac-item
2022-05-09 09:50:04	ga_ls9c_ard_3-2-1_095082_2022-05-09_final.stac-item
2022-05-16 09:56:09	ga_ls9c_ard_3-2-1_096082_2022-05-16_final.stac-item
2022-05-23 10:02:16	ga_ls9c_ard_3-2-1_097082_2022-05-23_final.stac-item
2022-05-25 09:49:54	ga_ls9c_ard_3-2-1_095082_2022-05-25_final.stac-item
2022-06-13 10:20:53	ga_ls9c_ard_3-2-1_100082_2022-06-13_final.stac-item
2022-06-20 10:27:12	ga_ls9c_ard_3-2-1_101082_2022-06-20_final.stac-item
2022-06-24 10:02:37	ga_ls9c_ard_3-2-1_097082_2022-06-24_final.stac-item
2022-06-29 10:21:10	ga_ls9c_ard_3-2-1_100082_2022-06-29_final.stac-item
2022-07-06 10:27:20	ga_ls9c_ard_3-2-1_101082_2022-07-06_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-07-15 10:21:05	ga_ls9c_ard_3-2-1_100082_2022-07-15_final.stac-item
2022-07-22 10:27:24	ga_ls9c_ard_3-2-1_101082_2022-07-22_final.stac-item
2022-08-11 10:02:55	ga_ls9c_ard_3-2-1_097082_2022-08-11_final.stac-item
2022-08-16 10:21:30	ga_ls9c_ard_3-2-1_100082_2022-08-16_final.stac-item
2022-08-23 10:27:42	ga_ls9c_ard_3-2-1_101082_2022-08-23_final.stac-item
2022-08-29 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-08-29_final.stac-item
2022-09-12 10:03:01	ga_ls9c_ard_3-2-1_097082_2022-09-12_final.stac-item
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final.stac-item
2022-09-17 10:21:36	ga_ls9c_ard_3-2-1_100082_2022-09-17_final.stac-item
2022-09-21 09:56:54	ga_ls9c_ard_3-2-1_096082_2022-09-21_final.stac-item
2022-09-30 09:50:45	ga_ls9c_ard_3-2-1_095082_2022-09-30_final.stac-item
2022-10-03 10:21:39	ga_ls9c_ard_3-2-1_100082_2022-10-03_final.stac-item
2022-10-19 10:21:45	ga_ls9c_ard_3-2-1_100082_2022-10-19_final.stac-item
2022-10-30 10:03:11	ga_ls9c_ard_3-2-1_097082_2022-10-30_final.stac-item
2022-11-01 09:50:49	ga_ls9c_ard_3-2-1_095082_2022-11-01_final.stac-item
2022-11-04 10:21:42	ga_ls9c_ard_3-2-1_100082_2022-11-04_final.stac-item
2022-11-08 09:57:01	ga_ls9c_ard_3-2-1_096082_2022-11-08_final.stac-item
2022-12-01 10:03:10	ga_ls9c_ard_3-2-1_097082_2022-12-01_final.stac-item
2022-12-03 09:50:48	ga_ls9c_ard_3-2-1_095082_2022-12-03_final.stac-item
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_final.stac-item
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_nrt.stac-item
2022-12-10 09:57:01	ga_ls9c_ard_3-2-1_096082_2022-12-10_final.stac-item
2022-12-13 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-12-13_final.stac-item
2022-12-17 10:03:12	ga_ls9c_ard_3-2-1_097082_2022-12-17_final.stac-item
2022-12-19 09:50:49	ga_ls9c_ard_3-2-1_095082_2022-12-19_final.stac-item
2022-12-22 10:21:42	ga_ls9c_ard_3-2-1_100082_2022-12-22_final.stac-item
2022-12-29 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-12-29_final.stac-item
2023-01-07 10:21:45	ga_ls9c_ard_3-2-1_100082_2023-01-07_final.stac-item
2023-01-14 10:27:52	ga_ls9c_ard_3-2-1_101082_2023-01-14_final.stac-item
2023-01-18 10:03:05	ga_ls9c_ard_3-2-1_097082_2023-01-18_final.stac-item
2023-01-23 10:21:38	ga_ls9c_ard_3-2-1_100082_2023-01-23_final.stac-item
2023-01-27 09:56:59	ga_ls9c_ard_3-2-1_096082_2023-01-27_final.stac-item
2023-01-30 10:27:55	ga_ls9c_ard_3-2-1_101082_2023-01-30_final.stac-item
2023-02-03 10:03:14	ga_ls9c_ard_3-2-1_097082_2023-02-03_final.stac-item
2023-02-05 09:50:54	ga_ls9c_ard_3-2-1_095082_2023-02-05_final.stac-item
2023-02-12 09:57:04	ga_ls9c_ard_3-2-1_096082_2023-02-12_final.stac-item
2023-02-19 10:03:08	ga_ls9c_ard_3-2-1_097082_2023-02-19_final.stac-item
2023-03-07 10:02:56	ga_ls9c_ard_3-2-1_097082_2023-03-07_final.stac-item
2023-03-09 09:50:32	ga_ls9c_ard_3-2-1_095082_2023-03-09_final.stac-item
2023-03-16 09:56:43	ga_ls9c_ard_3-2-1_096082_2023-03-16_final.stac-item
2023-03-19 10:27:36	ga_ls9c_ard_3-2-1_101082_2023-03-19_final.stac-item
2023-03-23 10:02:51	ga_ls9c_ard_3-2-1_097082_2023-03-23_final.stac-item
2023-03-25 09:50:27	ga_ls9c_ard_3-2-1_095082_2023-03-25_final.stac-item
2023-04-01 09:56:32	ga_ls9c_ard_3-2-1_096082_2023-04-01_final.stac-item
2023-04-10 09:50:18	ga_ls9c_ard_3-2-1_095082_2023-04-10_final.stac-item
2023-04-13 10:21:10	ga_ls9c_ard_3-2-1_100082_2023-04-13_final.stac-item
2023-04-17 09:56:26	ga_ls9c_ard_3-2-1_096082_2023-04-17_final.stac-item
2023-04-20 10:27:20	ga_ls9c_ard_3-2-1_101082_2023-04-20_final.stac-item
2023-04-24 10:02:35	ga_ls9c_ard_3-2-1_097082_2023-04-24_final.stac-item
2023-04-26 09:50:12	ga_ls9c_ard_3-2-1_095082_2023-04-26_final.stac-item
2023-05-03 09:56:15	ga_ls9c_ard_3-2-1_096082_2023-05-03_final.stac-item
2023-05-10 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-05-10_final.stac-item
2023-05-12 09:50:02	ga_ls9c_ard_3-2-1_095082_2023-05-12_final.stac-item
2023-05-15 10:20:55	ga_ls9c_ard_3-2-1_100082_2023-05-15_final.stac-item
2023-05-19 09:56:08	ga_ls9c_ard_3-2-1_096082_2023-05-19_final.stac-item
2023-05-22 10:27:00	ga_ls9c_ard_3-2-1_101082_2023-05-22_final.stac-item
2023-05-26 10:02:14	ga_ls9c_ard_3-2-1_097082_2023-05-26_final.stac-item
2023-05-28 09:49:52	ga_ls9c_ard_3-2-1_095082_2023-05-28_final.stac-item
2023-06-04 09:56:02	ga_ls9c_ard_3-2-1_096082_2023-06-04_final.stac-item
2023-06-07 10:26:54	ga_ls9c_ard_3-2-1_101082_2023-06-07_final.stac-item
2023-06-11 10:02:08	ga_ls9c_ard_3-2-1_097082_2023-06-11_final.stac-item
2023-06-20 09:55:54	ga_ls9c_ard_3-2-1_096082_2023-06-20_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-27 10:02:07	ga_ls9c_ard_3-2-1_097082_2023-06-27_final.stac-item
2023-06-29 09:49:49	ga_ls9c_ard_3-2-1_095082_2023-06-29_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-06 09:56:07	ga_ls9c_ard_3-2-1_096082_2023-07-06_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