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
2021-11-05 09:39:00	ga_ls9c_ard_3-2-1_093082_2021-11-05_final.stac-item
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final.stac-item
2021-11-10 09:41:29	ga_ls9c_ard_3-2-1_094082_2021-11-10_final.stac-item
2021-11-22 11:06:19	ga_ls9c_ard_3-2-1_107082_2021-11-22_final.stac-item
2021-12-04 11:04:58	ga_ls9c_ard_3-2-1_107082_2021-12-04_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
2021-12-18 09:38:18	ga_ls9c_ard_3-2-1_093082_2021-12-18_final.stac-item
2021-12-23 09:56:52	ga_ls9c_ard_3-2-1_096082_2021-12-23_final.stac-item
2021-12-27 11:11:02	ga_ls9c_ard_3-2-1_108082_2021-12-27_final.stac-item
2022-01-12 11:10:58	ga_ls9c_ard_3-2-1_108082_2022-01-12_final.stac-item
2022-01-28 11:11:01	ga_ls9c_ard_3-2-1_108082_2022-01-28_final.stac-item
2022-02-04 09:38:18	ga_ls9c_ard_3-2-1_093082_2022-02-04_final.stac-item
2022-02-11 09:44:27	ga_ls9c_ard_3-2-1_094082_2022-02-11_final.stac-item
2022-02-25 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-02-25_final.stac-item
2022-03-01 11:10:46	ga_ls9c_ard_3-2-1_108082_2022-03-01_final.stac-item
2022-03-06 11:29:18	ga_ls9c_ard_3-2-1_111082_2022-03-06_final.stac-item
2022-05-29 11:04:04	ga_ls9c_ard_3-2-1_107082_2022-05-29_final.stac-item
2022-06-14 11:04:10	ga_ls9c_ard_3-2-1_107082_2022-06-14_final.stac-item
2022-06-19 09:43:54	ga_ls9c_ard_3-2-1_094082_2022-06-19_final.stac-item
2022-06-24 10:02:37	ga_ls9c_ard_3-2-1_097082_2022-06-24_final.stac-item
2022-06-30 11:04:26	ga_ls9c_ard_3-2-1_107082_2022-06-30_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-07 11:10:35	ga_ls9c_ard_3-2-1_108082_2022-07-07_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-07-21 09:44:07	ga_ls9c_ard_3-2-1_094082_2022-07-21_final.stac-item
2022-07-23 11:10:41	ga_ls9c_ard_3-2-1_108082_2022-07-23_final.stac-item
2022-07-30 09:38:04	ga_ls9c_ard_3-2-1_093082_2022-07-30_final.stac-item
2022-08-01 11:04:37	ga_ls9c_ard_3-2-1_107082_2022-08-01_final.stac-item
2022-08-11 10:02:55	ga_ls9c_ard_3-2-1_097082_2022-08-11_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-08-17 11:04:46	ga_ls9c_ard_3-2-1_107082_2022-08-17_final.stac-item
2022-08-29 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-08-29_final.stac-item
2022-09-07 09:44:26	ga_ls9c_ard_3-2-1_094082_2022-09-07_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
2022-09-14 11:29:33	ga_ls9c_ard_3-2-1_111082_2022-09-14_final.stac-item
2022-09-16 09:38:20	ga_ls9c_ard_3-2-1_093082_2022-09-16_final.stac-item
2022-09-18 11:04:52	ga_ls9c_ard_3-2-1_107082_2022-09-18_final.stac-item
2022-09-21 09:56:54	ga_ls9c_ard_3-2-1_096082_2022-09-21_final.stac-item
2022-09-27 10:58:44	ga_ls9c_ard_3-2-1_106082_2022-09-27_final.stac-item
2022-09-30 09:50:45	ga_ls9c_ard_3-2-1_095082_2022-09-30_final.stac-item
2022-09-30 11:29:38	ga_ls9c_ard_3-2-1_111082_2022-09-30_final.stac-item
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final.stac-item
2022-10-11 11:11:08	ga_ls9c_ard_3-2-1_108082_2022-10-11_final.stac-item
2022-10-13 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-10-13_final.stac-item
2022-10-18 09:38:29	ga_ls9c_ard_3-2-1_093082_2022-10-18_final.stac-item
2022-10-27 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-10-27_final.stac-item
2022-10-29 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-10-29_final.stac-item
2022-10-30 10:03:11	ga_ls9c_ard_3-2-1_097082_2022-10-30_final.stac-item
2022-11-03 09:38:26	ga_ls9c_ard_3-2-1_093082_2022-11-03_final.stac-item
2022-11-05 11:04:58	ga_ls9c_ard_3-2-1_107082_2022-11-05_final.stac-item
2022-11-05 11:04:58	ga_ls9c_ard_3-2-1_107082_2022-11-05_interim.stac-item
2022-11-08 09:57:01	ga_ls9c_ard_3-2-1_096082_2022-11-08_final.stac-item
2022-11-12 11:11:12	ga_ls9c_ard_3-2-1_108082_2022-11-12_final.stac-item
2022-11-28 11:11:10	ga_ls9c_ard_3-2-1_108082_2022-11-28_final.stac-item
2022-12-07 11:05:00	ga_ls9c_ard_3-2-1_107082_2022-12-07_final.stac-item
2022-12-07 11:05:00	ga_ls9c_ard_3-2-1_107082_2022-12-07_nrt.stac-item
2022-12-10 09:57:01	ga_ls9c_ard_3-2-1_096082_2022-12-10_final.stac-item
2022-12-14 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-14_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
2022-12-23 11:04:57	ga_ls9c_ard_3-2-1_107082_2022-12-23_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-08 11:05:00	ga_ls9c_ard_3-2-1_107082_2023-01-08_final.stac-item
2023-01-13 09:44:38	ga_ls9c_ard_3-2-1_094082_2023-01-13_final.stac-item
2023-01-17 10:58:44	ga_ls9c_ard_3-2-1_106082_2023-01-17_final.stac-item
2023-01-24 11:04:54	ga_ls9c_ard_3-2-1_107082_2023-01-24_final.stac-item
2023-01-29 09:44:39	ga_ls9c_ard_3-2-1_094082_2023-01-29_final.stac-item
2023-01-31 11:11:12	ga_ls9c_ard_3-2-1_108082_2023-01-31_final.stac-item
2023-02-05 09:50:54	ga_ls9c_ard_3-2-1_095082_2023-02-05_final.stac-item
2023-02-09 11:05:04	ga_ls9c_ard_3-2-1_107082_2023-02-09_final.stac-item
2023-03-27 09:38:03	ga_ls9c_ard_3-2-1_093082_2023-03-27_final.stac-item
2023-04-19 09:44:04	ga_ls9c_ard_3-2-1_094082_2023-04-19_final.stac-item
2023-04-28 09:37:48	ga_ls9c_ard_3-2-1_093082_2023-04-28_final.stac-item
2023-05-10 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-05-10_final.stac-item
2023-05-25 10:57:51	ga_ls9c_ard_3-2-1_106082_2023-05-25_final.stac-item
2023-06-20 09:55:54	ga_ls9c_ard_3-2-1_096082_2023-06-20_final.stac-item
2023-06-22 09:43:32	ga_ls9c_ard_3-2-1_094082_2023-06-22_final.stac-item
2023-06-24 11:10:03	ga_ls9c_ard_3-2-1_108082_2023-06-24_final.stac-item
2023-06-26 10:57:42	ga_ls9c_ard_3-2-1_106082_2023-06-26_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
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-07-03 11:04:03	ga_ls9c_ard_3-2-1_107082_2023-07-03_final.stac-item
2023-07-06 09:56:07	ga_ls9c_ard_3-2-1_096082_2023-07-06_final.stac-item
2023-07-17 09:37:38	ga_ls9c_ard_3-2-1_093082_2023-07-17_final.stac-item
2023-07-19 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-07-19_final.stac-item
2023-07-26 11:10:20	ga_ls9c_ard_3-2-1_108082_2023-07-26_final.stac-item
2023-08-02 09:37:45	ga_ls9c_ard_3-2-1_093082_2023-08-02_final.stac-item
2023-08-04 11:04:17	ga_ls9c_ard_3-2-1_107082_2023-08-04_final.stac-item
2023-08-11 11:10:31	ga_ls9c_ard_3-2-1_108082_2023-08-11_final.stac-item
2023-08-18 09:37:48	ga_ls9c_ard_3-2-1_093082_2023-08-18_final.stac-item
2023-08-27 11:10:38	ga_ls9c_ard_3-2-1_108082_2023-08-27_final.stac-item
2023-09-05 11:04:32	ga_ls9c_ard_3-2-1_107082_2023-09-05_final.stac-item
2023-09-28 11:10:44	ga_ls9c_ard_3-2-1_108082_2023-09-28_final.stac-item
2023-11-15 11:10:54	ga_ls9c_ard_3-2-1_108082_2023-11-15_final.stac-item
2023-11-24 11:04:51	ga_ls9c_ard_3-2-1_107082_2023-11-24_final.stac-item
2023-12-26 11:04:54	ga_ls9c_ard_3-2-1_107082_2023-12-26_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