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 09:39:00	ga_ls9c_ard_3-2-1_093082_2021-11-05_final.stac-item
2021-11-10 09:41:29	ga_ls9c_ard_3-2-1_094082_2021-11-10_final.stac-item
2021-12-05 10:09:20	ga_ls9c_ard_3-2-1_098082_2021-12-05_final.stac-item
2021-12-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2021-12-08_final.stac-item
2021-12-17 10:33:55	ga_ls9c_ard_3-2-1_102082_2021-12-17_final.stac-item
2021-12-18 09:38:18	ga_ls9c_ard_3-2-1_093082_2021-12-18_final.stac-item
2021-12-24 10:40:07	ga_ls9c_ard_3-2-1_103082_2021-12-24_final.stac-item
2022-01-02 10:33:56	ga_ls9c_ard_3-2-1_102082_2022-01-02_final.stac-item
2022-01-06 10:09:12	ga_ls9c_ard_3-2-1_098082_2022-01-06_final.stac-item
2022-01-09 10:40:05	ga_ls9c_ard_3-2-1_103082_2022-01-09_final.stac-item
2022-01-10 09:44:28	ga_ls9c_ard_3-2-1_094082_2022-01-10_final.stac-item
2022-01-18 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-01-18_final.stac-item
2022-01-22 10:09:12	ga_ls9c_ard_3-2-1_098082_2022-01-22_final.stac-item
2022-02-04 09:38:18	ga_ls9c_ard_3-2-1_093082_2022-02-04_final.stac-item
2022-02-07 10:09:11	ga_ls9c_ard_3-2-1_098082_2022-02-07_final.stac-item
2022-02-10 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-02-10_final.stac-item
2022-02-11 09:44:27	ga_ls9c_ard_3-2-1_094082_2022-02-11_final.stac-item
2022-02-19 10:33:49	ga_ls9c_ard_3-2-1_102082_2022-02-19_final.stac-item
2022-02-23 10:09:03	ga_ls9c_ard_3-2-1_098082_2022-02-23_final.stac-item
2022-03-02 10:15:08	ga_ls9c_ard_3-2-1_099082_2022-03-02_final.stac-item
2022-03-23 10:33:38	ga_ls9c_ard_3-2-1_102082_2022-03-23_final.stac-item
2022-03-24 09:38:00	ga_ls9c_ard_3-2-1_093082_2022-03-24_final.stac-item
2022-03-27 10:08:52	ga_ls9c_ard_3-2-1_098082_2022-03-27_final.stac-item
2022-04-08 10:33:34	ga_ls9c_ard_3-2-1_102082_2022-04-08_final.stac-item
2022-04-16 09:44:03	ga_ls9c_ard_3-2-1_094082_2022-04-16_final.stac-item
2022-04-28 10:08:41	ga_ls9c_ard_3-2-1_098082_2022-04-28_final.stac-item
2022-05-01 10:39:34	ga_ls9c_ard_3-2-1_103082_2022-05-01_final.stac-item
2022-05-05 10:14:49	ga_ls9c_ard_3-2-1_099082_2022-05-05_final.stac-item
2022-05-10 10:33:19	ga_ls9c_ard_3-2-1_102082_2022-05-10_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-18 09:43:45	ga_ls9c_ard_3-2-1_094082_2022-05-18_final.stac-item
2022-05-21 10:14:37	ga_ls9c_ard_3-2-1_099082_2022-05-21_final.stac-item
2022-05-26 10:33:10	ga_ls9c_ard_3-2-1_102082_2022-05-26_final.stac-item
2022-06-02 10:39:22	ga_ls9c_ard_3-2-1_103082_2022-06-02_final.stac-item
2022-06-19 09:43:54	ga_ls9c_ard_3-2-1_094082_2022-06-19_final.stac-item
2022-07-01 10:08:49	ga_ls9c_ard_3-2-1_098082_2022-07-01_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-08 10:14:57	ga_ls9c_ard_3-2-1_099082_2022-07-08_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-21 09:44:07	ga_ls9c_ard_3-2-1_094082_2022-07-21_final.stac-item
2022-07-30 09:38:04	ga_ls9c_ard_3-2-1_093082_2022-07-30_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-08-30 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-08-30_final.stac-item
2022-09-03 10:09:10	ga_ls9c_ard_3-2-1_098082_2022-09-03_final.stac-item
2022-09-07 09:44:26	ga_ls9c_ard_3-2-1_094082_2022-09-07_final.stac-item
2022-09-15 10:33:57	ga_ls9c_ard_3-2-1_102082_2022-09-15_final.stac-item
2022-09-16 09:38:20	ga_ls9c_ard_3-2-1_093082_2022-09-16_final.stac-item
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final.stac-item
2022-10-17 10:34:06	ga_ls9c_ard_3-2-1_102082_2022-10-17_final.stac-item
2022-10-18 09:38:29	ga_ls9c_ard_3-2-1_093082_2022-10-18_final.stac-item
2022-10-21 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-10-21_final.stac-item
2022-11-03 09:38:26	ga_ls9c_ard_3-2-1_093082_2022-11-03_final.stac-item
2022-11-09 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-11-09_final.stac-item
2022-11-13 10:15:35	ga_ls9c_ard_3-2-1_099082_2022-11-13_final.stac-item
2022-11-29 10:15:32	ga_ls9c_ard_3-2-1_099082_2022-11-29_final.stac-item
2022-12-08 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-12-08_final.stac-item
2022-12-11 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-12-11_final.stac-item
2022-12-12 09:44:40	ga_ls9c_ard_3-2-1_094082_2022-12-12_final.stac-item
2022-12-15 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-12-15_final.stac-item
2022-12-20 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-20_final.stac-item
2023-01-09 10:09:23	ga_ls9c_ard_3-2-1_098082_2023-01-09_final.stac-item
2023-01-12 10:40:15	ga_ls9c_ard_3-2-1_103082_2023-01-12_final.stac-item
2023-01-13 09:44:38	ga_ls9c_ard_3-2-1_094082_2023-01-13_final.stac-item
2023-01-25 10:09:18	ga_ls9c_ard_3-2-1_098082_2023-01-25_final.stac-item
2023-01-28 10:40:15	ga_ls9c_ard_3-2-1_103082_2023-01-28_final.stac-item
2023-01-29 09:44:39	ga_ls9c_ard_3-2-1_094082_2023-01-29_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-02-17 10:15:33	ga_ls9c_ard_3-2-1_099082_2023-02-17_final.stac-item
2023-02-22 10:33:58	ga_ls9c_ard_3-2-1_102082_2023-02-22_final.stac-item
2023-03-01 10:40:06	ga_ls9c_ard_3-2-1_103082_2023-03-01_final.stac-item
2023-03-02 09:44:28	ga_ls9c_ard_3-2-1_094082_2023-03-02_final.stac-item
2023-03-10 10:33:47	ga_ls9c_ard_3-2-1_102082_2023-03-10_final.stac-item
2023-03-11 09:38:10	ga_ls9c_ard_3-2-1_093082_2023-03-11_final.stac-item
2023-03-18 09:44:21	ga_ls9c_ard_3-2-1_094082_2023-03-18_final.stac-item
2023-03-21 10:15:14	ga_ls9c_ard_3-2-1_099082_2023-03-21_final.stac-item
2023-03-26 10:33:41	ga_ls9c_ard_3-2-1_102082_2023-03-26_final.stac-item
2023-03-27 09:38:03	ga_ls9c_ard_3-2-1_093082_2023-03-27_final.stac-item
2023-04-02 10:39:48	ga_ls9c_ard_3-2-1_103082_2023-04-02_final.stac-item
2023-04-03 09:44:10	ga_ls9c_ard_3-2-1_094082_2023-04-03_final.stac-item
2023-04-12 09:37:55	ga_ls9c_ard_3-2-1_093082_2023-04-12_final.stac-item
2023-04-18 10:39:41	ga_ls9c_ard_3-2-1_103082_2023-04-18_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
2023-05-01 10:08:39	ga_ls9c_ard_3-2-1_098082_2023-05-01_final.stac-item
2023-05-04 10:39:29	ga_ls9c_ard_3-2-1_103082_2023-05-04_final.stac-item
2023-05-05 09:43:52	ga_ls9c_ard_3-2-1_094082_2023-05-05_final.stac-item
2023-05-08 10:14:46	ga_ls9c_ard_3-2-1_099082_2023-05-08_final.stac-item
2023-05-14 09:37:39	ga_ls9c_ard_3-2-1_093082_2023-05-14_final.stac-item
2023-05-17 10:08:32	ga_ls9c_ard_3-2-1_098082_2023-05-17_final.stac-item
2023-05-21 09:43:45	ga_ls9c_ard_3-2-1_094082_2023-05-21_final.stac-item
2023-05-30 09:37:31	ga_ls9c_ard_3-2-1_093082_2023-05-30_final.stac-item
2023-06-05 10:39:17	ga_ls9c_ard_3-2-1_103082_2023-06-05_final.stac-item
2023-06-18 10:08:15	ga_ls9c_ard_3-2-1_098082_2023-06-18_final.stac-item
2023-06-21 10:39:10	ga_ls9c_ard_3-2-1_103082_2023-06-21_final.stac-item
2023-06-22 09:43:32	ga_ls9c_ard_3-2-1_094082_2023-06-22_final.stac-item
2023-06-25 10:14:26	ga_ls9c_ard_3-2-1_099082_2023-06-25_final.stac-item
2023-06-30 10:33:06	ga_ls9c_ard_3-2-1_102082_2023-06-30_final.stac-item
2023-07-04 10:08:27	ga_ls9c_ard_3-2-1_098082_2023-07-04_final.stac-item
2023-07-17 09:37:38	ga_ls9c_ard_3-2-1_093082_2023-07-17_final.stac-item
2023-08-02 09:37:45	ga_ls9c_ard_3-2-1_093082_2023-08-02_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