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 09:55:45	ga_ls9c_ard_3-2-1_096077_2021-11-03_final.stac-item
2021-11-13 11:40:10	ga_ls9c_ard_3-2-1_113079_2021-11-13_final.stac-item
2021-11-18 10:02:22	ga_ls9c_ard_3-2-1_097075_2021-11-18_final.stac-item
2021-11-20 09:44:49	ga_ls9c_ard_3-2-1_094078_2021-11-20_final.stac-item
2021-12-23 09:54:28	ga_ls9c_ard_3-2-1_096076_2021-12-23_final.stac-item
2021-12-27 11:09:02	ga_ls9c_ard_3-2-1_108077_2021-12-27_final.stac-item
2021-12-31 10:43:30	ga_ls9c_ard_3-2-1_104075_2021-12-31_final.stac-item
2022-01-08 09:54:26	ga_ls9c_ard_3-2-1_096076_2022-01-08_final.stac-item
2022-01-09 10:38:54	ga_ls9c_ard_3-2-1_103079_2022-01-09_final.stac-item
2022-01-10 09:42:28	ga_ls9c_ard_3-2-1_094077_2022-01-10_final.stac-item
2022-01-10 09:42:52	ga_ls9c_ard_3-2-1_094078_2022-01-10_final.stac-item
2022-01-15 11:39:53	ga_ls9c_ard_3-2-1_113077_2022-01-15_final.stac-item
2022-01-31 11:39:55	ga_ls9c_ard_3-2-1_113077_2022-01-31_final.stac-item
2022-02-09 11:33:42	ga_ls9c_ard_3-2-1_112077_2022-02-09_final.stac-item
2022-02-20 09:38:11	ga_ls9c_ard_3-2-1_093082_2022-02-20_final.stac-item
2022-02-25 11:33:33	ga_ls9c_ard_3-2-1_112077_2022-02-25_final.stac-item
2022-03-04 11:39:40	ga_ls9c_ard_3-2-1_113077_2022-03-04_final.stac-item
2022-03-06 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-03-06_final.stac-item
2022-03-22 09:48:47	ga_ls9c_ard_3-2-1_095078_2022-03-22_final.stac-item
2022-03-29 09:54:07	ga_ls9c_ard_3-2-1_096076_2022-03-29_final.stac-item
2022-04-16 11:21:44	ga_ls9c_ard_3-2-1_110079_2022-04-16_final.stac-item
2022-04-24 10:31:01	ga_ls9c_ard_3-2-1_102076_2022-04-24_final.stac-item
2022-04-30 11:33:36	ga_ls9c_ard_3-2-1_112078_2022-04-30_final.stac-item
2022-05-06 10:57:41	ga_ls9c_ard_3-2-1_106081_2022-05-06_final.stac-item
2022-05-18 11:21:50	ga_ls9c_ard_3-2-1_110080_2022-05-18_final.stac-item
2022-06-05 11:08:40	ga_ls9c_ard_3-2-1_108078_2022-06-05_final.stac-item
2022-06-10 09:48:20	ga_ls9c_ard_3-2-1_095078_2022-06-10_final.stac-item
2022-06-19 11:21:36	ga_ls9c_ard_3-2-1_110079_2022-06-19_final.stac-item
2022-06-26 09:48:41	ga_ls9c_ard_3-2-1_095078_2022-06-26_final.stac-item
2022-06-29 10:17:35	ga_ls9c_ard_3-2-1_100073_2022-06-29_final.stac-item
2022-07-05 11:21:46	ga_ls9c_ard_3-2-1_110079_2022-07-05_final.stac-item
2022-07-12 11:27:54	ga_ls9c_ard_3-2-1_111079_2022-07-12_final.stac-item
2022-07-13 10:31:04	ga_ls9c_ard_3-2-1_102076_2022-07-13_final.stac-item
2022-07-19 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-19_final.stac-item
2022-07-26 11:39:14	ga_ls9c_ard_3-2-1_113076_2022-07-26_final.stac-item
2022-08-03 10:50:41	ga_ls9c_ard_3-2-1_105078_2022-08-03_final.stac-item
2022-08-04 09:54:17	ga_ls9c_ard_3-2-1_096076_2022-08-04_final.stac-item
2022-08-04 11:33:10	ga_ls9c_ard_3-2-1_112076_2022-08-04_final.stac-item
2022-08-06 09:42:44	ga_ls9c_ard_3-2-1_094078_2022-08-06_final.stac-item
2022-08-11 11:39:25	ga_ls9c_ard_3-2-1_113076_2022-08-11_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-08-20 11:34:05	ga_ls9c_ard_3-2-1_112078_2022-08-20_final.stac-item
2022-08-22 11:21:44	ga_ls9c_ard_3-2-1_110078_2022-08-22_final.stac-item
2022-08-22 11:22:08	ga_ls9c_ard_3-2-1_110079_2022-08-22_final.stac-item
2022-08-25 10:12:33	ga_ls9c_ard_3-2-1_099075_2022-08-25_final.stac-item
2022-08-27 11:39:29	ga_ls9c_ard_3-2-1_113076_2022-08-27_final.stac-item
2022-09-03 10:08:46	ga_ls9c_ard_3-2-1_098081_2022-09-03_final.stac-item
2022-09-14 09:48:41	ga_ls9c_ard_3-2-1_095077_2022-09-14_final.stac-item
2022-09-15 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-09-15_final.stac-item
2022-09-19 10:08:51	ga_ls9c_ard_3-2-1_098081_2022-09-19_final.stac-item
2022-09-19 10:09:15	ga_ls9c_ard_3-2-1_098082_2022-09-19_final.stac-item
2022-09-26 10:12:41	ga_ls9c_ard_3-2-1_099075_2022-09-26_final.stac-item
2022-09-30 09:49:09	ga_ls9c_ard_3-2-1_095078_2022-09-30_final.stac-item
2022-10-08 10:39:00	ga_ls9c_ard_3-2-1_103079_2022-10-08_final.stac-item
2022-10-16 09:48:50	ga_ls9c_ard_3-2-1_095077_2022-10-16_final.stac-item
2022-10-30 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-10-30_final.stac-item
2022-10-31 10:46:03	ga_ls9c_ard_3-2-1_104081_2022-10-31_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-12-10 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-12-10_final.stac-item
2022-12-22 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-12-22_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2022-12-30 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-30_final.stac-item
2023-01-11 11:34:18	ga_ls9c_ard_3-2-1_112078_2023-01-11_final.stac-item
2023-01-15 11:09:08	ga_ls9c_ard_3-2-1_108077_2023-01-15_final.stac-item
2023-01-29 09:43:27	ga_ls9c_ard_3-2-1_094079_2023-01-29_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-05 09:48:54	ga_ls9c_ard_3-2-1_095077_2023-02-05_final.stac-item
2023-02-14 09:43:06	ga_ls9c_ard_3-2-1_094078_2023-02-14_final.stac-item
2023-02-21 09:49:08	ga_ls9c_ard_3-2-1_095078_2023-02-21_final.stac-item
2023-03-11 09:38:10	ga_ls9c_ard_3-2-1_093082_2023-03-11_final.stac-item
2023-03-15 10:50:45	ga_ls9c_ard_3-2-1_105078_2023-03-15_final.stac-item
2023-03-30 10:08:53	ga_ls9c_ard_3-2-1_098082_2023-03-30_final.stac-item
2023-04-03 09:42:58	ga_ls9c_ard_3-2-1_094079_2023-04-03_final.stac-item
2023-04-09 10:45:32	ga_ls9c_ard_3-2-1_104081_2023-04-09_final.stac-item
2023-04-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2023-04-23_final.stac-item
2023-04-24 10:02:35	ga_ls9c_ard_3-2-1_097082_2023-04-24_final.stac-item
2023-05-03 11:33:32	ga_ls9c_ard_3-2-1_112078_2023-05-03_final.stac-item
2023-05-05 09:42:40	ga_ls9c_ard_3-2-1_094079_2023-05-05_final.stac-item
2023-05-19 09:53:45	ga_ls9c_ard_3-2-1_096076_2023-05-19_final.stac-item
2023-05-21 09:42:09	ga_ls9c_ard_3-2-1_094078_2023-05-21_final.stac-item
2023-06-02 10:05:36	ga_ls9c_ard_3-2-1_098075_2023-06-02_final.stac-item
2023-06-04 09:53:38	ga_ls9c_ard_3-2-1_096076_2023-06-04_final.stac-item
2023-06-27 11:38:36	ga_ls9c_ard_3-2-1_113076_2023-06-27_final.stac-item
2023-07-04 11:45:20	ga_ls9c_ard_3-2-1_114077_2023-07-04_final.stac-item
2023-07-13 11:38:50	ga_ls9c_ard_3-2-1_113076_2023-07-13_final.stac-item
2023-07-24 09:42:36	ga_ls9c_ard_3-2-1_094079_2023-07-24_final.stac-item
2023-07-24 11:23:52	ga_ls9c_ard_3-2-1_110085_2023-07-24_final.stac-item
2023-07-26 11:10:20	ga_ls9c_ard_3-2-1_108082_2023-07-26_final.stac-item
2023-07-29 11:38:54	ga_ls9c_ard_3-2-1_113076_2023-07-29_final.stac-item
2023-08-02 11:11:27	ga_ls9c_ard_3-2-1_109069_2023-08-02_final.stac-item
2023-08-05 10:06:17	ga_ls9c_ard_3-2-1_098076_2023-08-05_final.stac-item
2023-08-09 09:42:23	ga_ls9c_ard_3-2-1_094078_2023-08-09_final.stac-item
2023-08-18 11:11:53	ga_ls9c_ard_3-2-1_109070_2023-08-18_final.stac-item
2023-10-13 10:26:53	ga_ls9c_ard_3-2-1_101080_2023-10-13_final.stac-item
2023-10-24 10:06:47	ga_ls9c_ard_3-2-1_098076_2023-10-24_final.stac-item
2023-10-27 10:38:51	ga_ls9c_ard_3-2-1_103079_2023-10-27_final.stac-item
2023-10-28 11:18:31	ga_ls9c_ard_3-2-1_110070_2023-10-28_final.stac-item
2023-10-29 10:26:52	ga_ls9c_ard_3-2-1_101080_2023-10-29_final.stac-item
2023-10-30 11:08:55	ga_ls9c_ard_3-2-1_108077_2023-10-30_final.stac-item
2023-11-15 11:08:55	ga_ls9c_ard_3-2-1_108077_2023-11-15_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years