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
2021-11-08 09:55:27	ga_ls9c_ard_3-2-1_097070_2021-11-08_final.stac-item
2021-11-11 10:19:51	ga_ls9c_ard_3-2-1_100078_2021-11-11_final.stac-item
2021-11-13 11:38:10	ga_ls9c_ard_3-2-1_113074_2021-11-13_final.stac-item
2021-11-20 09:42:49	ga_ls9c_ard_3-2-1_094073_2021-11-20_final.stac-item
2021-12-04 11:00:35	ga_ls9c_ard_3-2-1_107071_2021-12-04_final.stac-item
2021-12-06 09:10:31	ga_ls9c_ard_3-2-1_089074_2021-12-05_final.stac-item
2021-12-10 10:27:49	ga_ls9c_ard_3-2-1_101082_2021-12-10_final.stac-item
2021-12-15 10:44:42	ga_ls9c_ard_3-2-1_104078_2021-12-15_final.stac-item
2021-12-19 10:17:35	ga_ls9c_ard_3-2-1_100072_2021-12-19_final.stac-item
2022-01-04 10:17:35	ga_ls9c_ard_3-2-1_100072_2022-01-04_final.stac-item
2022-01-08 11:32:31	ga_ls9c_ard_3-2-1_112074_2022-01-08_final.stac-item
2022-01-19 09:39:29	ga_ls9c_ard_3-2-1_093085_2022-01-19_final.stac-item
2022-01-27 10:28:09	ga_ls9c_ard_3-2-1_101083_2022-01-27_final.stac-item
2022-02-15 09:21:41	ga_ls9c_ard_3-2-1_090087_2022-02-14_final.stac-item
2022-03-20 09:56:46	ga_ls9c_ard_3-2-1_097067_2022-03-20_final.stac-item
2022-03-21 10:46:00	ga_ls9c_ard_3-2-1_104082_2022-03-21_final.stac-item
2022-03-24 09:34:01	ga_ls9c_ard_3-2-1_093072_2022-03-24_final.stac-item
2022-04-04 10:55:55	ga_ls9c_ard_3-2-1_106076_2022-04-04_final.stac-item
2022-04-07 11:25:37	ga_ls9c_ard_3-2-1_111073_2022-04-07_final.stac-item
2022-04-15 10:35:42	ga_ls9c_ard_3-2-1_103072_2022-04-15_final.stac-item
2022-04-29 09:15:51	ga_ls9c_ard_3-2-1_089089_2022-04-28_final.stac-item
2022-05-06 10:58:29	ga_ls9c_ard_3-2-1_106083_2022-05-06_final.stac-item
2022-05-13 11:01:47	ga_ls9c_ard_3-2-1_107076_2022-05-13_final.stac-item
2022-05-25 11:28:23	ga_ls9c_ard_3-2-1_111081_2022-05-25_final.stac-item
2022-06-15 10:08:57	ga_ls9c_ard_3-2-1_098083_2022-06-15_final.stac-item
2022-06-23 09:16:56	ga_ls9c_ard_3-2-1_090076_2022-06-22_final.stac-item
2022-07-02 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-07-02_final.stac-item
2022-07-03 09:57:14	ga_ls9c_ard_3-2-1_096084_2022-07-03_final.stac-item
2022-07-06 10:27:20	ga_ls9c_ard_3-2-1_101082_2022-07-06_final.stac-item
2022-07-15 11:58:23	ga_ls9c_ard_3-2-1_116078_2022-07-15_final.stac-item
2022-07-21 11:19:49	ga_ls9c_ard_3-2-1_110074_2022-07-21_final.stac-item
2022-07-24 10:15:04	ga_ls9c_ard_3-2-1_099082_2022-07-24_final.stac-item
2022-08-03 10:49:05	ga_ls9c_ard_3-2-1_105074_2022-08-03_final.stac-item
2022-08-10 09:16:51	ga_ls9c_ard_3-2-1_090075_2022-08-09_final.stac-item
2022-08-20 09:57:59	ga_ls9c_ard_3-2-1_096085_2022-08-20_final.stac-item
2022-08-21 10:36:04	ga_ls9c_ard_3-2-1_103072_2022-08-21_final.stac-item
2022-08-25 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-08-25_final.stac-item
2022-08-26 09:17:20	ga_ls9c_ard_3-2-1_090076_2022-08-25_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-08-28 09:06:34	ga_ls9c_ard_3-2-1_088080_2022-08-27_final.stac-item
2022-09-24 10:26:14	ga_ls9c_ard_3-2-1_101078_2022-09-24_final.stac-item
2022-10-21 10:05:24	ga_ls9c_ard_3-2-1_098072_2022-10-21_final.stac-item
2022-10-26 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-10-26_final.stac-item
2022-10-28 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-10-28_final.stac-item
2022-11-05 09:23:41	ga_ls9c_ard_3-2-1_091076_2022-11-04_final.stac-item
2022-11-07 10:50:14	ga_ls9c_ard_3-2-1_105076_2022-11-07_final.stac-item
2022-11-12 09:31:31	ga_ls9c_ard_3-2-1_092080_2022-11-12_final.stac-item
2022-11-13 10:09:36	ga_ls9c_ard_3-2-1_099067_2022-11-13_final.stac-item
2022-11-20 10:20:10	ga_ls9c_ard_3-2-1_100078_2022-11-20_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-11-21 09:22:09	ga_ls9c_ard_3-2-1_091072_2022-11-20_final.stac-item
2022-11-22 10:08:12	ga_ls9c_ard_3-2-1_098079_2022-11-22_final.stac-item
2022-11-23 10:47:04	ga_ls9c_ard_3-2-1_105068_2022-11-23_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2022-12-10 11:32:43	ga_ls9c_ard_3-2-1_112074_2022-12-10_final.stac-item
2022-12-14 09:29:54	ga_ls9c_ard_3-2-1_092076_2022-12-13_final.stac-item
2022-12-14 09:34:18	ga_ls9c_ard_3-2-1_092087_2022-12-14_final.stac-item
2022-12-23 11:02:33	ga_ls9c_ard_3-2-1_107076_2022-12-23_final.stac-item
2023-01-19 09:07:27	ga_ls9c_ard_3-2-1_088082_2023-01-18_final.stac-item
2023-01-22 09:35:33	ga_ls9c_ard_3-2-1_093075_2023-01-22_final.stac-item
2023-01-22 09:39:32	ga_ls9c_ard_3-2-1_093085_2023-01-22_final.stac-item
2023-01-26 09:14:54	ga_ls9c_ard_3-2-1_089085_2023-01-25_final.stac-item
2023-01-26 10:49:47	ga_ls9c_ard_3-2-1_105075_2023-01-26_final.stac-item
2023-01-27 11:32:40	ga_ls9c_ard_3-2-1_112074_2023-01-27_final.stac-item
2023-01-31 09:29:31	ga_ls9c_ard_3-2-1_092075_2023-01-30_final.stac-item
2023-02-06 10:28:34	ga_ls9c_ard_3-2-1_102068_2023-02-06_final.stac-item
2023-02-08 10:20:13	ga_ls9c_ard_3-2-1_100078_2023-02-08_final.stac-item
2023-02-09 09:29:23	ga_ls9c_ard_3-2-1_091090_2023-02-08_final.stac-item
2023-02-18 10:54:24	ga_ls9c_ard_3-2-1_106071_2023-02-18_final.stac-item
2023-02-26 10:06:01	ga_ls9c_ard_3-2-1_098074_2023-02-26_final.stac-item
2023-02-26 10:09:36	ga_ls9c_ard_3-2-1_098083_2023-02-26_final.stac-item
2023-03-02 11:20:33	ga_ls9c_ard_3-2-1_110075_2023-03-02_final.stac-item
2023-03-04 11:08:11	ga_ls9c_ard_3-2-1_108075_2023-03-04_final.stac-item
2023-03-17 10:35:59	ga_ls9c_ard_3-2-1_103072_2023-03-17_final.stac-item
2023-03-29 09:21:39	ga_ls9c_ard_3-2-1_091072_2023-03-28_final.stac-item
2023-04-01 09:57:20	ga_ls9c_ard_3-2-1_096084_2023-04-01_final.stac-item
2023-04-03 09:40:59	ga_ls9c_ard_3-2-1_094074_2023-04-03_final.stac-item
2023-04-04 10:23:02	ga_ls9c_ard_3-2-1_101071_2023-04-04_final.stac-item
2023-04-05 11:08:18	ga_ls9c_ard_3-2-1_108076_2023-04-05_final.stac-item
2023-04-07 09:16:38	ga_ls9c_ard_3-2-1_090075_2023-04-06_final.stac-item
2023-04-14 09:22:44	ga_ls9c_ard_3-2-1_091075_2023-04-13_final.stac-item
2023-05-16 09:24:29	ga_ls9c_ard_3-2-1_091080_2023-05-15_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-06-06 11:22:56	ga_ls9c_ard_3-2-1_110083_2023-06-06_final.stac-item
2023-06-18 11:46:45	ga_ls9c_ard_3-2-1_114081_2023-06-18_final.stac-item
2023-06-22 11:19:38	ga_ls9c_ard_3-2-1_110075_2023-06-22_final.stac-item
2023-06-24 09:27:59	ga_ls9c_ard_3-2-1_092074_2023-06-23_final.stac-item
2023-07-04 10:09:15	ga_ls9c_ard_3-2-1_098084_2023-07-04_final.stac-item
2023-07-19 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-07-18_final.stac-item
2023-07-28 09:16:44	ga_ls9c_ard_3-2-1_090076_2023-07-27_final.stac-item
2023-07-29 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-07-29_final.stac-item
2023-08-04 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-08-04_final.stac-item
2023-08-09 11:20:04	ga_ls9c_ard_3-2-1_110075_2023-08-09_final.stac-item
2023-08-13 10:55:45	ga_ls9c_ard_3-2-1_106076_2023-08-13_final.stac-item
2023-08-15 09:06:54	ga_ls9c_ard_3-2-1_088082_2023-08-14_final.stac-item
2023-10-17 09:57:25	ga_ls9c_ard_3-2-1_097068_2023-10-17_final.stac-item
2023-10-20 10:30:19	ga_ls9c_ard_3-2-1_102073_2023-10-20_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-11-19 09:07:21	ga_ls9c_ard_3-2-1_088082_2023-11-18_final.stac-item
2023-11-24 09:23:34	ga_ls9c_ard_3-2-1_091076_2023-11-23_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