Search ga_ls9c_ard_3 across December 2022

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
2022-12-01 10:00:22	ga_ls9c_ard_3-2-1_097075_2022-12-01_final.stac-item
2022-12-01 10:01:10	ga_ls9c_ard_3-2-1_097077_2022-12-01_final.stac-item
2022-12-01 11:39:15	ga_ls9c_ard_3-2-1_113075_2022-12-01_final.stac-item
2022-12-01 11:41:15	ga_ls9c_ard_3-2-1_113080_2022-12-01_final.stac-item
2022-12-02 10:44:49	ga_ls9c_ard_3-2-1_104078_2022-12-02_final.stac-item
2022-12-02 10:45:13	ga_ls9c_ard_3-2-1_104079_2022-12-02_final.stac-item
2022-12-03 09:48:01	ga_ls9c_ard_3-2-1_095075_2022-12-03_final.stac-item
2022-12-03 09:48:49	ga_ls9c_ard_3-2-1_095077_2022-12-03_final.stac-item
2022-12-03 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-12-03_final.stac-item
2022-12-03 09:50:00	ga_ls9c_ard_3-2-1_095080_2022-12-03_final.stac-item
2022-12-03 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-12-03_final.stac-item
2022-12-03 11:28:30	ga_ls9c_ard_3-2-1_111079_2022-12-03_final.stac-item
2022-12-03 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-03_final.stac-item
2022-12-04 10:31:41	ga_ls9c_ard_3-2-1_102076_2022-12-04_final.stac-item
2022-12-04 10:32:53	ga_ls9c_ard_3-2-1_102079_2022-12-04_final.stac-item
2022-12-04 10:33:17	ga_ls9c_ard_3-2-1_102080_2022-12-04_final.stac-item
2022-12-05 09:36:28	ga_ls9c_ard_3-2-1_093077_2022-12-05_final.stac-item
2022-12-05 09:37:16	ga_ls9c_ard_3-2-1_093079_2022-12-05_final.stac-item
2022-12-05 09:37:40	ga_ls9c_ard_3-2-1_093080_2022-12-05_final.stac-item
2022-12-05 11:16:33	ga_ls9c_ard_3-2-1_109080_2022-12-05_final.stac-item
2022-12-06 10:18:56	ga_ls9c_ard_3-2-1_100075_2022-12-06_final.stac-item
2022-12-06 10:19:44	ga_ls9c_ard_3-2-1_100077_2022-12-06_final.stac-item
2022-12-07 09:24:07	ga_ls9c_ard_3-2-1_091077_2022-12-06_final.stac-item
2022-12-07 09:25:19	ga_ls9c_ard_3-2-1_091080_2022-12-06_final.stac-item
2022-12-07 11:04:12	ga_ls9c_ard_3-2-1_107080_2022-12-07_final.stac-item
2022-12-08 10:06:35	ga_ls9c_ard_3-2-1_098075_2022-12-08_final.stac-item
2022-12-08 11:45:28	ga_ls9c_ard_3-2-1_114075_2022-12-08_final.stac-item
2022-12-08 11:46:16	ga_ls9c_ard_3-2-1_114077_2022-12-08_final.stac-item
2022-12-08 11:46:40	ga_ls9c_ard_3-2-1_114078_2022-12-08_final.stac-item
2022-12-08 11:47:28	ga_ls9c_ard_3-2-1_114080_2022-12-08_final.stac-item
2022-12-09 09:11:46	ga_ls9c_ard_3-2-1_089077_2022-12-08_final.stac-item
2022-12-09 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-12-09_final.stac-item
2022-12-10 09:54:14	ga_ls9c_ard_3-2-1_096075_2022-12-10_final.stac-item
2022-12-10 09:55:02	ga_ls9c_ard_3-2-1_096077_2022-12-10_final.stac-item
2022-12-10 09:56:14	ga_ls9c_ard_3-2-1_096080_2022-12-10_final.stac-item
2022-12-10 11:33:07	ga_ls9c_ard_3-2-1_112075_2022-12-10_final.stac-item
2022-12-10 11:35:07	ga_ls9c_ard_3-2-1_112080_2022-12-10_final.stac-item
2022-12-11 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-12-11_final.stac-item
2022-12-11 10:38:17	ga_ls9c_ard_3-2-1_103077_2022-12-11_final.stac-item
2022-12-11 10:39:05	ga_ls9c_ard_3-2-1_103079_2022-12-11_final.stac-item
2022-12-12 09:42:40	ga_ls9c_ard_3-2-1_094077_2022-12-12_final.stac-item
2022-12-12 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-12-12_final.stac-item
2022-12-12 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-12-12_final.stac-item
2022-12-12 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-12-12_final.stac-item
2022-12-12 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-12-12_final.stac-item
2022-12-13 10:25:08	ga_ls9c_ard_3-2-1_101075_2022-12-13_final.stac-item
2022-12-13 10:25:56	ga_ls9c_ard_3-2-1_101077_2022-12-13_final.stac-item
2022-12-14 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-14_final.stac-item
2022-12-14 11:10:23	ga_ls9c_ard_3-2-1_108080_2022-12-14_final.stac-item
2022-12-15 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-12-15_final.stac-item
2022-12-15 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-12-15_final.stac-item
2022-12-16 09:17:33	ga_ls9c_ard_3-2-1_090076_2022-12-15_final.stac-item
2022-12-16 09:19:08	ga_ls9c_ard_3-2-1_090080_2022-12-15_final.stac-item
2022-12-16 10:56:49	ga_ls9c_ard_3-2-1_106077_2022-12-16_final.stac-item
2022-12-17 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-12-17_final.stac-item
2022-12-17 11:41:17	ga_ls9c_ard_3-2-1_113080_2022-12-17_final.stac-item
2022-12-18 10:44:51	ga_ls9c_ard_3-2-1_104078_2022-12-18_final.stac-item
2022-12-18 10:45:15	ga_ls9c_ard_3-2-1_104079_2022-12-18_final.stac-item
2022-12-18 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-12-18_final.stac-item
2022-12-19 09:50:01	ga_ls9c_ard_3-2-1_095080_2022-12-19_final.stac-item
2022-12-19 11:27:43	ga_ls9c_ard_3-2-1_111077_2022-12-19_final.stac-item
2022-12-19 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-19_final.stac-item
2022-12-21 09:36:27	ga_ls9c_ard_3-2-1_093077_2022-12-21_final.stac-item
2022-12-21 09:37:39	ga_ls9c_ard_3-2-1_093080_2022-12-21_final.stac-item
2022-12-21 11:16:32	ga_ls9c_ard_3-2-1_109080_2022-12-21_final.stac-item
2022-12-22 10:18:54	ga_ls9c_ard_3-2-1_100075_2022-12-22_final.stac-item
2022-12-22 10:20:30	ga_ls9c_ard_3-2-1_100079_2022-12-22_final.stac-item
2022-12-22 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-12-22_final.stac-item
2022-12-23 09:24:04	ga_ls9c_ard_3-2-1_091077_2022-12-22_final.stac-item
2022-12-23 09:25:16	ga_ls9c_ard_3-2-1_091080_2022-12-22_final.stac-item
2022-12-23 11:03:45	ga_ls9c_ard_3-2-1_107079_2022-12-23_final.stac-item
2022-12-24 10:06:32	ga_ls9c_ard_3-2-1_098075_2022-12-24_final.stac-item
2022-12-24 10:08:08	ga_ls9c_ard_3-2-1_098079_2022-12-24_final.stac-item
2022-12-24 11:45:25	ga_ls9c_ard_3-2-1_114075_2022-12-24_final.stac-item
2022-12-24 11:46:13	ga_ls9c_ard_3-2-1_114077_2022-12-24_final.stac-item
2022-12-24 11:46:37	ga_ls9c_ard_3-2-1_114078_2022-12-24_final.stac-item
2022-12-24 11:47:25	ga_ls9c_ard_3-2-1_114080_2022-12-24_final.stac-item
2022-12-25 09:11:43	ga_ls9c_ard_3-2-1_089077_2022-12-24_final.stac-item
2022-12-25 10:51:00	ga_ls9c_ard_3-2-1_105078_2022-12-25_final.stac-item
2022-12-25 10:51:24	ga_ls9c_ard_3-2-1_105079_2022-12-25_final.stac-item
2022-12-25 10:51:48	ga_ls9c_ard_3-2-1_105080_2022-12-25_final.stac-item
2022-12-26 09:54:59	ga_ls9c_ard_3-2-1_096077_2022-12-26_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2022-12-26 11:35:04	ga_ls9c_ard_3-2-1_112080_2022-12-26_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2022-12-27 10:39:03	ga_ls9c_ard_3-2-1_103079_2022-12-27_final.stac-item
2022-12-27 10:39:27	ga_ls9c_ard_3-2-1_103080_2022-12-27_final.stac-item
2022-12-28 09:42:39	ga_ls9c_ard_3-2-1_094077_2022-12-28_final.stac-item
2022-12-28 09:43:27	ga_ls9c_ard_3-2-1_094079_2022-12-28_final.stac-item
2022-12-28 09:43:51	ga_ls9c_ard_3-2-1_094080_2022-12-28_final.stac-item
2022-12-28 11:22:20	ga_ls9c_ard_3-2-1_110079_2022-12-28_final.stac-item
2022-12-28 11:22:44	ga_ls9c_ard_3-2-1_110080_2022-12-28_final.stac-item
2022-12-29 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-12-29_final.stac-item
2022-12-29 10:25:55	ga_ls9c_ard_3-2-1_101077_2022-12-29_final.stac-item
2022-12-30 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-30_final.stac-item
2022-12-30 11:10:23	ga_ls9c_ard_3-2-1_108080_2022-12-30_final.stac-item
2022-12-31 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-12-31_final.stac-item
2022-12-31 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-12-31_final.stac-item
2022-12-31 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-12-31_final.stac-item
2022-12-31 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-31_final.stac-item

Return to ga_ls9c_ard_3 across December 2022 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

2022

December

All days