Search ga_ls9c_ard_3 across December 2023

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
2023-12-01 09:30:58	ga_ls9c_ard_3-2-1_092079_2023-12-01_final.stac-item
2023-12-01 09:31:45	ga_ls9c_ard_3-2-1_092081_2023-12-01_final.stac-item
2023-12-01 09:32:09	ga_ls9c_ard_3-2-1_092082_2023-12-01_final.stac-item
2023-12-01 11:10:38	ga_ls9c_ard_3-2-1_108081_2023-12-01_final.stac-item
2023-12-02 10:13:25	ga_ls9c_ard_3-2-1_099077_2023-12-02_final.stac-item
2023-12-02 10:15:01	ga_ls9c_ard_3-2-1_099081_2023-12-02_final.stac-item
2023-12-03 09:18:59	ga_ls9c_ard_3-2-1_090080_2023-12-02_final.stac-item
2023-12-03 09:19:23	ga_ls9c_ard_3-2-1_090081_2023-12-02_final.stac-item
2023-12-03 09:22:34	ga_ls9c_ard_3-2-1_090089_2023-12-02_final.stac-item
2023-12-03 10:57:28	ga_ls9c_ard_3-2-1_106079_2023-12-03_final.stac-item
2023-12-04 10:01:02	ga_ls9c_ard_3-2-1_097077_2023-12-04_final.stac-item
2023-12-04 10:02:38	ga_ls9c_ard_3-2-1_097081_2023-12-04_final.stac-item
2023-12-04 10:04:13	ga_ls9c_ard_3-2-1_097085_2023-12-04_final.stac-item
2023-12-05 09:07:00	ga_ls9c_ard_3-2-1_088081_2023-12-04_final.stac-item
2023-12-05 09:07:23	ga_ls9c_ard_3-2-1_088082_2023-12-04_final.stac-item
2023-12-05 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-12-05_final.stac-item
2023-12-05 14:10:02	ga_ls9c_ard_3-2-1_136097_2023-12-05_final.stac-item
2023-12-06 08:18:09	ga_ls9c_ard_3-2-1_079098_2023-12-05_final.stac-item
2023-12-06 09:49:02	ga_ls9c_ard_3-2-1_095078_2023-12-06_final.stac-item
2023-12-06 09:51:02	ga_ls9c_ard_3-2-1_095083_2023-12-06_final.stac-item
2023-12-06 11:27:55	ga_ls9c_ard_3-2-1_111078_2023-12-06_final.stac-item
2023-12-07 10:33:29	ga_ls9c_ard_3-2-1_102081_2023-12-07_final.stac-item
2023-12-08 09:36:39	ga_ls9c_ard_3-2-1_093078_2023-12-08_final.stac-item
2023-12-08 09:39:27	ga_ls9c_ard_3-2-1_093085_2023-12-08_final.stac-item
2023-12-08 11:16:20	ga_ls9c_ard_3-2-1_109080_2023-12-08_final.stac-item
2023-12-08 11:16:44	ga_ls9c_ard_3-2-1_109081_2023-12-08_final.stac-item
2023-12-08 11:17:08	ga_ls9c_ard_3-2-1_109082_2023-12-08_final.stac-item
2023-12-09 08:42:39	ga_ls9c_ard_3-2-1_084082_2023-12-08_final.stac-item
2023-12-09 10:21:08	ga_ls9c_ard_3-2-1_100081_2023-12-09_final.stac-item
2023-12-10 09:24:43	ga_ls9c_ard_3-2-1_091079_2023-12-09_final.stac-item
2023-12-10 09:25:07	ga_ls9c_ard_3-2-1_091080_2023-12-09_final.stac-item
2023-12-10 09:25:31	ga_ls9c_ard_3-2-1_091081_2023-12-09_final.stac-item
2023-12-11 10:07:12	ga_ls9c_ard_3-2-1_098077_2023-12-11_final.stac-item
2023-12-11 10:08:48	ga_ls9c_ard_3-2-1_098081_2023-12-11_final.stac-item
2023-12-11 10:09:12	ga_ls9c_ard_3-2-1_098082_2023-12-11_final.stac-item
2023-12-11 10:10:24	ga_ls9c_ard_3-2-1_098085_2023-12-11_final.stac-item
2023-12-12 09:13:11	ga_ls9c_ard_3-2-1_089081_2023-12-11_final.stac-item
2023-12-12 09:13:35	ga_ls9c_ard_3-2-1_089082_2023-12-11_final.stac-item
2023-12-12 09:16:23	ga_ls9c_ard_3-2-1_089089_2023-12-11_final.stac-item
2023-12-12 10:51:16	ga_ls9c_ard_3-2-1_105079_2023-12-12_final.stac-item
2023-12-13 08:24:22	ga_ls9c_ard_3-2-1_080098_2023-12-12_final.stac-item
2023-12-13 09:54:52	ga_ls9c_ard_3-2-1_096077_2023-12-13_final.stac-item
2023-12-13 09:55:16	ga_ls9c_ard_3-2-1_096078_2023-12-13_final.stac-item
2023-12-13 09:56:28	ga_ls9c_ard_3-2-1_096081_2023-12-13_final.stac-item
2023-12-13 11:35:21	ga_ls9c_ard_3-2-1_112081_2023-12-13_final.stac-item
2023-12-14 10:39:44	ga_ls9c_ard_3-2-1_103081_2023-12-14_final.stac-item
2023-12-14 14:03:54	ga_ls9c_ard_3-2-1_135097_2023-12-14_final.stac-item
2023-12-15 09:42:56	ga_ls9c_ard_3-2-1_094078_2023-12-15_final.stac-item
2023-12-15 09:43:19	ga_ls9c_ard_3-2-1_094079_2023-12-15_final.stac-item
2023-12-15 11:21:49	ga_ls9c_ard_3-2-1_110078_2023-12-15_final.stac-item
2023-12-16 08:48:55	ga_ls9c_ard_3-2-1_085082_2023-12-15_final.stac-item
2023-12-16 10:27:24	ga_ls9c_ard_3-2-1_101081_2023-12-16_final.stac-item
2023-12-17 09:30:59	ga_ls9c_ard_3-2-1_092079_2023-12-17_final.stac-item
2023-12-17 09:31:47	ga_ls9c_ard_3-2-1_092081_2023-12-17_final.stac-item
2023-12-17 09:32:11	ga_ls9c_ard_3-2-1_092082_2023-12-17_final.stac-item
2023-12-17 11:10:40	ga_ls9c_ard_3-2-1_108081_2023-12-17_final.stac-item
2023-12-18 10:13:27	ga_ls9c_ard_3-2-1_099077_2023-12-18_final.stac-item
2023-12-18 10:14:15	ga_ls9c_ard_3-2-1_099079_2023-12-18_final.stac-item
2023-12-18 10:15:03	ga_ls9c_ard_3-2-1_099081_2023-12-18_final.stac-item
2023-12-19 09:19:02	ga_ls9c_ard_3-2-1_090080_2023-12-18_final.stac-item
2023-12-19 09:19:26	ga_ls9c_ard_3-2-1_090081_2023-12-18_final.stac-item
2023-12-19 10:57:31	ga_ls9c_ard_3-2-1_106079_2023-12-19_final.stac-item
2023-12-20 10:01:06	ga_ls9c_ard_3-2-1_097077_2023-12-20_final.stac-item
2023-12-20 10:02:42	ga_ls9c_ard_3-2-1_097081_2023-12-20_final.stac-item
2023-12-20 10:04:17	ga_ls9c_ard_3-2-1_097085_2023-12-20_final.stac-item
2023-12-21 09:07:04	ga_ls9c_ard_3-2-1_088081_2023-12-20_final.stac-item
2023-12-21 09:07:28	ga_ls9c_ard_3-2-1_088082_2023-12-20_final.stac-item
2023-12-21 10:45:09	ga_ls9c_ard_3-2-1_104079_2023-12-21_final.stac-item
2023-12-21 10:45:57	ga_ls9c_ard_3-2-1_104081_2023-12-21_final.stac-item
2023-12-21 14:10:07	ga_ls9c_ard_3-2-1_136097_2023-12-21_final.stac-item
2023-12-22 08:18:15	ga_ls9c_ard_3-2-1_079098_2023-12-21_final.stac-item
2023-12-22 09:49:08	ga_ls9c_ard_3-2-1_095078_2023-12-22_final.stac-item
2023-12-22 09:51:08	ga_ls9c_ard_3-2-1_095083_2023-12-22_final.stac-item
2023-12-22 11:28:02	ga_ls9c_ard_3-2-1_111078_2023-12-22_final.stac-item
2023-12-23 10:33:36	ga_ls9c_ard_3-2-1_102081_2023-12-23_final.stac-item
2023-12-24 09:36:47	ga_ls9c_ard_3-2-1_093078_2023-12-24_final.stac-item
2023-12-24 09:39:35	ga_ls9c_ard_3-2-1_093085_2023-12-24_final.stac-item
2023-12-24 11:16:52	ga_ls9c_ard_3-2-1_109081_2023-12-24_final.stac-item
2023-12-25 08:42:45	ga_ls9c_ard_3-2-1_084082_2023-12-24_final.stac-item
2023-12-25 10:20:26	ga_ls9c_ard_3-2-1_100079_2023-12-25_final.stac-item
2023-12-25 10:21:14	ga_ls9c_ard_3-2-1_100081_2023-12-25_final.stac-item
2023-12-26 09:24:49	ga_ls9c_ard_3-2-1_091079_2023-12-25_final.stac-item
2023-12-26 09:25:13	ga_ls9c_ard_3-2-1_091080_2023-12-25_final.stac-item
2023-12-26 09:25:37	ga_ls9c_ard_3-2-1_091081_2023-12-25_final.stac-item
2023-12-27 10:07:16	ga_ls9c_ard_3-2-1_098077_2023-12-27_final.stac-item
2023-12-27 10:10:28	ga_ls9c_ard_3-2-1_098085_2023-12-27_final.stac-item
2023-12-28 09:13:15	ga_ls9c_ard_3-2-1_089081_2023-12-27_final.stac-item
2023-12-28 09:13:39	ga_ls9c_ard_3-2-1_089082_2023-12-27_final.stac-item
2023-12-28 09:16:26	ga_ls9c_ard_3-2-1_089089_2023-12-27_final.stac-item
2023-12-28 10:51:20	ga_ls9c_ard_3-2-1_105079_2023-12-28_final.stac-item
2023-12-29 08:24:24	ga_ls9c_ard_3-2-1_080098_2023-12-28_final.stac-item
2023-12-29 09:54:54	ga_ls9c_ard_3-2-1_096077_2023-12-29_final.stac-item
2023-12-29 09:55:18	ga_ls9c_ard_3-2-1_096078_2023-12-29_final.stac-item
2023-12-29 09:56:30	ga_ls9c_ard_3-2-1_096081_2023-12-29_final.stac-item
2023-12-29 11:35:23	ga_ls9c_ard_3-2-1_112081_2023-12-29_final.stac-item
2023-12-30 10:39:45	ga_ls9c_ard_3-2-1_103081_2023-12-30_final.stac-item
2023-12-30 14:03:54	ga_ls9c_ard_3-2-1_135097_2023-12-30_final.stac-item
2023-12-31 09:42:55	ga_ls9c_ard_3-2-1_094078_2023-12-31_final.stac-item
2023-12-31 09:43:19	ga_ls9c_ard_3-2-1_094079_2023-12-31_final.stac-item
2023-12-31 09:44:55	ga_ls9c_ard_3-2-1_094083_2023-12-31_final.stac-item

Return to ga_ls9c_ard_3 across December 2023 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

2023

December

All days