Search ga_ls9c_ard_3 across March 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
2022-03-01 09:34:40	ga_ls9c_ard_3-2-1_092089_2022-03-01_final.stac-item
2022-03-01 11:06:46	ga_ls9c_ard_3-2-1_108072_2022-03-01_final.stac-item
2022-03-01 11:09:58	ga_ls9c_ard_3-2-1_108080_2022-03-01_final.stac-item
2022-03-02 10:14:20	ga_ls9c_ard_3-2-1_099080_2022-03-02_final.stac-item
2022-03-02 10:16:20	ga_ls9c_ard_3-2-1_099085_2022-03-02_final.stac-item
2022-03-03 09:18:43	ga_ls9c_ard_3-2-1_090080_2022-03-02_final.stac-item
2022-03-03 09:20:42	ga_ls9c_ard_3-2-1_090085_2022-03-02_final.stac-item
2022-03-03 09:21:06	ga_ls9c_ard_3-2-1_090086_2022-03-02_final.stac-item
2022-03-03 09:22:18	ga_ls9c_ard_3-2-1_090089_2022-03-02_final.stac-item
2022-03-03 10:54:24	ga_ls9c_ard_3-2-1_106072_2022-03-03_final.stac-item
2022-03-03 12:31:18	ga_ls9c_ard_3-2-1_122067_2022-03-03_final.stac-item
2022-03-04 10:03:58	ga_ls9c_ard_3-2-1_097085_2022-03-04_final.stac-item
2022-03-04 11:39:16	ga_ls9c_ard_3-2-1_113076_2022-03-04_final.stac-item
2022-03-05 10:40:27	ga_ls9c_ard_3-2-1_104068_2022-03-05_final.stac-item
2022-03-05 10:41:15	ga_ls9c_ard_3-2-1_104070_2022-03-05_final.stac-item
2022-03-05 10:44:51	ga_ls9c_ard_3-2-1_104079_2022-03-05_final.stac-item
2022-03-05 14:09:48	ga_ls9c_ard_3-2-1_136097_2022-03-05_final.stac-item
2022-03-06 08:17:56	ga_ls9c_ard_3-2-1_079098_2022-03-05_final.stac-item
2022-03-06 09:49:37	ga_ls9c_ard_3-2-1_095080_2022-03-06_final.stac-item
2022-03-06 09:52:01	ga_ls9c_ard_3-2-1_095086_2022-03-06_final.stac-item
2022-03-06 11:24:07	ga_ls9c_ard_3-2-1_111069_2022-03-06_final.stac-item
2022-03-06 11:26:55	ga_ls9c_ard_3-2-1_111076_2022-03-06_final.stac-item
2022-03-06 11:28:30	ga_ls9c_ard_3-2-1_111080_2022-03-06_final.stac-item
2022-03-07 10:30:53	ga_ls9c_ard_3-2-1_102075_2022-03-07_final.stac-item
2022-03-08 09:36:52	ga_ls9c_ard_3-2-1_093079_2022-03-08_final.stac-item
2022-03-08 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-03-08_final.stac-item
2022-03-08 11:14:33	ga_ls9c_ard_3-2-1_109076_2022-03-08_final.stac-item
2022-03-08 11:15:45	ga_ls9c_ard_3-2-1_109079_2022-03-08_final.stac-item
2022-03-08 11:16:09	ga_ls9c_ard_3-2-1_109080_2022-03-08_final.stac-item
2022-03-09 10:17:20	ga_ls9c_ard_3-2-1_100072_2022-03-09_final.stac-item
2022-03-09 10:20:08	ga_ls9c_ard_3-2-1_100079_2022-03-09_final.stac-item
2022-03-09 10:20:32	ga_ls9c_ard_3-2-1_100080_2022-03-09_final.stac-item
2022-03-10 09:21:43	ga_ls9c_ard_3-2-1_091072_2022-03-09_final.stac-item
2022-03-10 09:24:30	ga_ls9c_ard_3-2-1_091079_2022-03-09_final.stac-item
2022-03-10 09:24:54	ga_ls9c_ard_3-2-1_091080_2022-03-09_final.stac-item
2022-03-10 09:28:06	ga_ls9c_ard_3-2-1_091088_2022-03-09_final.stac-item
2022-03-10 09:28:30	ga_ls9c_ard_3-2-1_091089_2022-03-09_final.stac-item
2022-03-10 11:00:36	ga_ls9c_ard_3-2-1_107072_2022-03-10_final.stac-item
2022-03-10 11:03:47	ga_ls9c_ard_3-2-1_107080_2022-03-10_final.stac-item
2022-03-10 12:37:29	ga_ls9c_ard_3-2-1_123067_2022-03-10_final.stac-item
2022-03-11 10:07:46	ga_ls9c_ard_3-2-1_098079_2022-03-11_final.stac-item
2022-03-11 10:08:10	ga_ls9c_ard_3-2-1_098080_2022-03-11_final.stac-item
2022-03-11 11:46:39	ga_ls9c_ard_3-2-1_114079_2022-03-11_final.stac-item
2022-03-12 09:12:09	ga_ls9c_ard_3-2-1_089079_2022-03-11_final.stac-item
2022-03-12 09:12:33	ga_ls9c_ard_3-2-1_089080_2022-03-11_final.stac-item
2022-03-12 09:14:32	ga_ls9c_ard_3-2-1_089085_2022-03-11_final.stac-item
2022-03-12 09:16:08	ga_ls9c_ard_3-2-1_089089_2022-03-11_final.stac-item
2022-03-12 09:16:32	ga_ls9c_ard_3-2-1_089090_2022-03-11_final.stac-item
2022-03-19 10:54:23	ga_ls9c_ard_3-2-1_106072_2022-03-19_final.stac-item
2022-03-19 10:57:11	ga_ls9c_ard_3-2-1_106079_2022-03-19_final.stac-item
2022-03-19 12:31:17	ga_ls9c_ard_3-2-1_122067_2022-03-19_final.stac-item
2022-03-20 10:03:57	ga_ls9c_ard_3-2-1_097085_2022-03-20_final.stac-item
2022-03-20 11:39:14	ga_ls9c_ard_3-2-1_113076_2022-03-20_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-21 10:41:13	ga_ls9c_ard_3-2-1_104070_2022-03-21_final.stac-item
2022-03-21 10:44:48	ga_ls9c_ard_3-2-1_104079_2022-03-21_final.stac-item
2022-03-21 14:09:46	ga_ls9c_ard_3-2-1_136097_2022-03-21_final.stac-item
2022-03-22 08:17:53	ga_ls9c_ard_3-2-1_079098_2022-03-21_final.stac-item
2022-03-22 09:51:58	ga_ls9c_ard_3-2-1_095086_2022-03-22_final.stac-item
2022-03-22 11:24:04	ga_ls9c_ard_3-2-1_111069_2022-03-22_final.stac-item
2022-03-22 11:26:52	ga_ls9c_ard_3-2-1_111076_2022-03-22_final.stac-item
2022-03-22 11:28:28	ga_ls9c_ard_3-2-1_111080_2022-03-22_final.stac-item
2022-03-23 10:28:50	ga_ls9c_ard_3-2-1_102070_2022-03-23_final.stac-item
2022-03-23 10:30:50	ga_ls9c_ard_3-2-1_102075_2022-03-23_final.stac-item
2022-03-23 10:32:26	ga_ls9c_ard_3-2-1_102079_2022-03-23_final.stac-item
2022-03-23 10:32:50	ga_ls9c_ard_3-2-1_102080_2022-03-23_final.stac-item
2022-03-24 09:36:48	ga_ls9c_ard_3-2-1_093079_2022-03-24_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-03-24 11:14:29	ga_ls9c_ard_3-2-1_109076_2022-03-24_final.stac-item
2022-03-24 11:15:41	ga_ls9c_ard_3-2-1_109079_2022-03-24_final.stac-item
2022-03-24 11:16:05	ga_ls9c_ard_3-2-1_109080_2022-03-24_final.stac-item
2022-03-25 10:17:16	ga_ls9c_ard_3-2-1_100072_2022-03-25_final.stac-item
2022-03-25 10:20:27	ga_ls9c_ard_3-2-1_100080_2022-03-25_final.stac-item
2022-03-26 09:24:25	ga_ls9c_ard_3-2-1_091079_2022-03-25_final.stac-item
2022-03-26 09:24:49	ga_ls9c_ard_3-2-1_091080_2022-03-25_final.stac-item
2022-03-26 09:28:01	ga_ls9c_ard_3-2-1_091088_2022-03-25_final.stac-item
2022-03-26 09:28:25	ga_ls9c_ard_3-2-1_091089_2022-03-25_final.stac-item
2022-03-26 11:00:31	ga_ls9c_ard_3-2-1_107072_2022-03-26_final.stac-item
2022-03-26 11:03:18	ga_ls9c_ard_3-2-1_107079_2022-03-26_final.stac-item
2022-03-26 11:03:42	ga_ls9c_ard_3-2-1_107080_2022-03-26_final.stac-item
2022-03-26 12:37:24	ga_ls9c_ard_3-2-1_123067_2022-03-26_final.stac-item
2022-03-27 10:07:41	ga_ls9c_ard_3-2-1_098079_2022-03-27_final.stac-item
2022-03-27 11:46:34	ga_ls9c_ard_3-2-1_114079_2022-03-27_final.stac-item
2022-03-28 09:14:27	ga_ls9c_ard_3-2-1_089085_2022-03-27_final.stac-item
2022-03-28 09:16:03	ga_ls9c_ard_3-2-1_089089_2022-03-27_final.stac-item
2022-03-28 09:16:27	ga_ls9c_ard_3-2-1_089090_2022-03-27_final.stac-item
2022-03-28 10:50:56	ga_ls9c_ard_3-2-1_105079_2022-03-28_final.stac-item
2022-03-29 08:24:01	ga_ls9c_ard_3-2-1_080098_2022-03-28_final.stac-item
2022-03-29 09:51:44	ga_ls9c_ard_3-2-1_096070_2022-03-29_final.stac-item
2022-03-29 09:55:43	ga_ls9c_ard_3-2-1_096080_2022-03-29_final.stac-item
2022-03-29 09:58:07	ga_ls9c_ard_3-2-1_096086_2022-03-29_final.stac-item
2022-03-29 11:33:00	ga_ls9c_ard_3-2-1_112076_2022-03-29_final.stac-item
2022-03-30 10:35:00	ga_ls9c_ard_3-2-1_103070_2022-03-30_final.stac-item
2022-03-30 10:35:47	ga_ls9c_ard_3-2-1_103072_2022-03-30_final.stac-item
2022-03-30 10:36:59	ga_ls9c_ard_3-2-1_103075_2022-03-30_final.stac-item
2022-03-30 10:38:59	ga_ls9c_ard_3-2-1_103080_2022-03-30_final.stac-item
2022-03-30 14:03:32	ga_ls9c_ard_3-2-1_135097_2022-03-30_final.stac-item
2022-03-31 09:45:21	ga_ls9c_ard_3-2-1_094085_2022-03-31_final.stac-item
2022-03-31 11:20:39	ga_ls9c_ard_3-2-1_110076_2022-03-31_final.stac-item
2022-03-31 11:22:15	ga_ls9c_ard_3-2-1_110080_2022-03-31_final.stac-item

Return to ga_ls9c_ard_3 across March 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

March

All days