Search ga_ls9c_ard_3 across October 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
2023-10-01 10:01:36	ga_ls9c_ard_3-2-1_097079_2023-10-01_final.stac-item
2023-10-01 11:38:30	ga_ls9c_ard_3-2-1_113074_2023-10-01_final.stac-item
2023-10-03 11:25:46	ga_ls9c_ard_3-2-1_111073_2023-10-03_final.stac-item
2023-10-03 11:26:10	ga_ls9c_ard_3-2-1_111074_2023-10-03_final.stac-item
2023-10-03 11:28:58	ga_ls9c_ard_3-2-1_111081_2023-10-03_final.stac-item
2023-10-03 11:30:10	ga_ls9c_ard_3-2-1_111084_2023-10-03_final.stac-item
2023-10-04 10:32:33	ga_ls9c_ard_3-2-1_102079_2023-10-04_final.stac-item
2023-10-05 09:35:21	ga_ls9c_ard_3-2-1_093075_2023-10-05_final.stac-item
2023-10-05 09:37:45	ga_ls9c_ard_3-2-1_093081_2023-10-05_final.stac-item
2023-10-05 09:39:20	ga_ls9c_ard_3-2-1_093085_2023-10-05_final.stac-item
2023-10-05 11:13:26	ga_ls9c_ard_3-2-1_109073_2023-10-05_final.stac-item
2023-10-05 11:13:50	ga_ls9c_ard_3-2-1_109074_2023-10-05_final.stac-item
2023-10-05 11:14:14	ga_ls9c_ard_3-2-1_109075_2023-10-05_final.stac-item
2023-10-05 11:16:38	ga_ls9c_ard_3-2-1_109081_2023-10-05_final.stac-item
2023-10-05 11:17:49	ga_ls9c_ard_3-2-1_109084_2023-10-05_final.stac-item
2023-10-06 10:18:37	ga_ls9c_ard_3-2-1_100075_2023-10-06_final.stac-item
2023-10-06 10:20:13	ga_ls9c_ard_3-2-1_100079_2023-10-06_final.stac-item
2023-10-06 10:21:01	ga_ls9c_ard_3-2-1_100081_2023-10-06_final.stac-item
2023-10-07 09:23:00	ga_ls9c_ard_3-2-1_091075_2023-10-06_final.stac-item
2023-10-07 09:26:36	ga_ls9c_ard_3-2-1_091084_2023-10-06_final.stac-item
2023-10-07 09:27:48	ga_ls9c_ard_3-2-1_091087_2023-10-06_final.stac-item
2023-10-07 11:04:17	ga_ls9c_ard_3-2-1_107081_2023-10-07_final.stac-item
2023-10-07 11:05:29	ga_ls9c_ard_3-2-1_107084_2023-10-07_final.stac-item
2023-10-08 10:07:52	ga_ls9c_ard_3-2-1_098079_2023-10-08_final.stac-item
2023-10-08 10:09:52	ga_ls9c_ard_3-2-1_098084_2023-10-08_final.stac-item
2023-10-08 11:47:09	ga_ls9c_ard_3-2-1_114080_2023-10-08_final.stac-item
2023-10-09 09:16:39	ga_ls9c_ard_3-2-1_089090_2023-10-08_final.stac-item
2023-10-10 11:32:26	ga_ls9c_ard_3-2-1_112074_2023-10-10_final.stac-item
2023-10-10 11:35:13	ga_ls9c_ard_3-2-1_112081_2023-10-10_final.stac-item
2023-10-12 09:41:37	ga_ls9c_ard_3-2-1_094075_2023-10-12_final.stac-item
2023-10-12 11:19:42	ga_ls9c_ard_3-2-1_110073_2023-10-12_final.stac-item
2023-10-12 11:20:06	ga_ls9c_ard_3-2-1_110074_2023-10-12_final.stac-item
2023-10-12 11:20:30	ga_ls9c_ard_3-2-1_110075_2023-10-12_final.stac-item
2023-10-12 11:22:54	ga_ls9c_ard_3-2-1_110081_2023-10-12_final.stac-item
2023-10-12 11:24:05	ga_ls9c_ard_3-2-1_110084_2023-10-12_final.stac-item
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_final.stac-item
2023-10-13 10:26:29	ga_ls9c_ard_3-2-1_101079_2023-10-13_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-10-14 09:31:16	ga_ls9c_ard_3-2-1_092080_2023-10-14_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-14 09:33:16	ga_ls9c_ard_3-2-1_092085_2023-10-14_final.stac-item
2023-10-14 11:08:10	ga_ls9c_ard_3-2-1_108075_2023-10-14_final.stac-item
2023-10-14 11:10:33	ga_ls9c_ard_3-2-1_108081_2023-10-14_final.stac-item
2023-10-14 11:11:45	ga_ls9c_ard_3-2-1_108084_2023-10-14_final.stac-item
2023-10-15 10:12:33	ga_ls9c_ard_3-2-1_099075_2023-10-15_final.stac-item
2023-10-15 10:14:09	ga_ls9c_ard_3-2-1_099079_2023-10-15_final.stac-item
2023-10-15 11:53:26	ga_ls9c_ard_3-2-1_115080_2023-10-15_final.stac-item
2023-10-16 09:21:43	ga_ls9c_ard_3-2-1_090087_2023-10-15_final.stac-item
2023-10-16 09:22:55	ga_ls9c_ard_3-2-1_090090_2023-10-15_final.stac-item
2023-10-17 10:01:48	ga_ls9c_ard_3-2-1_097079_2023-10-17_final.stac-item
2023-10-17 11:38:41	ga_ls9c_ard_3-2-1_113074_2023-10-17_final.stac-item
2023-10-19 11:25:56	ga_ls9c_ard_3-2-1_111073_2023-10-19_final.stac-item
2023-10-19 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_final.stac-item
2023-10-19 11:28:20	ga_ls9c_ard_3-2-1_111079_2023-10-19_final.stac-item
2023-10-19 11:29:08	ga_ls9c_ard_3-2-1_111081_2023-10-19_final.stac-item
2023-10-20 10:33:30	ga_ls9c_ard_3-2-1_102081_2023-10-20_final.stac-item
2023-10-21 09:35:29	ga_ls9c_ard_3-2-1_093075_2023-10-21_final.stac-item
2023-10-21 09:37:53	ga_ls9c_ard_3-2-1_093081_2023-10-21_final.stac-item
2023-10-21 09:39:29	ga_ls9c_ard_3-2-1_093085_2023-10-21_final.stac-item
2023-10-21 11:13:35	ga_ls9c_ard_3-2-1_109073_2023-10-21_final.stac-item
2023-10-21 11:13:58	ga_ls9c_ard_3-2-1_109074_2023-10-21_final.stac-item
2023-10-21 11:14:22	ga_ls9c_ard_3-2-1_109075_2023-10-21_final.stac-item
2023-10-21 11:15:58	ga_ls9c_ard_3-2-1_109079_2023-10-21_final.stac-item
2023-10-21 11:16:46	ga_ls9c_ard_3-2-1_109081_2023-10-21_final.stac-item
2023-10-21 11:17:58	ga_ls9c_ard_3-2-1_109084_2023-10-21_final.stac-item
2023-10-22 10:18:45	ga_ls9c_ard_3-2-1_100075_2023-10-22_final.stac-item
2023-10-22 10:20:21	ga_ls9c_ard_3-2-1_100079_2023-10-22_final.stac-item
2023-10-22 10:21:09	ga_ls9c_ard_3-2-1_100081_2023-10-22_final.stac-item
2023-10-23 09:22:19	ga_ls9c_ard_3-2-1_091073_2023-10-22_final.stac-item
2023-10-23 09:23:07	ga_ls9c_ard_3-2-1_091075_2023-10-22_final.stac-item
2023-10-23 09:26:43	ga_ls9c_ard_3-2-1_091084_2023-10-22_final.stac-item
2023-10-23 09:27:55	ga_ls9c_ard_3-2-1_091087_2023-10-22_final.stac-item
2023-10-23 11:02:00	ga_ls9c_ard_3-2-1_107075_2023-10-23_final.stac-item
2023-10-23 11:04:24	ga_ls9c_ard_3-2-1_107081_2023-10-23_final.stac-item
2023-10-23 11:05:36	ga_ls9c_ard_3-2-1_107084_2023-10-23_final.stac-item
2023-10-24 10:07:59	ga_ls9c_ard_3-2-1_098079_2023-10-24_final.stac-item
2023-10-24 10:09:58	ga_ls9c_ard_3-2-1_098084_2023-10-24_final.stac-item
2023-10-24 11:47:16	ga_ls9c_ard_3-2-1_114080_2023-10-24_final.stac-item
2023-10-25 09:16:44	ga_ls9c_ard_3-2-1_089090_2023-10-24_final.stac-item
2023-10-26 11:32:29	ga_ls9c_ard_3-2-1_112074_2023-10-26_final.stac-item
2023-10-26 11:35:17	ga_ls9c_ard_3-2-1_112081_2023-10-26_final.stac-item
2023-10-28 09:41:38	ga_ls9c_ard_3-2-1_094075_2023-10-28_final.stac-item
2023-10-28 11:20:07	ga_ls9c_ard_3-2-1_110074_2023-10-28_final.stac-item
2023-10-28 11:20:31	ga_ls9c_ard_3-2-1_110075_2023-10-28_final.stac-item
2023-10-28 11:22:06	ga_ls9c_ard_3-2-1_110079_2023-10-28_final.stac-item
2023-10-28 11:22:54	ga_ls9c_ard_3-2-1_110081_2023-10-28_final.stac-item
2023-10-28 11:24:06	ga_ls9c_ard_3-2-1_110084_2023-10-28_final.stac-item
2023-10-29 10:24:52	ga_ls9c_ard_3-2-1_101075_2023-10-29_final.stac-item
2023-10-29 10:26:28	ga_ls9c_ard_3-2-1_101079_2023-10-29_final.stac-item
2023-10-29 10:27:16	ga_ls9c_ard_3-2-1_101081_2023-10-29_final.stac-item
2023-10-30 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-10-29_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-10-30 09:31:38	ga_ls9c_ard_3-2-1_092081_2023-10-30_final.stac-item
2023-10-30 09:33:14	ga_ls9c_ard_3-2-1_092085_2023-10-30_final.stac-item
2023-10-30 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-10-30_final.stac-item
2023-10-30 11:10:31	ga_ls9c_ard_3-2-1_108081_2023-10-30_final.stac-item
2023-10-30 11:11:43	ga_ls9c_ard_3-2-1_108084_2023-10-30_final.stac-item
2023-10-31 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-10-31_final.stac-item
2023-10-31 10:14:05	ga_ls9c_ard_3-2-1_099079_2023-10-31_final.stac-item

Return to ga_ls9c_ard_3 across October 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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2023

October

All days