Search ga_ls9c_ard_3 across September 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
2023-09-01 09:47:57	ga_ls9c_ard_3-2-1_095076_2023-09-01_final.stac-item
2023-09-01 09:50:44	ga_ls9c_ard_3-2-1_095083_2023-09-01_final.stac-item
2023-09-01 09:51:32	ga_ls9c_ard_3-2-1_095085_2023-09-01_final.stac-item
2023-09-01 11:23:38	ga_ls9c_ard_3-2-1_111068_2023-09-01_final.stac-item
2023-09-01 11:24:02	ga_ls9c_ard_3-2-1_111069_2023-09-01_final.stac-item
2023-09-02 10:28:01	ga_ls9c_ard_3-2-1_102068_2023-09-02_final.stac-item
2023-09-03 09:35:12	ga_ls9c_ard_3-2-1_093075_2023-09-03_final.stac-item
2023-09-03 09:35:36	ga_ls9c_ard_3-2-1_093076_2023-09-03_final.stac-item
2023-09-03 09:40:23	ga_ls9c_ard_3-2-1_093088_2023-09-03_final.stac-item
2023-09-04 10:19:16	ga_ls9c_ard_3-2-1_100077_2023-09-04_final.stac-item
2023-09-04 11:58:33	ga_ls9c_ard_3-2-1_116078_2023-09-04_final.stac-item
2023-09-05 09:22:52	ga_ls9c_ard_3-2-1_091075_2023-09-04_final.stac-item
2023-09-05 09:23:16	ga_ls9c_ard_3-2-1_091076_2023-09-04_final.stac-item
2023-09-05 09:24:51	ga_ls9c_ard_3-2-1_091080_2023-09-04_final.stac-item
2023-09-05 09:27:39	ga_ls9c_ard_3-2-1_091087_2023-09-04_final.stac-item
2023-09-05 09:28:03	ga_ls9c_ard_3-2-1_091088_2023-09-04_final.stac-item
2023-09-05 09:28:51	ga_ls9c_ard_3-2-1_091090_2023-09-04_final.stac-item
2023-09-05 10:59:21	ga_ls9c_ard_3-2-1_107069_2023-09-05_final.stac-item
2023-09-06 10:02:33	ga_ls9c_ard_3-2-1_098066_2023-09-06_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-09-06 10:10:08	ga_ls9c_ard_3-2-1_098085_2023-09-06_final.stac-item
2023-09-06 11:47:01	ga_ls9c_ard_3-2-1_114080_2023-09-06_final.stac-item
2023-09-07 09:11:20	ga_ls9c_ard_3-2-1_089077_2023-09-06_final.stac-item
2023-09-07 09:16:31	ga_ls9c_ard_3-2-1_089090_2023-09-06_final.stac-item
2023-09-07 10:46:13	ga_ls9c_ard_3-2-1_105067_2023-09-07_final.stac-item
2023-09-07 10:46:37	ga_ls9c_ard_3-2-1_105068_2023-09-07_final.stac-item
2023-09-07 10:49:49	ga_ls9c_ard_3-2-1_105076_2023-09-07_final.stac-item
2023-09-08 09:57:48	ga_ls9c_ard_3-2-1_096085_2023-09-08_final.stac-item
2023-09-08 11:34:17	ga_ls9c_ard_3-2-1_112079_2023-09-08_final.stac-item
2023-09-09 10:34:17	ga_ls9c_ard_3-2-1_103068_2023-09-09_final.stac-item
2023-09-10 09:41:28	ga_ls9c_ard_3-2-1_094075_2023-09-10_final.stac-item
2023-09-10 09:41:52	ga_ls9c_ard_3-2-1_094076_2023-09-10_final.stac-item
2023-09-10 09:45:27	ga_ls9c_ard_3-2-1_094085_2023-09-10_final.stac-item
2023-09-10 11:21:57	ga_ls9c_ard_3-2-1_110079_2023-09-10_final.stac-item
2023-09-12 09:29:07	ga_ls9c_ard_3-2-1_092075_2023-09-11_final.stac-item
2023-09-12 09:29:31	ga_ls9c_ard_3-2-1_092076_2023-09-11_final.stac-item
2023-09-12 09:33:55	ga_ls9c_ard_3-2-1_092087_2023-09-12_final.stac-item
2023-09-12 09:34:19	ga_ls9c_ard_3-2-1_092088_2023-09-12_final.stac-item
2023-09-12 09:35:07	ga_ls9c_ard_3-2-1_092090_2023-09-12_final.stac-item
2023-09-13 10:08:48	ga_ls9c_ard_3-2-1_099066_2023-09-13_final.stac-item
2023-09-13 10:09:12	ga_ls9c_ard_3-2-1_099067_2023-09-13_final.stac-item
2023-09-13 10:16:23	ga_ls9c_ard_3-2-1_099085_2023-09-13_final.stac-item
2023-09-13 11:53:16	ga_ls9c_ard_3-2-1_115080_2023-09-13_final.stac-item
2023-09-14 09:17:34	ga_ls9c_ard_3-2-1_090077_2023-09-13_final.stac-item
2023-09-14 09:21:34	ga_ls9c_ard_3-2-1_090087_2023-09-13_final.stac-item
2023-09-14 09:22:46	ga_ls9c_ard_3-2-1_090090_2023-09-13_final.stac-item
2023-09-14 10:52:52	ga_ls9c_ard_3-2-1_106068_2023-09-14_final.stac-item
2023-09-15 09:56:51	ga_ls9c_ard_3-2-1_097067_2023-09-15_final.stac-item
2023-09-15 09:57:39	ga_ls9c_ard_3-2-1_097069_2023-09-15_final.stac-item
2023-09-15 09:58:03	ga_ls9c_ard_3-2-1_097070_2023-09-15_final.stac-item
2023-09-15 10:04:02	ga_ls9c_ard_3-2-1_097085_2023-09-15_final.stac-item
2023-09-15 11:40:31	ga_ls9c_ard_3-2-1_113079_2023-09-15_final.stac-item
2023-09-16 10:40:31	ga_ls9c_ard_3-2-1_104068_2023-09-16_final.stac-item
2023-09-17 09:48:05	ga_ls9c_ard_3-2-1_095076_2023-09-17_final.stac-item
2023-09-17 09:50:52	ga_ls9c_ard_3-2-1_095083_2023-09-17_final.stac-item
2023-09-17 09:51:40	ga_ls9c_ard_3-2-1_095085_2023-09-17_final.stac-item
2023-09-17 11:28:10	ga_ls9c_ard_3-2-1_111079_2023-09-17_final.stac-item
2023-09-18 10:28:09	ga_ls9c_ard_3-2-1_102068_2023-09-18_final.stac-item
2023-09-19 09:35:19	ga_ls9c_ard_3-2-1_093075_2023-09-19_final.stac-item
2023-09-19 09:35:43	ga_ls9c_ard_3-2-1_093076_2023-09-19_final.stac-item
2023-09-19 09:40:30	ga_ls9c_ard_3-2-1_093088_2023-09-19_final.stac-item
2023-09-20 10:19:22	ga_ls9c_ard_3-2-1_100077_2023-09-20_final.stac-item
2023-09-20 11:58:39	ga_ls9c_ard_3-2-1_116078_2023-09-20_final.stac-item
2023-09-21 09:22:57	ga_ls9c_ard_3-2-1_091075_2023-09-20_final.stac-item
2023-09-21 09:23:21	ga_ls9c_ard_3-2-1_091076_2023-09-20_final.stac-item
2023-09-21 09:24:57	ga_ls9c_ard_3-2-1_091080_2023-09-20_final.stac-item
2023-09-21 09:27:44	ga_ls9c_ard_3-2-1_091087_2023-09-20_final.stac-item
2023-09-21 09:28:08	ga_ls9c_ard_3-2-1_091088_2023-09-20_final.stac-item
2023-09-21 09:28:56	ga_ls9c_ard_3-2-1_091090_2023-09-20_final.stac-item
2023-09-22 10:02:37	ga_ls9c_ard_3-2-1_098066_2023-09-22_final.stac-item
2023-09-22 10:03:01	ga_ls9c_ard_3-2-1_098067_2023-09-22_final.stac-item
2023-09-22 10:10:12	ga_ls9c_ard_3-2-1_098085_2023-09-22_final.stac-item
2023-09-22 11:47:05	ga_ls9c_ard_3-2-1_114080_2023-09-22_final.stac-item
2023-09-23 09:10:34	ga_ls9c_ard_3-2-1_089075_2023-09-22_final.stac-item
2023-09-23 09:11:22	ga_ls9c_ard_3-2-1_089077_2023-09-22_final.stac-item
2023-09-23 10:46:16	ga_ls9c_ard_3-2-1_105067_2023-09-23_final.stac-item
2023-09-23 10:46:40	ga_ls9c_ard_3-2-1_105068_2023-09-23_final.stac-item
2023-09-24 09:57:49	ga_ls9c_ard_3-2-1_096085_2023-09-24_final.stac-item
2023-09-25 10:34:17	ga_ls9c_ard_3-2-1_103068_2023-09-25_final.stac-item
2023-09-26 09:41:26	ga_ls9c_ard_3-2-1_094075_2023-09-26_final.stac-item
2023-09-26 09:41:50	ga_ls9c_ard_3-2-1_094076_2023-09-26_final.stac-item
2023-09-26 09:45:26	ga_ls9c_ard_3-2-1_094085_2023-09-26_final.stac-item
2023-09-26 11:21:55	ga_ls9c_ard_3-2-1_110079_2023-09-26_final.stac-item
2023-09-26 11:24:19	ga_ls9c_ard_3-2-1_110085_2023-09-26_final.stac-item
2023-09-27 10:25:29	ga_ls9c_ard_3-2-1_101077_2023-09-27_final.stac-item
2023-09-28 09:29:03	ga_ls9c_ard_3-2-1_092075_2023-09-27_final.stac-item
2023-09-28 09:29:27	ga_ls9c_ard_3-2-1_092076_2023-09-27_final.stac-item
2023-09-28 09:33:50	ga_ls9c_ard_3-2-1_092087_2023-09-28_final.stac-item
2023-09-28 09:34:14	ga_ls9c_ard_3-2-1_092088_2023-09-28_final.stac-item
2023-09-28 09:35:02	ga_ls9c_ard_3-2-1_092090_2023-09-28_final.stac-item
2023-09-29 10:08:45	ga_ls9c_ard_3-2-1_099066_2023-09-29_final.stac-item
2023-09-29 10:09:08	ga_ls9c_ard_3-2-1_099067_2023-09-29_final.stac-item
2023-09-29 10:14:20	ga_ls9c_ard_3-2-1_099080_2023-09-29_final.stac-item
2023-09-29 10:16:19	ga_ls9c_ard_3-2-1_099085_2023-09-29_final.stac-item
2023-09-29 11:53:13	ga_ls9c_ard_3-2-1_115080_2023-09-29_final.stac-item
2023-09-30 09:17:32	ga_ls9c_ard_3-2-1_090077_2023-09-29_final.stac-item
2023-09-30 09:22:19	ga_ls9c_ard_3-2-1_090089_2023-09-29_final.stac-item
2023-09-30 09:22:43	ga_ls9c_ard_3-2-1_090090_2023-09-29_final.stac-item
2023-09-30 10:52:49	ga_ls9c_ard_3-2-1_106068_2023-09-30_final.stac-item
2023-09-30 10:56:01	ga_ls9c_ard_3-2-1_106076_2023-09-30_final.stac-item

Return to ga_ls9c_ard_3 across September 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

September

All days