Search ga_ls8c_ard_3 across July 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
2022-07-01 09:16:33	ga_ls8c_ard_3-2-1_090074_2022-06-30_final
2022-07-01 09:16:57	ga_ls8c_ard_3-2-1_090075_2022-06-30_final
2022-07-01 09:17:21	ga_ls8c_ard_3-2-1_090076_2022-06-30_final
2022-07-01 09:17:44	ga_ls8c_ard_3-2-1_090077_2022-06-30_final
2022-07-01 09:18:08	ga_ls8c_ard_3-2-1_090078_2022-06-30_final
2022-07-01 09:18:32	ga_ls8c_ard_3-2-1_090079_2022-06-30_final
2022-07-01 09:18:56	ga_ls8c_ard_3-2-1_090080_2022-06-30_final
2022-07-01 09:19:20	ga_ls8c_ard_3-2-1_090081_2022-06-30_final
2022-07-01 09:19:44	ga_ls8c_ard_3-2-1_090082_2022-06-30_final
2022-07-01 09:20:08	ga_ls8c_ard_3-2-1_090083_2022-06-30_final
2022-07-01 09:20:32	ga_ls8c_ard_3-2-1_090084_2022-06-30_final
2022-07-01 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-06-30_final
2022-07-01 09:21:20	ga_ls8c_ard_3-2-1_090086_2022-06-30_final
2022-07-01 09:21:44	ga_ls8c_ard_3-2-1_090087_2022-06-30_final
2022-07-01 09:22:08	ga_ls8c_ard_3-2-1_090088_2022-06-30_final
2022-07-01 09:22:32	ga_ls8c_ard_3-2-1_090089_2022-06-30_final
2022-07-01 09:22:56	ga_ls8c_ard_3-2-1_090090_2022-06-30_final
2022-07-01 09:23:20	ga_ls8c_ard_3-2-1_090091_2022-06-30_final
2022-07-01 10:52:38	ga_ls8c_ard_3-2-1_106067_2022-07-01_final
2022-07-01 10:53:02	ga_ls8c_ard_3-2-1_106068_2022-07-01_final
2022-07-01 10:53:26	ga_ls8c_ard_3-2-1_106069_2022-07-01_final
2022-07-01 10:53:50	ga_ls8c_ard_3-2-1_106070_2022-07-01_final
2022-07-01 10:54:14	ga_ls8c_ard_3-2-1_106071_2022-07-01_final
2022-07-01 10:54:38	ga_ls8c_ard_3-2-1_106072_2022-07-01_final
2022-07-01 10:55:02	ga_ls8c_ard_3-2-1_106073_2022-07-01_final
2022-07-01 10:55:26	ga_ls8c_ard_3-2-1_106074_2022-07-01_final
2022-07-01 10:55:50	ga_ls8c_ard_3-2-1_106075_2022-07-01_final
2022-07-01 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-07-01_final
2022-07-01 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-07-01_final
2022-07-01 10:57:01	ga_ls8c_ard_3-2-1_106078_2022-07-01_final
2022-07-01 10:57:25	ga_ls8c_ard_3-2-1_106079_2022-07-01_final
2022-07-01 10:57:49	ga_ls8c_ard_3-2-1_106080_2022-07-01_final
2022-07-01 10:58:13	ga_ls8c_ard_3-2-1_106081_2022-07-01_final
2022-07-01 10:58:37	ga_ls8c_ard_3-2-1_106082_2022-07-01_final
2022-07-01 10:59:01	ga_ls8c_ard_3-2-1_106083_2022-07-01_final
2022-07-01 12:31:31	ga_ls8c_ard_3-2-1_122067_2022-07-01_final
2022-07-02 09:57:01	ga_ls8c_ard_3-2-1_097067_2022-07-02_final
2022-07-02 09:57:25	ga_ls8c_ard_3-2-1_097068_2022-07-02_final
2022-07-02 09:57:49	ga_ls8c_ard_3-2-1_097069_2022-07-02_final
2022-07-02 09:58:13	ga_ls8c_ard_3-2-1_097070_2022-07-02_final
2022-07-02 09:58:37	ga_ls8c_ard_3-2-1_097071_2022-07-02_final
2022-07-02 09:59:00	ga_ls8c_ard_3-2-1_097072_2022-07-02_final
2022-07-02 09:59:24	ga_ls8c_ard_3-2-1_097073_2022-07-02_final
2022-07-02 09:59:48	ga_ls8c_ard_3-2-1_097074_2022-07-02_final
2022-07-02 10:00:12	ga_ls8c_ard_3-2-1_097075_2022-07-02_final
2022-07-02 10:00:36	ga_ls8c_ard_3-2-1_097076_2022-07-02_final
2022-07-02 10:01:00	ga_ls8c_ard_3-2-1_097077_2022-07-02_final
2022-07-02 10:01:24	ga_ls8c_ard_3-2-1_097078_2022-07-02_final
2022-07-02 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-07-02_final
2022-07-02 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-07-02_final
2022-07-02 10:02:36	ga_ls8c_ard_3-2-1_097081_2022-07-02_final
2022-07-02 10:03:00	ga_ls8c_ard_3-2-1_097082_2022-07-02_final
2022-07-02 10:03:24	ga_ls8c_ard_3-2-1_097083_2022-07-02_final
2022-07-02 10:03:48	ga_ls8c_ard_3-2-1_097084_2022-07-02_final
2022-07-02 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-02_final
2022-07-04 11:23:56	ga_ls8c_ard_3-2-1_111068_2022-07-04_final
2022-07-04 11:24:20	ga_ls8c_ard_3-2-1_111069_2022-07-04_final
2022-07-04 11:24:44	ga_ls8c_ard_3-2-1_111070_2022-07-04_final
2022-07-04 11:25:08	ga_ls8c_ard_3-2-1_111071_2022-07-04_final
2022-07-04 11:25:32	ga_ls8c_ard_3-2-1_111072_2022-07-04_final
2022-07-04 11:25:56	ga_ls8c_ard_3-2-1_111073_2022-07-04_final
2022-07-04 11:26:20	ga_ls8c_ard_3-2-1_111074_2022-07-04_final
2022-07-04 11:26:44	ga_ls8c_ard_3-2-1_111075_2022-07-04_final
2022-07-04 11:27:08	ga_ls8c_ard_3-2-1_111076_2022-07-04_final
2022-07-04 11:27:32	ga_ls8c_ard_3-2-1_111077_2022-07-04_final
2022-07-04 11:27:56	ga_ls8c_ard_3-2-1_111078_2022-07-04_final
2022-07-04 11:28:20	ga_ls8c_ard_3-2-1_111079_2022-07-04_final
2022-07-04 11:28:43	ga_ls8c_ard_3-2-1_111080_2022-07-04_final
2022-07-04 11:29:07	ga_ls8c_ard_3-2-1_111081_2022-07-04_final
2022-07-04 11:29:31	ga_ls8c_ard_3-2-1_111082_2022-07-04_final
2022-07-04 11:29:55	ga_ls8c_ard_3-2-1_111083_2022-07-04_final
2022-07-04 11:30:19	ga_ls8c_ard_3-2-1_111084_2022-07-04_final
2022-07-05 10:28:19	ga_ls8c_ard_3-2-1_102068_2022-07-05_final
2022-07-05 10:28:43	ga_ls8c_ard_3-2-1_102069_2022-07-05_final
2022-07-05 10:29:07	ga_ls8c_ard_3-2-1_102070_2022-07-05_final
2022-07-05 10:29:31	ga_ls8c_ard_3-2-1_102071_2022-07-05_final
2022-07-05 10:29:55	ga_ls8c_ard_3-2-1_102072_2022-07-05_final
2022-07-05 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-07-05_final
2022-07-05 10:30:42	ga_ls8c_ard_3-2-1_102074_2022-07-05_final
2022-07-05 10:31:06	ga_ls8c_ard_3-2-1_102075_2022-07-05_final
2022-07-05 10:31:30	ga_ls8c_ard_3-2-1_102076_2022-07-05_final
2022-07-05 10:31:54	ga_ls8c_ard_3-2-1_102077_2022-07-05_final
2022-07-05 10:32:18	ga_ls8c_ard_3-2-1_102078_2022-07-05_final
2022-07-05 10:32:42	ga_ls8c_ard_3-2-1_102079_2022-07-05_final
2022-07-05 10:33:06	ga_ls8c_ard_3-2-1_102080_2022-07-05_final
2022-07-05 10:33:30	ga_ls8c_ard_3-2-1_102081_2022-07-05_final
2022-07-05 10:33:54	ga_ls8c_ard_3-2-1_102082_2022-07-05_final
2022-07-07 10:17:09	ga_ls8c_ard_3-2-1_100071_2022-07-07_final
2022-07-07 10:17:57	ga_ls8c_ard_3-2-1_100073_2022-07-07_final
2022-07-07 10:18:21	ga_ls8c_ard_3-2-1_100074_2022-07-07_final
2022-07-07 10:18:45	ga_ls8c_ard_3-2-1_100075_2022-07-07_final
2022-07-07 10:19:33	ga_ls8c_ard_3-2-1_100077_2022-07-07_final
2022-07-07 10:19:56	ga_ls8c_ard_3-2-1_100078_2022-07-07_final
2022-07-07 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-07-07_final
2022-07-07 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-07-07_final
2022-07-07 10:21:08	ga_ls8c_ard_3-2-1_100081_2022-07-07_final
2022-07-07 10:21:32	ga_ls8c_ard_3-2-1_100082_2022-07-07_final
2022-07-07 10:21:56	ga_ls8c_ard_3-2-1_100083_2022-07-07_final
2022-07-07 10:22:20	ga_ls8c_ard_3-2-1_100084_2022-07-07_final
2022-07-07 11:58:02	ga_ls8c_ard_3-2-1_116076_2022-07-07_final

Return to ga_ls8c_ard_3 across July 2022 overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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

2022

July

All days