Search ga_ls8c_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 10:34:15	ga_ls8c_ard_3-2-1_103068_2023-09-01_final
2023-09-01 10:34:39	ga_ls8c_ard_3-2-1_103069_2023-09-01_final
2023-09-01 10:35:02	ga_ls8c_ard_3-2-1_103070_2023-09-01_final
2023-09-01 10:35:26	ga_ls8c_ard_3-2-1_103071_2023-09-01_final
2023-09-01 10:35:50	ga_ls8c_ard_3-2-1_103072_2023-09-01_final
2023-09-01 10:36:14	ga_ls8c_ard_3-2-1_103073_2023-09-01_final
2023-09-01 10:36:38	ga_ls8c_ard_3-2-1_103074_2023-09-01_final
2023-09-01 10:37:02	ga_ls8c_ard_3-2-1_103075_2023-09-01_final
2023-09-01 10:37:26	ga_ls8c_ard_3-2-1_103076_2023-09-01_final
2023-09-01 10:37:50	ga_ls8c_ard_3-2-1_103077_2023-09-01_final
2023-09-01 10:38:14	ga_ls8c_ard_3-2-1_103078_2023-09-01_final
2023-09-01 10:38:38	ga_ls8c_ard_3-2-1_103079_2023-09-01_final
2023-09-01 10:39:02	ga_ls8c_ard_3-2-1_103080_2023-09-01_final
2023-09-01 10:39:26	ga_ls8c_ard_3-2-1_103081_2023-09-01_final
2023-09-01 10:39:50	ga_ls8c_ard_3-2-1_103082_2023-09-01_final
2023-09-01 14:03:35	ga_ls8c_ard_3-2-1_135097_2023-09-01_final
2023-09-02 11:19:30	ga_ls8c_ard_3-2-1_110073_2023-09-02_final
2023-09-02 11:19:54	ga_ls8c_ard_3-2-1_110074_2023-09-02_final
2023-09-02 11:20:18	ga_ls8c_ard_3-2-1_110075_2023-09-02_final
2023-09-02 11:20:42	ga_ls8c_ard_3-2-1_110076_2023-09-02_final
2023-09-02 11:21:06	ga_ls8c_ard_3-2-1_110077_2023-09-02_final
2023-09-02 11:21:29	ga_ls8c_ard_3-2-1_110078_2023-09-02_final
2023-09-02 11:21:53	ga_ls8c_ard_3-2-1_110079_2023-09-02_final
2023-09-02 11:22:17	ga_ls8c_ard_3-2-1_110080_2023-09-02_final
2023-09-02 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-09-02_final
2023-09-02 11:23:05	ga_ls8c_ard_3-2-1_110082_2023-09-02_final
2023-09-02 11:23:29	ga_ls8c_ard_3-2-1_110083_2023-09-02_final
2023-09-02 11:23:53	ga_ls8c_ard_3-2-1_110084_2023-09-02_final
2023-09-02 11:24:17	ga_ls8c_ard_3-2-1_110085_2023-09-02_final
2023-09-03 08:48:35	ga_ls8c_ard_3-2-1_085082_2023-09-02_final
2023-09-03 10:22:16	ga_ls8c_ard_3-2-1_101069_2023-09-03_final
2023-09-03 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-09-03_final
2023-09-03 10:23:04	ga_ls8c_ard_3-2-1_101071_2023-09-03_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-03 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-09-03_final
2023-09-03 10:24:16	ga_ls8c_ard_3-2-1_101074_2023-09-03_final
2023-09-03 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-09-03_final
2023-09-03 10:25:04	ga_ls8c_ard_3-2-1_101076_2023-09-03_final
2023-09-03 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-09-03_final
2023-09-03 10:25:52	ga_ls8c_ard_3-2-1_101078_2023-09-03_final
2023-09-03 10:26:16	ga_ls8c_ard_3-2-1_101079_2023-09-03_final
2023-09-03 10:26:40	ga_ls8c_ard_3-2-1_101080_2023-09-03_final
2023-09-03 10:27:04	ga_ls8c_ard_3-2-1_101081_2023-09-03_final
2023-09-03 10:27:28	ga_ls8c_ard_3-2-1_101082_2023-09-03_final
2023-09-03 10:27:52	ga_ls8c_ard_3-2-1_101083_2023-09-03_final
2023-09-04 09:27:27	ga_ls8c_ard_3-2-1_092071_2023-09-03_final
2023-09-04 09:27:50	ga_ls8c_ard_3-2-1_092072_2023-09-03_final
2023-09-04 09:28:14	ga_ls8c_ard_3-2-1_092073_2023-09-03_final
2023-09-04 09:28:38	ga_ls8c_ard_3-2-1_092074_2023-09-03_final
2023-09-04 09:29:02	ga_ls8c_ard_3-2-1_092075_2023-09-03_final
2023-09-04 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-09-03_final
2023-09-04 09:29:50	ga_ls8c_ard_3-2-1_092077_2023-09-03_final
2023-09-04 09:30:14	ga_ls8c_ard_3-2-1_092078_2023-09-04_final
2023-09-04 09:30:38	ga_ls8c_ard_3-2-1_092079_2023-09-04_final
2023-09-04 09:31:02	ga_ls8c_ard_3-2-1_092080_2023-09-04_final
2023-09-04 09:31:26	ga_ls8c_ard_3-2-1_092081_2023-09-04_final
2023-09-04 09:31:50	ga_ls8c_ard_3-2-1_092082_2023-09-04_final
2023-09-04 09:32:14	ga_ls8c_ard_3-2-1_092083_2023-09-04_final
2023-09-04 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-09-04_final
2023-09-04 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-09-04_final
2023-09-04 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-09-04_final
2023-09-04 09:33:50	ga_ls8c_ard_3-2-1_092087_2023-09-04_final
2023-09-04 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-09-04_final
2023-09-04 09:34:38	ga_ls8c_ard_3-2-1_092089_2023-09-04_final
2023-09-04 09:35:02	ga_ls8c_ard_3-2-1_092090_2023-09-04_final
2023-09-04 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-09-04_final
2023-09-04 11:05:56	ga_ls8c_ard_3-2-1_108070_2023-09-04_final
2023-09-04 11:06:20	ga_ls8c_ard_3-2-1_108071_2023-09-04_final
2023-09-04 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-09-04_final
2023-09-04 11:07:07	ga_ls8c_ard_3-2-1_108073_2023-09-04_final
2023-09-04 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-09-04_final
2023-09-04 11:07:55	ga_ls8c_ard_3-2-1_108075_2023-09-04_final
2023-09-04 11:08:19	ga_ls8c_ard_3-2-1_108076_2023-09-04_final
2023-09-04 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-09-04_final
2023-09-04 11:09:07	ga_ls8c_ard_3-2-1_108078_2023-09-04_final
2023-09-04 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-09-04_final
2023-09-04 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-09-04_final
2023-09-04 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-09-04_final
2023-09-04 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-09-04_final
2023-09-04 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-09-04_final
2023-09-04 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-09-04_final
2023-09-05 10:08:42	ga_ls8c_ard_3-2-1_099066_2023-09-05_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-05 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-09-05_final
2023-09-05 10:09:54	ga_ls8c_ard_3-2-1_099069_2023-09-05_final
2023-09-05 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-09-05_final
2023-09-05 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-09-05_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-09-05_final
2023-09-05 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-09-05_final
2023-09-05 10:11:54	ga_ls8c_ard_3-2-1_099074_2023-09-05_final
2023-09-05 10:12:17	ga_ls8c_ard_3-2-1_099075_2023-09-05_final
2023-09-05 10:12:41	ga_ls8c_ard_3-2-1_099076_2023-09-05_final
2023-09-05 10:13:05	ga_ls8c_ard_3-2-1_099077_2023-09-05_final
2023-09-05 10:13:29	ga_ls8c_ard_3-2-1_099078_2023-09-05_final
2023-09-05 10:13:53	ga_ls8c_ard_3-2-1_099079_2023-09-05_final
2023-09-15 09:16:10	ga_ls8c_ard_3-2-1_089089_2023-09-14_final
2023-09-15 09:16:34	ga_ls8c_ard_3-2-1_089090_2023-09-14_final
2023-09-15 10:47:04	ga_ls8c_ard_3-2-1_105069_2023-09-15_final
2023-09-15 10:47:28	ga_ls8c_ard_3-2-1_105070_2023-09-15_final
2023-09-15 10:47:52	ga_ls8c_ard_3-2-1_105071_2023-09-15_final

Return to ga_ls8c_ard_3 across September 2023 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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2023

September

All days