Search ga_ls8c_ard_3 whole collection

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
2023-10-14 10:21:04	ga_ls8c_ard_3-2-1_100081_2023-10-14_final
2023-10-14 10:21:28	ga_ls8c_ard_3-2-1_100082_2023-10-14_final
2023-10-14 10:21:52	ga_ls8c_ard_3-2-1_100083_2023-10-14_final
2023-10-14 10:22:16	ga_ls8c_ard_3-2-1_100084_2023-10-14_final
2023-10-16 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-10-16_final
2023-10-16 10:09:54	ga_ls8c_ard_3-2-1_098084_2023-10-16_final
2023-10-23 10:14:05	ga_ls8c_ard_3-2-1_099079_2023-10-23_final
2023-10-23 10:14:29	ga_ls8c_ard_3-2-1_099080_2023-10-23_final
2023-10-23 10:14:53	ga_ls8c_ard_3-2-1_099081_2023-10-23_final
2023-10-23 10:15:17	ga_ls8c_ard_3-2-1_099082_2023-10-23_final
2023-10-23 10:15:41	ga_ls8c_ard_3-2-1_099083_2023-10-23_final
2023-10-23 10:16:05	ga_ls8c_ard_3-2-1_099084_2023-10-23_final
2023-10-30 10:18:43	ga_ls8c_ard_3-2-1_100075_2023-10-30_final
2023-10-30 10:19:07	ga_ls8c_ard_3-2-1_100076_2023-10-30_final
2023-10-30 10:19:31	ga_ls8c_ard_3-2-1_100077_2023-10-30_final
2023-10-30 10:19:55	ga_ls8c_ard_3-2-1_100078_2023-10-30_final
2023-10-30 10:20:19	ga_ls8c_ard_3-2-1_100079_2023-10-30_final
2023-10-30 10:21:07	ga_ls8c_ard_3-2-1_100081_2023-10-30_final
2023-11-01 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-01_final
2023-11-01 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-11-01_final
2023-11-01 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-11-01_final
2023-11-02 10:46:25	ga_ls8c_ard_3-2-1_105067_2023-11-02_final
2023-11-02 10:46:49	ga_ls8c_ard_3-2-1_105068_2023-11-02_final
2023-11-04 10:34:27	ga_ls8c_ard_3-2-1_103068_2023-11-04_final
2023-11-04 10:34:51	ga_ls8c_ard_3-2-1_103069_2023-11-04_final
2023-11-04 10:35:15	ga_ls8c_ard_3-2-1_103070_2023-11-04_final
2023-11-04 10:35:39	ga_ls8c_ard_3-2-1_103071_2023-11-04_final
2023-11-04 10:36:03	ga_ls8c_ard_3-2-1_103072_2023-11-04_final
2023-11-04 10:36:27	ga_ls8c_ard_3-2-1_103073_2023-11-04_final
2023-11-04 10:36:51	ga_ls8c_ard_3-2-1_103074_2023-11-04_final
2023-11-04 10:37:15	ga_ls8c_ard_3-2-1_103075_2023-11-04_final
2023-11-04 10:37:39	ga_ls8c_ard_3-2-1_103076_2023-11-04_final
2023-11-04 10:38:03	ga_ls8c_ard_3-2-1_103077_2023-11-04_final
2023-11-06 10:22:52	ga_ls8c_ard_3-2-1_101070_2023-11-06_final
2023-11-06 10:23:16	ga_ls8c_ard_3-2-1_101071_2023-11-06_final
2023-11-06 10:23:40	ga_ls8c_ard_3-2-1_101072_2023-11-06_final
2023-11-06 10:24:04	ga_ls8c_ard_3-2-1_101073_2023-11-06_final
2023-11-06 10:24:28	ga_ls8c_ard_3-2-1_101074_2023-11-06_final
2023-11-06 10:24:52	ga_ls8c_ard_3-2-1_101075_2023-11-06_final
2023-11-06 10:25:16	ga_ls8c_ard_3-2-1_101076_2023-11-06_final
2023-11-06 10:25:40	ga_ls8c_ard_3-2-1_101077_2023-11-06_final
2023-11-06 10:26:04	ga_ls8c_ard_3-2-1_101078_2023-11-06_final
2023-11-06 10:26:28	ga_ls8c_ard_3-2-1_101079_2023-11-06_final
2023-11-06 10:26:52	ga_ls8c_ard_3-2-1_101080_2023-11-06_final
2023-11-06 10:27:16	ga_ls8c_ard_3-2-1_101081_2023-11-06_final
2023-11-06 10:27:40	ga_ls8c_ard_3-2-1_101082_2023-11-06_final
2023-11-06 10:28:03	ga_ls8c_ard_3-2-1_101083_2023-11-06_final
2023-11-13 10:28:14	ga_ls8c_ard_3-2-1_102068_2023-11-13_final
2023-11-13 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-11-13_final
2023-11-13 10:29:02	ga_ls8c_ard_3-2-1_102070_2023-11-13_final
2023-11-13 10:29:26	ga_ls8c_ard_3-2-1_102071_2023-11-13_final
2023-11-13 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-11-13_final
2023-11-13 10:30:14	ga_ls8c_ard_3-2-1_102073_2023-11-13_final
2023-11-13 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-11-13_final
2023-11-13 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-11-13_final
2023-11-13 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-11-13_final
2023-11-13 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-11-13_final
2023-11-13 10:32:13	ga_ls8c_ard_3-2-1_102078_2023-11-13_final
2023-11-13 10:32:37	ga_ls8c_ard_3-2-1_102079_2023-11-13_final
2023-11-13 10:33:01	ga_ls8c_ard_3-2-1_102080_2023-11-13_final
2023-11-13 10:33:25	ga_ls8c_ard_3-2-1_102081_2023-11-13_final
2023-11-13 10:33:49	ga_ls8c_ard_3-2-1_102082_2023-11-13_final
2023-11-15 10:18:42	ga_ls8c_ard_3-2-1_100075_2023-11-15_final
2023-11-15 10:19:05	ga_ls8c_ard_3-2-1_100076_2023-11-15_final
2023-11-15 10:19:29	ga_ls8c_ard_3-2-1_100077_2023-11-15_final
2023-11-15 10:19:53	ga_ls8c_ard_3-2-1_100078_2023-11-15_final
2023-11-15 10:20:17	ga_ls8c_ard_3-2-1_100079_2023-11-15_final
2023-11-15 10:20:41	ga_ls8c_ard_3-2-1_100080_2023-11-15_final
2023-11-15 10:21:05	ga_ls8c_ard_3-2-1_100081_2023-11-15_final
2023-11-15 10:21:29	ga_ls8c_ard_3-2-1_100082_2023-11-15_final
2023-11-15 10:21:53	ga_ls8c_ard_3-2-1_100083_2023-11-15_final
2023-11-15 10:22:17	ga_ls8c_ard_3-2-1_100084_2023-11-15_final
2023-11-17 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-17_final
2023-11-17 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-11-17_final
2023-11-17 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-11-17_final
2023-11-18 10:46:26	ga_ls8c_ard_3-2-1_105067_2023-11-18_final
2023-11-18 10:46:50	ga_ls8c_ard_3-2-1_105068_2023-11-18_final
2023-11-20 10:34:29	ga_ls8c_ard_3-2-1_103068_2023-11-20_final
2023-11-20 10:34:53	ga_ls8c_ard_3-2-1_103069_2023-11-20_final
2023-11-20 10:35:17	ga_ls8c_ard_3-2-1_103070_2023-11-20_final
2023-11-20 10:35:41	ga_ls8c_ard_3-2-1_103071_2023-11-20_final
2023-11-20 10:36:05	ga_ls8c_ard_3-2-1_103072_2023-11-20_final
2023-11-20 10:36:29	ga_ls8c_ard_3-2-1_103073_2023-11-20_final
2023-11-20 10:36:53	ga_ls8c_ard_3-2-1_103074_2023-11-20_final
2023-11-20 10:37:17	ga_ls8c_ard_3-2-1_103075_2023-11-20_final
2023-11-20 10:37:41	ga_ls8c_ard_3-2-1_103076_2023-11-20_final
2023-11-20 10:38:04	ga_ls8c_ard_3-2-1_103077_2023-11-20_final
2023-11-22 10:22:56	ga_ls8c_ard_3-2-1_101070_2023-11-22_final
2023-11-22 10:23:20	ga_ls8c_ard_3-2-1_101071_2023-11-22_final
2023-11-22 10:23:44	ga_ls8c_ard_3-2-1_101072_2023-11-22_final
2023-11-22 10:24:08	ga_ls8c_ard_3-2-1_101073_2023-11-22_final
2023-11-22 10:24:32	ga_ls8c_ard_3-2-1_101074_2023-11-22_final
2023-11-22 10:24:56	ga_ls8c_ard_3-2-1_101075_2023-11-22_final
2023-11-22 10:25:20	ga_ls8c_ard_3-2-1_101076_2023-11-22_final
2023-11-22 10:25:44	ga_ls8c_ard_3-2-1_101077_2023-11-22_final
2023-11-22 10:26:07	ga_ls8c_ard_3-2-1_101078_2023-11-22_final
2023-11-22 10:26:31	ga_ls8c_ard_3-2-1_101079_2023-11-22_final
2023-11-22 10:26:55	ga_ls8c_ard_3-2-1_101080_2023-11-22_final
2023-11-22 10:27:19	ga_ls8c_ard_3-2-1_101081_2023-11-22_final
2023-11-22 10:27:43	ga_ls8c_ard_3-2-1_101082_2023-11-22_final

Return to ga_ls8c_ard_3 whole collection 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

All years