Search ga_ls8c_ard_3 across February 2020

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
2020-02-04 09:06:00	ga_ls8c_ard_3-1-0_088079_2020-02-03_final
2020-02-04 09:06:24	ga_ls8c_ard_3-1-0_088080_2020-02-03_final
2020-02-04 09:06:48	ga_ls8c_ard_3-1-0_088081_2020-02-03_final
2020-02-04 09:07:12	ga_ls8c_ard_3-1-0_088082_2020-02-03_final
2020-02-04 09:07:36	ga_ls8c_ard_3-1-0_088083_2020-02-03_final
2020-02-04 09:08:00	ga_ls8c_ard_3-1-0_088084_2020-02-03_final
2020-02-04 10:40:06	ga_ls8c_ard_3-1-0_104067_2020-02-04_final
2020-02-04 10:40:30	ga_ls8c_ard_3-1-0_104068_2020-02-04_final
2020-02-04 10:40:54	ga_ls8c_ard_3-1-0_104069_2020-02-04_final
2020-02-04 10:41:18	ga_ls8c_ard_3-1-0_104070_2020-02-04_final
2020-02-04 10:41:41	ga_ls8c_ard_3-1-0_104071_2020-02-04_final
2020-02-04 10:42:05	ga_ls8c_ard_3-1-0_104072_2020-02-04_final
2020-02-04 10:42:29	ga_ls8c_ard_3-1-0_104073_2020-02-04_final
2020-02-04 10:42:53	ga_ls8c_ard_3-1-0_104074_2020-02-04_final
2020-02-04 10:43:17	ga_ls8c_ard_3-1-0_104075_2020-02-04_final
2020-02-04 10:43:41	ga_ls8c_ard_3-1-0_104076_2020-02-04_final
2020-02-04 10:44:05	ga_ls8c_ard_3-1-0_104077_2020-02-04_final
2020-02-04 10:44:29	ga_ls8c_ard_3-1-0_104078_2020-02-04_final
2020-02-04 10:44:53	ga_ls8c_ard_3-1-0_104079_2020-02-04_final
2020-02-04 10:45:17	ga_ls8c_ard_3-1-0_104080_2020-02-04_final
2020-02-04 10:45:41	ga_ls8c_ard_3-1-0_104081_2020-02-04_final
2020-02-04 10:46:05	ga_ls8c_ard_3-1-0_104082_2020-02-04_final
2020-02-04 10:46:29	ga_ls8c_ard_3-1-0_104083_2020-02-04_final
2020-02-04 14:09:50	ga_ls8c_ard_3-2-1_136097_2020-02-04_final
2020-02-05 08:10:46	ga_ls8c_ard_3-2-1_079080_2020-02-04_final
2020-02-05 08:17:58	ga_ls8c_ard_3-2-1_079098_2020-02-04_final
2020-02-05 09:44:28	ga_ls8c_ard_3-1-0_095067_2020-02-05_final
2020-02-05 09:45:40	ga_ls8c_ard_3-1-0_095070_2020-02-05_final
2020-02-05 09:46:04	ga_ls8c_ard_3-1-0_095071_2020-02-05_final
2020-02-05 09:46:28	ga_ls8c_ard_3-1-0_095072_2020-02-05_final
2020-02-05 09:46:52	ga_ls8c_ard_3-1-0_095073_2020-02-05_final
2020-02-05 09:47:16	ga_ls8c_ard_3-1-0_095074_2020-02-05_final
2020-02-05 09:47:40	ga_ls8c_ard_3-1-0_095075_2020-02-05_final
2020-02-05 09:48:04	ga_ls8c_ard_3-1-0_095076_2020-02-05_final
2020-02-05 09:48:27	ga_ls8c_ard_3-1-0_095077_2020-02-05_final
2020-02-05 09:48:51	ga_ls8c_ard_3-1-0_095078_2020-02-05_final
2020-02-05 09:49:15	ga_ls8c_ard_3-1-0_095079_2020-02-05_final
2020-02-05 09:49:39	ga_ls8c_ard_3-1-0_095080_2020-02-05_final
2020-02-05 09:50:03	ga_ls8c_ard_3-1-0_095081_2020-02-05_final
2020-02-05 09:50:27	ga_ls8c_ard_3-1-0_095082_2020-02-05_final
2020-02-05 09:50:51	ga_ls8c_ard_3-1-0_095083_2020-02-05_final
2020-02-05 09:51:15	ga_ls8c_ard_3-1-0_095084_2020-02-05_final
2020-02-05 09:51:39	ga_ls8c_ard_3-1-0_095085_2020-02-05_final
2020-02-05 09:52:03	ga_ls8c_ard_3-1-0_095086_2020-02-05_final
2020-02-05 09:52:27	ga_ls8c_ard_3-1-0_095087_2020-02-05_final
2020-02-05 09:52:51	ga_ls8c_ard_3-1-0_095088_2020-02-05_final
2020-02-05 11:23:21	ga_ls8c_ard_3-1-0_111067_2020-02-05_final
2020-02-05 11:23:45	ga_ls8c_ard_3-1-0_111068_2020-02-05_final
2020-02-05 11:24:09	ga_ls8c_ard_3-1-0_111069_2020-02-05_final
2020-02-05 11:24:33	ga_ls8c_ard_3-1-0_111070_2020-02-05_final
2020-02-05 11:24:57	ga_ls8c_ard_3-1-0_111071_2020-02-05_final
2020-02-05 11:25:21	ga_ls8c_ard_3-1-0_111072_2020-02-05_final
2020-02-05 11:25:45	ga_ls8c_ard_3-1-0_111073_2020-02-05_final
2020-02-05 11:26:09	ga_ls8c_ard_3-1-0_111074_2020-02-05_final
2020-02-05 11:26:33	ga_ls8c_ard_3-1-0_111075_2020-02-05_final
2020-02-05 11:26:57	ga_ls8c_ard_3-1-0_111076_2020-02-05_final
2020-02-05 11:27:21	ga_ls8c_ard_3-1-0_111077_2020-02-05_final
2020-02-05 11:27:44	ga_ls8c_ard_3-1-0_111078_2020-02-05_final
2020-02-05 11:28:08	ga_ls8c_ard_3-1-0_111079_2020-02-05_final
2020-02-05 11:28:32	ga_ls8c_ard_3-1-0_111080_2020-02-05_final
2020-02-05 11:28:56	ga_ls8c_ard_3-1-0_111081_2020-02-05_final
2020-02-05 11:29:20	ga_ls8c_ard_3-1-0_111082_2020-02-05_final
2020-02-05 11:29:44	ga_ls8c_ard_3-1-0_111083_2020-02-05_final
2020-02-05 11:30:08	ga_ls8c_ard_3-1-0_111084_2020-02-05_final
2020-02-05 11:30:32	ga_ls8c_ard_3-1-0_111085_2020-02-05_final
2020-02-17 10:09:09	ga_ls8c_ard_3-1-0_099067_2020-02-17_final
2020-02-17 10:09:33	ga_ls8c_ard_3-1-0_099068_2020-02-17_final
2020-02-17 10:09:57	ga_ls8c_ard_3-1-0_099069_2020-02-17_final
2020-02-17 10:10:21	ga_ls8c_ard_3-1-0_099070_2020-02-17_final
2020-02-17 10:10:45	ga_ls8c_ard_3-1-0_099071_2020-02-17_final
2020-02-17 10:11:09	ga_ls8c_ard_3-1-0_099072_2020-02-17_final
2020-02-17 10:11:33	ga_ls8c_ard_3-1-0_099073_2020-02-17_final
2020-02-17 10:11:57	ga_ls8c_ard_3-1-0_099074_2020-02-17_final
2020-02-17 10:12:21	ga_ls8c_ard_3-1-0_099075_2020-02-17_final
2020-02-17 10:12:45	ga_ls8c_ard_3-1-0_099076_2020-02-17_final
2020-02-17 10:13:09	ga_ls8c_ard_3-1-0_099077_2020-02-17_final
2020-02-17 10:13:33	ga_ls8c_ard_3-1-0_099078_2020-02-17_final
2020-02-17 10:13:57	ga_ls8c_ard_3-1-0_099079_2020-02-17_final
2020-02-17 10:14:20	ga_ls8c_ard_3-1-0_099080_2020-02-17_final
2020-02-17 10:14:44	ga_ls8c_ard_3-1-0_099081_2020-02-17_final
2020-02-17 10:15:08	ga_ls8c_ard_3-1-0_099082_2020-02-17_final
2020-02-17 10:15:32	ga_ls8c_ard_3-1-0_099083_2020-02-17_final
2020-02-17 10:15:56	ga_ls8c_ard_3-1-0_099084_2020-02-17_final
2020-02-18 09:16:19	ga_ls8c_ard_3-1-0_090074_2020-02-17_final
2020-02-18 09:16:43	ga_ls8c_ard_3-1-0_090075_2020-02-17_final
2020-02-18 09:17:07	ga_ls8c_ard_3-1-0_090076_2020-02-17_final
2020-02-18 09:17:31	ga_ls8c_ard_3-1-0_090077_2020-02-17_final
2020-02-18 09:17:55	ga_ls8c_ard_3-1-0_090078_2020-02-17_final
2020-02-18 09:18:19	ga_ls8c_ard_3-1-0_090079_2020-02-17_final
2020-02-18 09:18:43	ga_ls8c_ard_3-1-0_090080_2020-02-17_final
2020-02-18 09:19:07	ga_ls8c_ard_3-1-0_090081_2020-02-17_final
2020-02-18 09:19:31	ga_ls8c_ard_3-1-0_090082_2020-02-17_final
2020-02-18 09:19:55	ga_ls8c_ard_3-1-0_090083_2020-02-17_final
2020-02-18 09:20:19	ga_ls8c_ard_3-1-0_090084_2020-02-17_final
2020-02-18 09:20:43	ga_ls8c_ard_3-1-0_090085_2020-02-17_final
2020-02-18 09:21:07	ga_ls8c_ard_3-1-0_090086_2020-02-17_final
2020-02-18 09:21:31	ga_ls8c_ard_3-1-0_090087_2020-02-17_final
2020-02-18 09:21:55	ga_ls8c_ard_3-1-0_090088_2020-02-17_final
2020-02-18 09:22:19	ga_ls8c_ard_3-1-0_090089_2020-02-17_final
2020-02-18 09:22:42	ga_ls8c_ard_3-1-0_090090_2020-02-17_final

Return to ga_ls8c_ard_3 across February 2020 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

2020

February

All days