Search ga_ls8c_ard_3 across December 2018

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
2018-12-15 09:05:48	ga_ls8c_ard_3-0-0_088079_2018-12-14_final
2018-12-15 09:06:12	ga_ls8c_ard_3-0-0_088080_2018-12-14_final
2018-12-15 09:06:36	ga_ls8c_ard_3-1-0_088081_2018-12-14_final
2018-12-15 09:07:00	ga_ls8c_ard_3-0-0_088082_2018-12-14_final
2018-12-15 09:07:24	ga_ls8c_ard_3-0-0_088083_2018-12-14_final
2018-12-15 09:07:48	ga_ls8c_ard_3-0-0_088084_2018-12-14_final
2018-12-15 10:39:54	ga_ls8c_ard_3-0-0_104067_2018-12-15_final
2018-12-15 10:40:18	ga_ls8c_ard_3-0-0_104068_2018-12-15_final
2018-12-15 10:40:42	ga_ls8c_ard_3-0-0_104069_2018-12-15_final
2018-12-15 10:41:06	ga_ls8c_ard_3-0-0_104070_2018-12-15_final
2018-12-15 10:41:30	ga_ls8c_ard_3-0-0_104071_2018-12-15_final
2018-12-15 10:41:54	ga_ls8c_ard_3-0-0_104072_2018-12-15_final
2018-12-15 10:42:17	ga_ls8c_ard_3-0-0_104073_2018-12-15_final
2018-12-15 10:42:41	ga_ls8c_ard_3-0-0_104074_2018-12-15_final
2018-12-15 10:43:05	ga_ls8c_ard_3-0-0_104075_2018-12-15_final
2018-12-15 10:43:29	ga_ls8c_ard_3-0-0_104076_2018-12-15_final
2018-12-15 10:43:53	ga_ls8c_ard_3-1-0_104077_2018-12-15_final
2018-12-15 10:44:17	ga_ls8c_ard_3-0-0_104078_2018-12-15_final
2018-12-15 10:44:41	ga_ls8c_ard_3-0-0_104079_2018-12-15_final
2018-12-15 10:45:05	ga_ls8c_ard_3-0-0_104080_2018-12-15_final
2018-12-15 10:45:29	ga_ls8c_ard_3-0-0_104081_2018-12-15_final
2018-12-15 10:45:53	ga_ls8c_ard_3-0-0_104082_2018-12-15_final
2018-12-15 10:46:17	ga_ls8c_ard_3-0-0_104083_2018-12-15_final
2018-12-15 14:09:39	ga_ls8c_ard_3-2-1_136097_2018-12-15_final
2018-12-16 08:10:35	ga_ls8c_ard_3-2-1_079080_2018-12-15_final
2018-12-16 08:17:46	ga_ls8c_ard_3-2-1_079098_2018-12-15_final
2018-12-16 09:44:17	ga_ls8c_ard_3-0-0_095067_2018-12-16_final
2018-12-16 09:45:28	ga_ls8c_ard_3-0-0_095070_2018-12-16_final
2018-12-16 09:45:52	ga_ls8c_ard_3-0-0_095071_2018-12-16_final
2018-12-16 09:46:16	ga_ls8c_ard_3-0-0_095072_2018-12-16_final
2018-12-16 09:46:40	ga_ls8c_ard_3-0-0_095073_2018-12-16_final
2018-12-16 09:47:04	ga_ls8c_ard_3-0-0_095074_2018-12-16_final
2018-12-16 09:47:28	ga_ls8c_ard_3-0-0_095075_2018-12-16_final
2018-12-16 09:47:52	ga_ls8c_ard_3-0-0_095076_2018-12-16_final
2018-12-16 09:48:16	ga_ls8c_ard_3-0-0_095077_2018-12-16_final
2018-12-16 09:48:40	ga_ls8c_ard_3-0-0_095078_2018-12-16_final
2018-12-16 09:49:04	ga_ls8c_ard_3-0-0_095079_2018-12-16_final
2018-12-16 09:49:28	ga_ls8c_ard_3-0-0_095080_2018-12-16_final
2018-12-16 09:49:52	ga_ls8c_ard_3-0-0_095081_2018-12-16_final
2018-12-16 09:50:16	ga_ls8c_ard_3-0-0_095082_2018-12-16_final
2018-12-16 09:50:40	ga_ls8c_ard_3-0-0_095083_2018-12-16_final
2018-12-16 09:51:04	ga_ls8c_ard_3-0-0_095084_2018-12-16_final
2018-12-16 09:51:28	ga_ls8c_ard_3-0-0_095085_2018-12-16_final
2018-12-16 09:51:52	ga_ls8c_ard_3-0-0_095086_2018-12-16_final
2018-12-16 09:52:16	ga_ls8c_ard_3-0-0_095087_2018-12-16_final
2018-12-16 09:52:39	ga_ls8c_ard_3-0-0_095088_2018-12-16_final
2018-12-16 11:23:10	ga_ls8c_ard_3-0-0_111067_2018-12-16_final
2018-12-16 11:23:34	ga_ls8c_ard_3-0-0_111068_2018-12-16_final
2018-12-16 11:23:58	ga_ls8c_ard_3-0-0_111069_2018-12-16_final
2018-12-16 11:24:22	ga_ls8c_ard_3-0-0_111070_2018-12-16_final
2018-12-16 11:24:45	ga_ls8c_ard_3-0-0_111071_2018-12-16_final
2018-12-16 11:25:09	ga_ls8c_ard_3-0-0_111072_2018-12-16_final
2018-12-16 11:25:33	ga_ls8c_ard_3-0-0_111073_2018-12-16_final
2018-12-16 11:25:57	ga_ls8c_ard_3-0-0_111074_2018-12-16_final
2018-12-16 11:26:21	ga_ls8c_ard_3-0-0_111075_2018-12-16_final
2018-12-16 11:26:45	ga_ls8c_ard_3-0-0_111076_2018-12-16_final
2018-12-16 11:27:09	ga_ls8c_ard_3-0-0_111077_2018-12-16_final
2018-12-16 11:27:33	ga_ls8c_ard_3-0-0_111078_2018-12-16_final
2018-12-16 11:27:57	ga_ls8c_ard_3-0-0_111079_2018-12-16_final
2018-12-16 11:28:21	ga_ls8c_ard_3-0-0_111080_2018-12-16_final
2018-12-16 11:28:45	ga_ls8c_ard_3-0-0_111081_2018-12-16_final
2018-12-16 11:29:09	ga_ls8c_ard_3-0-0_111082_2018-12-16_final
2018-12-16 11:29:33	ga_ls8c_ard_3-0-0_111083_2018-12-16_final
2018-12-16 11:29:57	ga_ls8c_ard_3-0-0_111084_2018-12-16_final
2018-12-16 11:30:21	ga_ls8c_ard_3-0-0_111085_2018-12-16_final
2018-12-28 10:09:00	ga_ls8c_ard_3-0-0_099067_2018-12-28_final
2018-12-28 10:09:24	ga_ls8c_ard_3-0-0_099068_2018-12-28_final
2018-12-28 10:09:48	ga_ls8c_ard_3-0-0_099069_2018-12-28_final
2018-12-28 10:10:12	ga_ls8c_ard_3-0-0_099070_2018-12-28_final
2018-12-28 10:10:36	ga_ls8c_ard_3-0-0_099071_2018-12-28_final
2018-12-28 10:11:00	ga_ls8c_ard_3-0-0_099072_2018-12-28_final
2018-12-28 10:11:24	ga_ls8c_ard_3-0-0_099073_2018-12-28_final
2018-12-28 10:11:48	ga_ls8c_ard_3-0-0_099074_2018-12-28_final
2018-12-28 10:12:12	ga_ls8c_ard_3-0-0_099075_2018-12-28_final
2018-12-28 10:12:36	ga_ls8c_ard_3-0-0_099076_2018-12-28_final
2018-12-28 10:13:00	ga_ls8c_ard_3-0-0_099077_2018-12-28_final
2018-12-28 10:13:24	ga_ls8c_ard_3-0-0_099078_2018-12-28_final
2018-12-28 10:13:48	ga_ls8c_ard_3-0-0_099079_2018-12-28_final
2018-12-28 10:14:12	ga_ls8c_ard_3-0-0_099080_2018-12-28_final
2018-12-28 10:14:35	ga_ls8c_ard_3-0-0_099081_2018-12-28_final
2018-12-28 10:14:59	ga_ls8c_ard_3-0-0_099082_2018-12-28_final
2018-12-28 10:15:23	ga_ls8c_ard_3-0-0_099083_2018-12-28_final
2018-12-28 10:15:47	ga_ls8c_ard_3-0-0_099084_2018-12-28_final
2018-12-29 09:16:11	ga_ls8c_ard_3-0-0_090074_2018-12-28_final
2018-12-29 09:16:34	ga_ls8c_ard_3-0-0_090075_2018-12-28_final
2018-12-29 09:16:58	ga_ls8c_ard_3-0-0_090076_2018-12-28_final
2018-12-29 09:17:22	ga_ls8c_ard_3-0-0_090077_2018-12-28_final
2018-12-29 09:17:46	ga_ls8c_ard_3-0-0_090078_2018-12-28_final
2018-12-29 09:18:10	ga_ls8c_ard_3-0-0_090079_2018-12-28_final
2018-12-29 09:18:34	ga_ls8c_ard_3-0-0_090080_2018-12-28_final
2018-12-29 09:18:58	ga_ls8c_ard_3-0-0_090081_2018-12-28_final
2018-12-29 09:19:22	ga_ls8c_ard_3-0-0_090082_2018-12-28_final
2018-12-29 09:19:46	ga_ls8c_ard_3-0-0_090083_2018-12-28_final
2018-12-29 09:20:10	ga_ls8c_ard_3-0-0_090084_2018-12-28_final
2018-12-29 09:20:34	ga_ls8c_ard_3-0-0_090085_2018-12-28_final
2018-12-29 09:20:58	ga_ls8c_ard_3-0-0_090086_2018-12-28_final
2018-12-29 09:21:22	ga_ls8c_ard_3-0-0_090087_2018-12-28_final
2018-12-29 09:21:46	ga_ls8c_ard_3-0-0_090088_2018-12-28_final
2018-12-29 09:22:10	ga_ls8c_ard_3-0-0_090089_2018-12-28_final
2018-12-29 09:22:34	ga_ls8c_ard_3-0-0_090090_2018-12-28_final

Return to ga_ls8c_ard_3 across December 2018 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

2018

December

All days