Search ga_ls8c_ard_3 across December 2019

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
2019-12-13 10:21:47	ga_ls8c_ard_3-2-0_101067_2019-12-13_final
2019-12-13 10:22:11	ga_ls8c_ard_3-2-0_101068_2019-12-13_final
2019-12-13 10:22:35	ga_ls8c_ard_3-2-0_101069_2019-12-13_final
2019-12-13 10:22:59	ga_ls8c_ard_3-2-0_101070_2019-12-13_final
2019-12-13 10:23:23	ga_ls8c_ard_3-2-0_101071_2019-12-13_final
2019-12-13 10:26:35	ga_ls8c_ard_3-2-0_101079_2019-12-13_final
2019-12-13 10:26:59	ga_ls8c_ard_3-2-0_101080_2019-12-13_final
2019-12-13 10:28:11	ga_ls8c_ard_3-2-0_101083_2019-12-13_final
2019-12-13 10:28:34	ga_ls8c_ard_3-2-0_101084_2019-12-13_final
2019-12-14 09:26:10	ga_ls8c_ard_3-2-0_092067_2019-12-13_final
2019-12-14 09:26:34	ga_ls8c_ard_3-2-0_092068_2019-12-13_final
2019-12-14 09:27:46	ga_ls8c_ard_3-2-0_092071_2019-12-13_final
2019-12-14 09:28:10	ga_ls8c_ard_3-2-0_092072_2019-12-13_final
2019-12-14 09:28:34	ga_ls8c_ard_3-2-0_092073_2019-12-13_final
2019-12-14 09:28:58	ga_ls8c_ard_3-2-0_092074_2019-12-13_final
2019-12-14 09:30:57	ga_ls8c_ard_3-2-0_092079_2019-12-14_final
2019-12-14 09:33:45	ga_ls8c_ard_3-2-0_092086_2019-12-14_final
2019-12-14 09:34:09	ga_ls8c_ard_3-2-0_092087_2019-12-14_final
2019-12-14 09:34:33	ga_ls8c_ard_3-2-0_092088_2019-12-14_final
2019-12-14 09:34:57	ga_ls8c_ard_3-2-0_092089_2019-12-14_final
2019-12-14 09:35:21	ga_ls8c_ard_3-2-0_092090_2019-12-14_final
2019-12-14 11:05:03	ga_ls8c_ard_3-2-0_108067_2019-12-14_final
2019-12-14 11:06:15	ga_ls8c_ard_3-2-0_108070_2019-12-14_final
2019-12-14 11:06:39	ga_ls8c_ard_3-2-0_108071_2019-12-14_final
2019-12-14 11:07:27	ga_ls8c_ard_3-2-0_108073_2019-12-14_final
2019-12-14 11:07:51	ga_ls8c_ard_3-2-0_108074_2019-12-14_final
2019-12-14 11:08:14	ga_ls8c_ard_3-2-0_108075_2019-12-14_final
2019-12-14 11:08:38	ga_ls8c_ard_3-2-0_108076_2019-12-14_final
2019-12-14 11:09:02	ga_ls8c_ard_3-2-0_108077_2019-12-14_final
2019-12-14 11:09:26	ga_ls8c_ard_3-2-0_108078_2019-12-14_final
2019-12-14 11:09:50	ga_ls8c_ard_3-2-0_108079_2019-12-14_final
2019-12-14 11:10:14	ga_ls8c_ard_3-2-0_108080_2019-12-14_final
2019-12-14 11:10:38	ga_ls8c_ard_3-2-0_108081_2019-12-14_final
2019-12-14 11:11:26	ga_ls8c_ard_3-2-0_108083_2019-12-14_final
2019-12-14 11:11:50	ga_ls8c_ard_3-2-0_108084_2019-12-14_final
2019-12-14 11:12:14	ga_ls8c_ard_3-2-0_108085_2019-12-14_final
2019-12-15 10:09:02	ga_ls8c_ard_3-2-1_099066_2019-12-15_final
2019-12-15 10:09:26	ga_ls8c_ard_3-2-0_099067_2019-12-15_final
2019-12-15 10:09:49	ga_ls8c_ard_3-2-0_099068_2019-12-15_final
2019-12-15 10:10:13	ga_ls8c_ard_3-2-0_099069_2019-12-15_final
2019-12-15 10:10:37	ga_ls8c_ard_3-2-0_099070_2019-12-15_final
2019-12-15 10:11:01	ga_ls8c_ard_3-2-0_099071_2019-12-15_final
2019-12-15 10:11:25	ga_ls8c_ard_3-2-0_099072_2019-12-15_final
2019-12-15 10:11:49	ga_ls8c_ard_3-2-0_099073_2019-12-15_final
2019-12-15 10:12:13	ga_ls8c_ard_3-2-0_099074_2019-12-15_final
2019-12-15 10:12:37	ga_ls8c_ard_3-2-0_099075_2019-12-15_final
2019-12-15 10:13:01	ga_ls8c_ard_3-2-0_099076_2019-12-15_final
2019-12-15 10:13:25	ga_ls8c_ard_3-2-0_099077_2019-12-15_final
2019-12-15 10:13:49	ga_ls8c_ard_3-2-0_099078_2019-12-15_final
2019-12-15 10:14:13	ga_ls8c_ard_3-2-0_099079_2019-12-15_final
2019-12-15 10:14:37	ga_ls8c_ard_3-2-0_099080_2019-12-15_final
2019-12-15 10:15:01	ga_ls8c_ard_3-2-0_099081_2019-12-15_final
2019-12-15 10:15:25	ga_ls8c_ard_3-2-0_099082_2019-12-15_final
2019-12-15 10:15:49	ga_ls8c_ard_3-2-0_099083_2019-12-15_final
2019-12-15 10:16:13	ga_ls8c_ard_3-2-0_099084_2019-12-15_final
2019-12-15 10:16:36	ga_ls8c_ard_3-2-0_099085_2019-12-15_final
2019-12-15 11:50:42	ga_ls8c_ard_3-2-0_115073_2019-12-15_final
2019-12-15 11:51:06	ga_ls8c_ard_3-2-0_115074_2019-12-15_final
2019-12-15 11:51:30	ga_ls8c_ard_3-2-0_115075_2019-12-15_final
2019-12-15 11:51:54	ga_ls8c_ard_3-2-0_115076_2019-12-15_final
2019-12-15 11:52:18	ga_ls8c_ard_3-2-0_115077_2019-12-15_final
2019-12-15 11:52:42	ga_ls8c_ard_3-2-0_115078_2019-12-15_final
2019-12-15 11:53:06	ga_ls8c_ard_3-2-0_115079_2019-12-15_final
2019-12-15 11:53:30	ga_ls8c_ard_3-2-0_115080_2019-12-15_final
2019-12-16 09:16:36	ga_ls8c_ard_3-2-0_090074_2019-12-15_final
2019-12-16 09:17:00	ga_ls8c_ard_3-2-0_090075_2019-12-15_final
2019-12-16 09:17:23	ga_ls8c_ard_3-2-0_090076_2019-12-15_final
2019-12-16 09:17:47	ga_ls8c_ard_3-2-0_090077_2019-12-15_final
2019-12-16 09:18:11	ga_ls8c_ard_3-2-0_090078_2019-12-15_final
2019-12-16 09:18:35	ga_ls8c_ard_3-2-0_090079_2019-12-15_final
2019-12-16 09:18:59	ga_ls8c_ard_3-2-0_090080_2019-12-15_final
2019-12-16 09:19:23	ga_ls8c_ard_3-2-0_090081_2019-12-15_final
2019-12-16 09:19:47	ga_ls8c_ard_3-2-0_090082_2019-12-15_final
2019-12-16 09:20:11	ga_ls8c_ard_3-2-0_090083_2019-12-15_final
2019-12-16 09:20:35	ga_ls8c_ard_3-2-0_090084_2019-12-15_final
2019-12-16 09:20:59	ga_ls8c_ard_3-2-0_090085_2019-12-15_final
2019-12-16 09:21:23	ga_ls8c_ard_3-2-0_090086_2019-12-15_final
2019-12-16 09:21:47	ga_ls8c_ard_3-2-0_090087_2019-12-15_final
2019-12-16 09:22:11	ga_ls8c_ard_3-2-0_090088_2019-12-15_final
2019-12-16 09:22:35	ga_ls8c_ard_3-2-0_090089_2019-12-15_final
2019-12-16 09:22:59	ga_ls8c_ard_3-2-0_090090_2019-12-15_final
2019-12-16 09:23:23	ga_ls8c_ard_3-2-0_090091_2019-12-15_final
2019-12-16 10:52:41	ga_ls8c_ard_3-2-0_106067_2019-12-16_final
2019-12-16 10:53:05	ga_ls8c_ard_3-2-0_106068_2019-12-16_final
2019-12-16 10:53:29	ga_ls8c_ard_3-2-0_106069_2019-12-16_final
2019-12-16 10:53:53	ga_ls8c_ard_3-2-0_106070_2019-12-16_final
2019-12-16 10:54:17	ga_ls8c_ard_3-2-0_106071_2019-12-16_final
2019-12-16 10:54:41	ga_ls8c_ard_3-2-0_106072_2019-12-16_final
2019-12-16 10:55:05	ga_ls8c_ard_3-2-0_106073_2019-12-16_final
2019-12-16 10:55:29	ga_ls8c_ard_3-2-0_106074_2019-12-16_final
2019-12-16 10:55:52	ga_ls8c_ard_3-2-0_106075_2019-12-16_final
2019-12-16 10:56:16	ga_ls8c_ard_3-2-0_106076_2019-12-16_final
2019-12-16 10:56:40	ga_ls8c_ard_3-2-0_106077_2019-12-16_final
2019-12-16 10:57:04	ga_ls8c_ard_3-2-0_106078_2019-12-16_final
2019-12-16 10:57:28	ga_ls8c_ard_3-2-0_106079_2019-12-16_final
2019-12-16 10:57:52	ga_ls8c_ard_3-2-0_106080_2019-12-16_final
2019-12-16 10:58:16	ga_ls8c_ard_3-2-0_106081_2019-12-16_final
2019-12-16 10:58:40	ga_ls8c_ard_3-2-0_106082_2019-12-16_final
2019-12-16 10:59:04	ga_ls8c_ard_3-2-0_106083_2019-12-16_final
2019-12-16 10:59:28	ga_ls8c_ard_3-2-0_106084_2019-12-16_final

Return to ga_ls8c_ard_3 across December 2019 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

2019

December

All days