Search ga_ls7e_ard_3 across December 2017

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
2017-12-14 09:43:00	ga_ls7e_ard_3-0-0_094073_2017-12-14_final
2017-12-14 09:43:24	ga_ls7e_ard_3-0-0_094074_2017-12-14_final
2017-12-14 09:43:48	ga_ls7e_ard_3-0-0_094075_2017-12-14_final
2017-12-14 09:44:12	ga_ls7e_ard_3-0-0_094076_2017-12-14_final
2017-12-14 09:44:36	ga_ls7e_ard_3-0-0_094077_2017-12-14_final
2017-12-14 09:45:00	ga_ls7e_ard_3-0-0_094078_2017-12-14_final
2017-12-14 09:45:24	ga_ls7e_ard_3-0-0_094079_2017-12-14_final
2017-12-14 09:45:48	ga_ls7e_ard_3-0-0_094080_2017-12-14_final
2017-12-14 09:46:11	ga_ls7e_ard_3-0-0_094081_2017-12-14_final
2017-12-14 09:46:35	ga_ls7e_ard_3-0-0_094082_2017-12-14_final
2017-12-14 09:46:59	ga_ls7e_ard_3-0-0_094083_2017-12-14_final
2017-12-14 09:47:23	ga_ls7e_ard_3-0-0_094084_2017-12-14_final
2017-12-14 09:47:47	ga_ls7e_ard_3-0-0_094085_2017-12-14_final
2017-12-14 09:48:11	ga_ls7e_ard_3-0-0_094086_2017-12-14_final
2017-12-14 11:19:29	ga_ls7e_ard_3-0-0_110067_2017-12-14_final
2017-12-14 11:21:05	ga_ls7e_ard_3-0-0_110071_2017-12-14_final
2017-12-14 11:21:29	ga_ls7e_ard_3-1-0_110072_2017-12-14_final
2017-12-14 11:21:53	ga_ls7e_ard_3-0-0_110073_2017-12-14_final
2017-12-14 11:22:17	ga_ls7e_ard_3-0-0_110074_2017-12-14_final
2017-12-14 11:22:41	ga_ls7e_ard_3-0-0_110075_2017-12-14_final
2017-12-14 11:23:05	ga_ls7e_ard_3-0-0_110076_2017-12-14_final
2017-12-14 11:23:29	ga_ls7e_ard_3-0-0_110077_2017-12-14_final
2017-12-14 11:23:53	ga_ls7e_ard_3-0-0_110078_2017-12-14_final
2017-12-14 11:24:17	ga_ls7e_ard_3-0-0_110079_2017-12-14_final
2017-12-14 11:24:41	ga_ls7e_ard_3-0-0_110080_2017-12-14_final
2017-12-14 11:25:04	ga_ls7e_ard_3-0-0_110081_2017-12-14_final
2017-12-14 11:25:28	ga_ls7e_ard_3-0-0_110082_2017-12-14_final
2017-12-14 11:25:52	ga_ls7e_ard_3-0-0_110083_2017-12-14_final
2017-12-14 11:26:16	ga_ls7e_ard_3-0-0_110084_2017-12-14_final
2017-12-15 10:25:27	ga_ls7e_ard_3-0-0_101071_2017-12-15_final
2017-12-15 10:25:51	ga_ls7e_ard_3-0-0_101072_2017-12-15_final
2017-12-15 10:26:15	ga_ls7e_ard_3-0-0_101073_2017-12-15_final
2017-12-15 10:26:39	ga_ls7e_ard_3-0-0_101074_2017-12-15_final
2017-12-15 10:27:03	ga_ls7e_ard_3-1-0_101075_2017-12-15_final
2017-12-15 10:27:27	ga_ls7e_ard_3-0-0_101076_2017-12-15_final
2017-12-15 10:27:51	ga_ls7e_ard_3-0-0_101077_2017-12-15_final
2017-12-15 10:28:15	ga_ls7e_ard_3-0-0_101078_2017-12-15_final
2017-12-15 10:28:39	ga_ls7e_ard_3-0-0_101079_2017-12-15_final
2017-12-15 10:29:03	ga_ls7e_ard_3-0-0_101080_2017-12-15_final
2017-12-15 10:29:27	ga_ls7e_ard_3-0-0_101081_2017-12-15_final
2017-12-15 10:29:50	ga_ls7e_ard_3-0-0_101082_2017-12-15_final
2017-12-15 10:30:14	ga_ls7e_ard_3-0-0_101083_2017-12-15_final
2017-12-16 09:31:25	ga_ls7e_ard_3-0-0_092075_2017-12-16_final
2017-12-16 09:31:49	ga_ls7e_ard_3-0-0_092076_2017-12-16_final
2017-12-16 09:32:13	ga_ls7e_ard_3-0-0_092077_2017-12-16_final
2017-12-16 09:32:37	ga_ls7e_ard_3-0-0_092078_2017-12-16_final
2017-12-16 09:33:01	ga_ls7e_ard_3-0-0_092079_2017-12-16_final
2017-12-16 09:33:25	ga_ls7e_ard_3-0-0_092080_2017-12-16_final
2017-12-16 09:33:49	ga_ls7e_ard_3-0-0_092081_2017-12-16_final
2017-12-16 09:34:13	ga_ls7e_ard_3-0-0_092082_2017-12-16_final
2017-12-16 09:34:37	ga_ls7e_ard_3-0-0_092083_2017-12-16_final
2017-12-16 09:35:00	ga_ls7e_ard_3-0-0_092084_2017-12-16_final
2017-12-16 09:35:24	ga_ls7e_ard_3-0-0_092085_2017-12-16_final
2017-12-16 09:35:48	ga_ls7e_ard_3-0-0_092086_2017-12-16_final
2017-12-16 09:36:12	ga_ls7e_ard_3-0-0_092087_2017-12-16_final
2017-12-16 11:07:54	ga_ls7e_ard_3-0-0_108069_2017-12-16_final
2017-12-16 11:08:18	ga_ls7e_ard_3-0-0_108070_2017-12-16_final
2017-12-16 11:08:42	ga_ls7e_ard_3-0-0_108071_2017-12-16_final
2017-12-16 11:09:06	ga_ls7e_ard_3-0-0_108072_2017-12-16_final
2017-12-16 11:09:30	ga_ls7e_ard_3-0-0_108073_2017-12-16_final
2017-12-16 11:09:54	ga_ls7e_ard_3-0-0_108074_2017-12-16_final
2017-12-16 11:10:18	ga_ls7e_ard_3-1-0_108075_2017-12-16_final
2017-12-16 11:10:42	ga_ls7e_ard_3-0-0_108076_2017-12-16_final
2017-12-16 11:11:06	ga_ls7e_ard_3-0-0_108077_2017-12-16_final
2017-12-16 11:11:30	ga_ls7e_ard_3-0-0_108078_2017-12-16_final
2017-12-16 11:11:54	ga_ls7e_ard_3-0-0_108079_2017-12-16_final
2017-12-16 11:12:18	ga_ls7e_ard_3-0-0_108080_2017-12-16_final
2017-12-16 11:12:42	ga_ls7e_ard_3-0-0_108081_2017-12-16_final
2017-12-16 11:13:06	ga_ls7e_ard_3-0-0_108082_2017-12-16_final
2017-12-16 11:13:29	ga_ls7e_ard_3-0-0_108083_2017-12-16_final
2017-12-16 11:13:53	ga_ls7e_ard_3-0-0_108084_2017-12-16_final
2017-12-17 10:11:29	ga_ls7e_ard_3-0-0_099067_2017-12-17_final
2017-12-17 10:11:52	ga_ls7e_ard_3-0-0_099068_2017-12-17_final
2017-12-17 10:12:16	ga_ls7e_ard_3-0-0_099069_2017-12-17_final
2017-12-17 10:12:40	ga_ls7e_ard_3-0-0_099070_2017-12-17_final
2017-12-17 10:13:04	ga_ls7e_ard_3-0-0_099071_2017-12-17_final
2017-12-17 10:13:28	ga_ls7e_ard_3-0-0_099072_2017-12-17_final
2017-12-17 10:13:52	ga_ls7e_ard_3-0-0_099073_2017-12-17_final
2017-12-17 10:14:16	ga_ls7e_ard_3-0-0_099074_2017-12-17_final
2017-12-17 10:14:40	ga_ls7e_ard_3-0-0_099075_2017-12-17_final
2017-12-17 10:15:04	ga_ls7e_ard_3-0-0_099076_2017-12-17_final
2017-12-17 10:15:28	ga_ls7e_ard_3-0-0_099077_2017-12-17_final
2017-12-17 10:15:52	ga_ls7e_ard_3-0-0_099078_2017-12-17_final
2017-12-17 10:16:16	ga_ls7e_ard_3-0-0_099079_2017-12-17_final
2017-12-17 10:16:40	ga_ls7e_ard_3-0-0_099080_2017-12-17_final
2017-12-17 10:17:04	ga_ls7e_ard_3-0-0_099081_2017-12-17_final
2017-12-17 10:17:28	ga_ls7e_ard_3-0-0_099082_2017-12-17_final
2017-12-17 10:17:52	ga_ls7e_ard_3-0-0_099083_2017-12-17_final
2017-12-17 11:53:09	ga_ls7e_ard_3-0-0_115074_2017-12-17_final
2017-12-17 11:53:33	ga_ls7e_ard_3-0-0_115075_2017-12-17_final
2017-12-17 11:53:57	ga_ls7e_ard_3-0-0_115076_2017-12-17_final
2017-12-17 11:54:21	ga_ls7e_ard_3-1-0_115077_2017-12-17_final
2017-12-17 11:54:45	ga_ls7e_ard_3-0-0_115078_2017-12-17_final
2017-12-18 09:19:50	ga_ls7e_ard_3-0-0_090077_2017-12-17_final
2017-12-18 09:20:14	ga_ls7e_ard_3-0-0_090078_2017-12-17_final
2017-12-18 09:20:38	ga_ls7e_ard_3-0-0_090079_2017-12-17_final
2017-12-18 09:21:02	ga_ls7e_ard_3-0-0_090080_2017-12-17_final
2017-12-18 09:21:26	ga_ls7e_ard_3-0-0_090081_2017-12-17_final
2017-12-18 09:21:50	ga_ls7e_ard_3-0-0_090082_2017-12-17_final
2017-12-18 09:22:14	ga_ls7e_ard_3-0-0_090083_2017-12-17_final

Return to ga_ls7e_ard_3 across December 2017 overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2017

December

All days