Search ga_ls7e_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
2019-12-01 08:53:48	ga_ls7e_ard_3-1-0_089077_2019-11-30_final
2019-12-01 08:54:12	ga_ls7e_ard_3-1-0_089078_2019-11-30_final
2019-12-01 08:54:35	ga_ls7e_ard_3-1-0_089079_2019-11-30_final
2019-12-01 08:54:59	ga_ls7e_ard_3-1-0_089080_2019-11-30_final
2019-12-01 08:56:35	ga_ls7e_ard_3-1-0_089084_2019-11-30_final
2019-12-01 08:56:59	ga_ls7e_ard_3-1-0_089085_2019-11-30_final
2019-12-01 08:57:23	ga_ls7e_ard_3-1-0_089086_2019-11-30_final
2019-12-01 10:29:05	ga_ls7e_ard_3-1-0_105068_2019-12-01_final
2019-12-01 10:29:29	ga_ls7e_ard_3-1-0_105069_2019-12-01_final
2019-12-01 10:29:53	ga_ls7e_ard_3-1-0_105070_2019-12-01_final
2019-12-01 10:31:05	ga_ls7e_ard_3-1-0_105073_2019-12-01_final
2019-12-01 10:31:29	ga_ls7e_ard_3-1-0_105074_2019-12-01_final
2019-12-01 10:31:52	ga_ls7e_ard_3-1-0_105075_2019-12-01_final
2019-12-01 10:32:16	ga_ls7e_ard_3-1-0_105076_2019-12-01_final
2019-12-01 10:32:40	ga_ls7e_ard_3-1-0_105077_2019-12-01_final
2019-12-01 10:33:04	ga_ls7e_ard_3-1-0_105078_2019-12-01_final
2019-12-01 10:33:28	ga_ls7e_ard_3-1-0_105079_2019-12-01_final
2019-12-01 10:33:52	ga_ls7e_ard_3-1-0_105080_2019-12-01_final
2019-12-01 10:34:16	ga_ls7e_ard_3-1-0_105081_2019-12-01_final
2019-12-02 09:33:01	ga_ls7e_ard_3-1-0_096067_2019-12-02_final
2019-12-02 09:34:13	ga_ls7e_ard_3-1-0_096070_2019-12-02_final
2019-12-02 09:34:37	ga_ls7e_ard_3-1-0_096071_2019-12-02_final
2019-12-02 09:35:01	ga_ls7e_ard_3-1-0_096072_2019-12-02_final
2019-12-02 09:35:24	ga_ls7e_ard_3-1-0_096073_2019-12-02_final
2019-12-02 09:35:48	ga_ls7e_ard_3-1-0_096074_2019-12-02_final
2019-12-02 09:36:12	ga_ls7e_ard_3-1-0_096075_2019-12-02_final
2019-12-02 09:36:36	ga_ls7e_ard_3-1-0_096076_2019-12-02_final
2019-12-02 09:37:00	ga_ls7e_ard_3-1-0_096077_2019-12-02_final
2019-12-02 09:37:24	ga_ls7e_ard_3-1-0_096078_2019-12-02_final
2019-12-02 09:37:48	ga_ls7e_ard_3-1-0_096079_2019-12-02_final
2019-12-02 09:38:12	ga_ls7e_ard_3-1-0_096080_2019-12-02_final
2019-12-19 10:15:49	ga_ls7e_ard_3-1-0_103068_2019-12-19_final
2019-12-19 10:16:13	ga_ls7e_ard_3-1-0_103069_2019-12-19_final
2019-12-19 10:16:37	ga_ls7e_ard_3-1-0_103070_2019-12-19_final
2019-12-19 10:17:01	ga_ls7e_ard_3-1-0_103071_2019-12-19_final
2019-12-19 10:17:25	ga_ls7e_ard_3-1-0_103072_2019-12-19_final
2019-12-19 10:17:49	ga_ls7e_ard_3-1-0_103073_2019-12-19_final
2019-12-19 10:18:13	ga_ls7e_ard_3-1-0_103074_2019-12-19_final
2019-12-19 10:18:37	ga_ls7e_ard_3-1-0_103075_2019-12-19_final
2019-12-19 10:19:01	ga_ls7e_ard_3-1-0_103076_2019-12-19_final
2019-12-19 10:19:25	ga_ls7e_ard_3-1-0_103077_2019-12-19_final
2019-12-19 10:19:49	ga_ls7e_ard_3-1-0_103078_2019-12-19_final
2019-12-19 10:20:13	ga_ls7e_ard_3-1-0_103079_2019-12-19_final
2019-12-19 10:20:37	ga_ls7e_ard_3-1-0_103080_2019-12-19_final
2019-12-19 10:21:01	ga_ls7e_ard_3-1-0_103081_2019-12-19_final
2019-12-19 10:21:25	ga_ls7e_ard_3-1-0_103082_2019-12-19_final
2019-12-20 09:19:45	ga_ls7e_ard_3-1-0_094067_2019-12-19_final
2019-12-20 09:22:09	ga_ls7e_ard_3-1-0_094073_2019-12-19_final
2019-12-20 09:22:33	ga_ls7e_ard_3-1-0_094074_2019-12-19_final
2019-12-20 09:22:57	ga_ls7e_ard_3-1-0_094075_2019-12-19_final
2019-12-20 09:23:21	ga_ls7e_ard_3-1-0_094076_2019-12-19_final
2019-12-20 09:23:44	ga_ls7e_ard_3-1-0_094077_2019-12-19_final
2019-12-20 09:24:08	ga_ls7e_ard_3-1-0_094078_2019-12-19_final
2019-12-20 09:24:32	ga_ls7e_ard_3-1-0_094079_2019-12-19_final
2019-12-20 09:24:56	ga_ls7e_ard_3-1-0_094080_2019-12-19_final
2019-12-20 09:25:20	ga_ls7e_ard_3-1-0_094081_2019-12-19_final
2019-12-20 09:25:44	ga_ls7e_ard_3-1-0_094082_2019-12-19_final
2019-12-20 09:26:08	ga_ls7e_ard_3-1-0_094083_2019-12-19_final
2019-12-20 09:26:32	ga_ls7e_ard_3-1-0_094084_2019-12-19_final
2019-12-20 09:26:56	ga_ls7e_ard_3-1-0_094085_2019-12-19_final
2019-12-20 09:27:20	ga_ls7e_ard_3-1-0_094086_2019-12-19_final
2019-12-20 09:27:44	ga_ls7e_ard_3-1-0_094087_2019-12-19_final
2019-12-21 10:04:33	ga_ls7e_ard_3-1-0_101071_2019-12-21_final
2019-12-21 10:04:57	ga_ls7e_ard_3-1-0_101072_2019-12-21_final
2019-12-21 10:05:21	ga_ls7e_ard_3-1-0_101073_2019-12-21_final
2019-12-21 10:05:45	ga_ls7e_ard_3-1-0_101074_2019-12-21_final
2019-12-21 10:06:09	ga_ls7e_ard_3-1-0_101075_2019-12-21_final
2019-12-21 10:06:33	ga_ls7e_ard_3-1-0_101076_2019-12-21_final
2019-12-21 10:06:57	ga_ls7e_ard_3-1-0_101077_2019-12-21_final
2019-12-21 10:07:21	ga_ls7e_ard_3-1-0_101078_2019-12-21_final
2019-12-21 10:07:45	ga_ls7e_ard_3-1-0_101079_2019-12-21_final
2019-12-21 10:08:09	ga_ls7e_ard_3-1-0_101080_2019-12-21_final
2019-12-21 10:08:33	ga_ls7e_ard_3-1-0_101081_2019-12-21_final
2019-12-21 10:08:57	ga_ls7e_ard_3-1-0_101082_2019-12-21_final
2019-12-21 10:09:21	ga_ls7e_ard_3-1-0_101083_2019-12-21_final
2019-12-22 09:10:29	ga_ls7e_ard_3-1-0_092075_2019-12-21_final
2019-12-22 09:10:53	ga_ls7e_ard_3-1-0_092076_2019-12-21_final
2019-12-22 09:11:17	ga_ls7e_ard_3-1-0_092077_2019-12-21_final
2019-12-22 09:11:41	ga_ls7e_ard_3-1-0_092078_2019-12-21_final
2019-12-22 09:12:05	ga_ls7e_ard_3-1-0_092079_2019-12-21_final
2019-12-22 09:12:29	ga_ls7e_ard_3-1-0_092080_2019-12-21_final
2019-12-22 09:12:53	ga_ls7e_ard_3-1-0_092081_2019-12-21_final
2019-12-22 09:13:16	ga_ls7e_ard_3-1-0_092082_2019-12-21_final
2019-12-22 09:13:40	ga_ls7e_ard_3-1-0_092083_2019-12-21_final
2019-12-22 09:14:04	ga_ls7e_ard_3-1-0_092084_2019-12-21_final
2019-12-22 09:14:28	ga_ls7e_ard_3-1-0_092085_2019-12-21_final
2019-12-22 09:14:52	ga_ls7e_ard_3-1-0_092086_2019-12-21_final
2019-12-22 09:15:16	ga_ls7e_ard_3-1-0_092087_2019-12-21_final
2019-12-22 09:15:40	ga_ls7e_ard_3-1-0_092088_2019-12-21_final
2019-12-22 09:16:04	ga_ls7e_ard_3-1-0_092089_2019-12-21_final
2019-12-22 10:46:58	ga_ls7e_ard_3-1-0_108069_2019-12-22_final
2019-12-22 10:47:22	ga_ls7e_ard_3-1-0_108070_2019-12-22_final
2019-12-22 10:47:46	ga_ls7e_ard_3-1-0_108071_2019-12-22_final
2019-12-22 10:48:10	ga_ls7e_ard_3-1-0_108072_2019-12-22_final
2019-12-22 10:48:34	ga_ls7e_ard_3-1-0_108073_2019-12-22_final
2019-12-22 10:48:58	ga_ls7e_ard_3-1-0_108074_2019-12-22_final
2019-12-22 10:49:22	ga_ls7e_ard_3-1-0_108075_2019-12-22_final
2019-12-22 10:49:46	ga_ls7e_ard_3-1-0_108076_2019-12-22_final
2019-12-22 10:50:10	ga_ls7e_ard_3-1-0_108077_2019-12-22_final
2019-12-22 10:50:33	ga_ls7e_ard_3-1-0_108078_2019-12-22_final

Return to ga_ls7e_ard_3 across December 2019 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

2019

December

All days