Search ga_ls7e_ard_3 whole collection

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

47 results

Time (local)	Label
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-16 09:27:58	ga_ls7e_ard_3-2-1_104072_2022-01-15_final
2022-01-17 08:32:15	ga_ls7e_ard_3-2-1_095072_2022-01-16_final
2022-01-17 08:32:39	ga_ls7e_ard_3-2-1_095073_2022-01-16_final
2022-01-17 08:33:03	ga_ls7e_ard_3-2-1_095074_2022-01-16_final
2022-01-17 08:35:50	ga_ls7e_ard_3-2-1_095081_2022-01-16_final
2022-01-17 08:37:26	ga_ls7e_ard_3-2-1_095085_2022-01-16_final
2022-01-17 08:37:50	ga_ls7e_ard_3-2-1_095086_2022-01-16_final
2022-01-17 10:11:31	ga_ls7e_ard_3-2-1_111073_2022-01-17_final
2022-01-17 10:11:55	ga_ls7e_ard_3-2-1_111074_2022-01-17_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-17 10:13:07	ga_ls7e_ard_3-2-1_111077_2022-01-17_final
2022-01-17 10:13:55	ga_ls7e_ard_3-2-1_111079_2022-01-17_final
2022-01-17 10:14:19	ga_ls7e_ard_3-2-1_111080_2022-01-17_final
2022-01-17 10:14:43	ga_ls7e_ard_3-2-1_111081_2022-01-17_final
2022-01-17 10:15:31	ga_ls7e_ard_3-2-1_111083_2022-01-17_final
2022-01-18 09:14:37	ga_ls7e_ard_3-2-1_102070_2022-01-17_final
2022-01-18 09:15:25	ga_ls7e_ard_3-2-1_102072_2022-01-17_final
2022-01-18 09:16:36	ga_ls7e_ard_3-2-1_102075_2022-01-17_final
2022-01-18 09:17:00	ga_ls7e_ard_3-2-1_102076_2022-01-17_final
2022-01-18 09:17:24	ga_ls7e_ard_3-2-1_102077_2022-01-17_final
2022-01-18 09:17:48	ga_ls7e_ard_3-2-1_102078_2022-01-17_final
2022-01-19 08:20:30	ga_ls7e_ard_3-2-1_093074_2022-01-18_final
2022-01-19 08:20:54	ga_ls7e_ard_3-2-1_093075_2022-01-18_final
2022-01-19 08:21:17	ga_ls7e_ard_3-2-1_093076_2022-01-18_final
2022-01-19 08:21:41	ga_ls7e_ard_3-2-1_093077_2022-01-18_final
2022-01-19 08:22:05	ga_ls7e_ard_3-2-1_093078_2022-01-18_final
2022-01-19 08:24:53	ga_ls7e_ard_3-2-1_093085_2022-01-18_final
2022-01-19 08:25:17	ga_ls7e_ard_3-2-1_093086_2022-01-18_final
2022-01-19 09:57:23	ga_ls7e_ard_3-2-1_109069_2022-01-19_final
2022-01-19 09:58:34	ga_ls7e_ard_3-2-1_109072_2022-01-19_final
2022-01-19 09:58:58	ga_ls7e_ard_3-2-1_109073_2022-01-19_final
2022-01-19 09:59:22	ga_ls7e_ard_3-2-1_109074_2022-01-19_final
2022-01-19 09:59:46	ga_ls7e_ard_3-2-1_109075_2022-01-19_final
2022-01-19 10:00:10	ga_ls7e_ard_3-2-1_109076_2022-01-19_final
2022-01-19 10:00:34	ga_ls7e_ard_3-2-1_109077_2022-01-19_final
2022-01-19 10:01:22	ga_ls7e_ard_3-2-1_109079_2022-01-19_final
2022-01-20 09:02:51	ga_ls7e_ard_3-2-1_100072_2022-01-19_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-01-20 09:04:03	ga_ls7e_ard_3-2-1_100075_2022-01-19_final
2022-01-20 09:04:27	ga_ls7e_ard_3-2-1_100076_2022-01-19_final
2022-01-20 09:04:51	ga_ls7e_ard_3-2-1_100077_2022-01-19_final
2022-01-20 09:05:15	ga_ls7e_ard_3-2-1_100078_2022-01-19_final
2022-01-20 09:05:39	ga_ls7e_ard_3-2-1_100079_2022-01-19_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-20 09:06:27	ga_ls7e_ard_3-2-1_100081_2022-01-19_final
2022-01-20 09:07:15	ga_ls7e_ard_3-2-1_100083_2022-01-19_final

Return to ga_ls7e_ard_3 whole collection overview

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

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years