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

73 results

Time (local)	Label
2021-12-18 10:02:29	ga_ls7e_ard_3-2-1_109074_2021-12-18_final
2021-12-18 10:04:29	ga_ls7e_ard_3-2-1_109079_2021-12-18_final
2021-12-18 10:06:05	ga_ls7e_ard_3-2-1_109083_2021-12-18_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2021-12-19 09:06:46	ga_ls7e_ard_3-2-1_100074_2021-12-18_final
2021-12-20 09:51:56	ga_ls7e_ard_3-2-1_107079_2021-12-20_final
2021-12-22 09:37:47	ga_ls7e_ard_3-2-1_105075_2021-12-22_final
2021-12-22 09:38:58	ga_ls7e_ard_3-2-1_105078_2021-12-22_final
2021-12-23 10:20:56	ga_ls7e_ard_3-2-1_112075_2021-12-23_final
2021-12-24 09:26:25	ga_ls7e_ard_3-2-1_103078_2021-12-23_final
2021-12-24 09:27:37	ga_ls7e_ard_3-2-1_103081_2021-12-23_final
2021-12-25 10:07:59	ga_ls7e_ard_3-2-1_110074_2021-12-25_final
2021-12-25 10:09:11	ga_ls7e_ard_3-2-1_110077_2021-12-25_final
2021-12-25 10:11:34	ga_ls7e_ard_3-2-1_110083_2021-12-25_final
2021-12-26 09:13:27	ga_ls7e_ard_3-2-1_101077_2021-12-25_final
2021-12-26 09:14:39	ga_ls7e_ard_3-2-1_101080_2021-12-25_final
2021-12-27 08:19:20	ga_ls7e_ard_3-2-1_092081_2021-12-26_final
2021-12-27 08:21:20	ga_ls7e_ard_3-2-1_092086_2021-12-26_final
2021-12-27 09:53:49	ga_ls7e_ard_3-2-1_108070_2021-12-27_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-27 09:57:49	ga_ls7e_ard_3-2-1_108080_2021-12-27_final
2021-12-28 09:02:06	ga_ls7e_ard_3-2-1_099080_2021-12-27_final
2021-12-29 08:06:22	ga_ls7e_ard_3-2-1_090080_2021-12-28_final
2021-12-29 08:09:58	ga_ls7e_ard_3-2-1_090089_2021-12-28_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2021-12-30 08:50:44	ga_ls7e_ard_3-2-1_097083_2021-12-29_final
2021-12-30 10:26:25	ga_ls7e_ard_3-2-1_113075_2021-12-30_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2021-12-30 10:27:37	ga_ls7e_ard_3-2-1_113078_2021-12-30_final
2021-12-30 10:28:01	ga_ls7e_ard_3-2-1_113079_2021-12-30_final
2021-12-30 10:28:25	ga_ls7e_ard_3-2-1_113080_2021-12-30_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-01 08:34:58	ga_ls7e_ard_3-2-1_095075_2021-12-31_final
2022-01-01 08:35:22	ga_ls7e_ard_3-2-1_095076_2021-12-31_final
2022-01-01 08:37:46	ga_ls7e_ard_3-2-1_095082_2021-12-31_final
2022-01-01 08:39:22	ga_ls7e_ard_3-2-1_095086_2021-12-31_final
2022-01-11 09:09:29	ga_ls7e_ard_3-2-1_101071_2022-01-10_final
2022-01-11 09:09:53	ga_ls7e_ard_3-2-1_101072_2022-01-10_final
2022-01-11 09:10:17	ga_ls7e_ard_3-2-1_101073_2022-01-10_final
2022-01-11 09:11:05	ga_ls7e_ard_3-2-1_101075_2022-01-10_final
2022-01-11 09:11:29	ga_ls7e_ard_3-2-1_101076_2022-01-10_final
2022-01-11 09:11:53	ga_ls7e_ard_3-2-1_101077_2022-01-10_final
2022-01-11 09:12:41	ga_ls7e_ard_3-2-1_101079_2022-01-10_final
2022-01-11 09:13:29	ga_ls7e_ard_3-2-1_101081_2022-01-10_final
2022-01-12 08:15:22	ga_ls7e_ard_3-2-1_092075_2022-01-11_final
2022-01-12 08:15:46	ga_ls7e_ard_3-2-1_092076_2022-01-11_final
2022-01-12 08:16:10	ga_ls7e_ard_3-2-1_092077_2022-01-11_final
2022-01-12 08:16:34	ga_ls7e_ard_3-2-1_092078_2022-01-11_final
2022-01-12 08:16:58	ga_ls7e_ard_3-2-1_092079_2022-01-11_final
2022-01-12 08:17:22	ga_ls7e_ard_3-2-1_092080_2022-01-11_final
2022-01-12 08:17:46	ga_ls7e_ard_3-2-1_092081_2022-01-11_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-12 08:18:34	ga_ls7e_ard_3-2-1_092083_2022-01-11_final
2022-01-12 08:18:58	ga_ls7e_ard_3-2-1_092084_2022-01-11_final
2022-01-12 08:19:22	ga_ls7e_ard_3-2-1_092085_2022-01-11_final
2022-01-12 08:19:46	ga_ls7e_ard_3-2-1_092086_2022-01-11_final
2022-01-12 08:20:10	ga_ls7e_ard_3-2-1_092087_2022-01-11_final
2022-01-12 09:51:52	ga_ls7e_ard_3-2-1_108069_2022-01-12_final
2022-01-12 09:52:15	ga_ls7e_ard_3-2-1_108070_2022-01-12_final
2022-01-12 09:52:39	ga_ls7e_ard_3-2-1_108071_2022-01-12_final
2022-01-12 09:53:03	ga_ls7e_ard_3-2-1_108072_2022-01-12_final
2022-01-12 09:53:27	ga_ls7e_ard_3-2-1_108073_2022-01-12_final
2022-01-12 09:53:51	ga_ls7e_ard_3-2-1_108074_2022-01-12_final
2022-01-12 09:54:15	ga_ls7e_ard_3-2-1_108075_2022-01-12_final
2022-01-12 09:54:39	ga_ls7e_ard_3-2-1_108076_2022-01-12_final
2022-01-12 09:55:03	ga_ls7e_ard_3-2-1_108077_2022-01-12_final
2022-01-12 09:55:27	ga_ls7e_ard_3-2-1_108078_2022-01-12_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-12 09:56:39	ga_ls7e_ard_3-2-1_108081_2022-01-12_final
2022-01-12 09:57:03	ga_ls7e_ard_3-2-1_108082_2022-01-12_final
2022-01-12 09:57:27	ga_ls7e_ard_3-2-1_108083_2022-01-12_final
2022-01-12 09:57:51	ga_ls7e_ard_3-2-1_108084_2022-01-12_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