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

First 100 results (query limit)

Time (local)	Label
2022-03-22 08:26:19	ga_ls7e_ard_3-2-1_095073_2022-03-21_final
2022-03-22 08:26:43	ga_ls7e_ard_3-2-1_095074_2022-03-21_final
2022-03-22 08:27:07	ga_ls7e_ard_3-2-1_095075_2022-03-21_final
2022-03-22 08:27:31	ga_ls7e_ard_3-2-1_095076_2022-03-21_final
2022-03-22 08:27:55	ga_ls7e_ard_3-2-1_095077_2022-03-21_final
2022-03-22 08:28:19	ga_ls7e_ard_3-2-1_095078_2022-03-21_final
2022-03-22 08:28:43	ga_ls7e_ard_3-2-1_095079_2022-03-21_final
2022-03-22 08:29:31	ga_ls7e_ard_3-2-1_095081_2022-03-21_final
2022-03-22 08:29:55	ga_ls7e_ard_3-2-1_095082_2022-03-21_final
2022-03-22 08:30:43	ga_ls7e_ard_3-2-1_095084_2022-03-21_final
2022-03-22 10:03:12	ga_ls7e_ard_3-2-1_111068_2022-03-22_final
2022-03-22 10:03:36	ga_ls7e_ard_3-2-1_111069_2022-03-22_final
2022-03-22 10:04:24	ga_ls7e_ard_3-2-1_111071_2022-03-22_final
2022-03-22 10:04:48	ga_ls7e_ard_3-2-1_111072_2022-03-22_final
2022-03-22 10:06:00	ga_ls7e_ard_3-2-1_111075_2022-03-22_final
2022-03-22 10:06:24	ga_ls7e_ard_3-2-1_111076_2022-03-22_final
2022-03-22 10:07:12	ga_ls7e_ard_3-2-1_111078_2022-03-22_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-23 09:07:30	ga_ls7e_ard_3-2-1_102068_2022-03-22_final
2022-03-23 09:07:54	ga_ls7e_ard_3-2-1_102069_2022-03-22_final
2022-03-23 09:08:17	ga_ls7e_ard_3-2-1_102070_2022-03-22_final
2022-03-23 09:08:41	ga_ls7e_ard_3-2-1_102071_2022-03-22_final
2022-03-23 09:09:05	ga_ls7e_ard_3-2-1_102072_2022-03-22_final
2022-03-23 09:09:53	ga_ls7e_ard_3-2-1_102074_2022-03-22_final
2022-03-23 09:10:17	ga_ls7e_ard_3-2-1_102075_2022-03-22_final
2022-03-23 09:10:41	ga_ls7e_ard_3-2-1_102076_2022-03-22_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-23 09:11:29	ga_ls7e_ard_3-2-1_102078_2022-03-22_final
2022-03-23 09:12:17	ga_ls7e_ard_3-2-1_102080_2022-03-22_final
2022-03-23 09:12:41	ga_ls7e_ard_3-2-1_102081_2022-03-22_final
2022-03-23 09:13:05	ga_ls7e_ard_3-2-1_102082_2022-03-22_final
2022-03-24 08:14:10	ga_ls7e_ard_3-2-1_093074_2022-03-23_final
2022-03-24 08:14:58	ga_ls7e_ard_3-2-1_093076_2022-03-23_final
2022-03-24 08:15:22	ga_ls7e_ard_3-2-1_093077_2022-03-23_final
2022-03-24 08:15:46	ga_ls7e_ard_3-2-1_093078_2022-03-23_final
2022-03-24 08:16:10	ga_ls7e_ard_3-2-1_093079_2022-03-23_final
2022-03-24 08:16:34	ga_ls7e_ard_3-2-1_093080_2022-03-23_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-24 08:17:22	ga_ls7e_ard_3-2-1_093082_2022-03-23_final
2022-03-24 08:17:46	ga_ls7e_ard_3-2-1_093083_2022-03-23_final
2022-03-24 08:18:10	ga_ls7e_ard_3-2-1_093084_2022-03-23_final
2022-03-24 08:18:34	ga_ls7e_ard_3-2-1_093085_2022-03-23_final
2022-03-24 08:18:58	ga_ls7e_ard_3-2-1_093086_2022-03-23_final
2022-03-24 08:19:22	ga_ls7e_ard_3-2-1_093087_2022-03-23_final
2022-03-24 09:51:27	ga_ls7e_ard_3-2-1_109070_2022-03-24_final
2022-03-24 09:53:03	ga_ls7e_ard_3-2-1_109074_2022-03-24_final
2022-03-24 09:53:27	ga_ls7e_ard_3-2-1_109075_2022-03-24_final
2022-03-24 09:53:51	ga_ls7e_ard_3-2-1_109076_2022-03-24_final
2022-03-24 09:54:39	ga_ls7e_ard_3-2-1_109078_2022-03-24_final
2022-03-24 09:55:03	ga_ls7e_ard_3-2-1_109079_2022-03-24_final
2022-03-24 09:55:27	ga_ls7e_ard_3-2-1_109080_2022-03-24_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-24 09:56:39	ga_ls7e_ard_3-2-1_109083_2022-03-24_final
2022-03-25 08:56:09	ga_ls7e_ard_3-2-1_100071_2022-03-24_final
2022-03-25 08:56:32	ga_ls7e_ard_3-2-1_100072_2022-03-24_final
2022-03-25 08:56:56	ga_ls7e_ard_3-2-1_100073_2022-03-24_final
2022-03-25 08:57:20	ga_ls7e_ard_3-2-1_100074_2022-03-24_final
2022-03-25 08:57:44	ga_ls7e_ard_3-2-1_100075_2022-03-24_final
2022-03-25 08:58:08	ga_ls7e_ard_3-2-1_100076_2022-03-24_final
2022-03-25 08:58:56	ga_ls7e_ard_3-2-1_100078_2022-03-24_final
2022-03-25 08:59:20	ga_ls7e_ard_3-2-1_100079_2022-03-24_final
2022-03-25 08:59:44	ga_ls7e_ard_3-2-1_100080_2022-03-24_final
2022-03-25 09:00:32	ga_ls7e_ard_3-2-1_100082_2022-03-24_final
2022-03-25 09:00:56	ga_ls7e_ard_3-2-1_100083_2022-03-24_final
2022-03-25 09:01:20	ga_ls7e_ard_3-2-1_100084_2022-03-24_final
2022-03-26 08:02:26	ga_ls7e_ard_3-2-1_091076_2022-03-25_final
2022-03-26 08:02:49	ga_ls7e_ard_3-2-1_091077_2022-03-25_final
2022-03-26 08:04:01	ga_ls7e_ard_3-2-1_091080_2022-03-25_final
2022-03-26 08:05:13	ga_ls7e_ard_3-2-1_091083_2022-03-25_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-26 08:06:49	ga_ls7e_ard_3-2-1_091087_2022-03-25_final
2022-03-26 09:38:55	ga_ls7e_ard_3-2-1_107070_2022-03-26_final
2022-03-26 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-26 09:41:18	ga_ls7e_ard_3-2-1_107076_2022-03-26_final
2022-03-26 09:41:42	ga_ls7e_ard_3-2-1_107077_2022-03-26_final
2022-03-26 09:42:06	ga_ls7e_ard_3-2-1_107078_2022-03-26_final
2022-03-26 09:43:18	ga_ls7e_ard_3-2-1_107081_2022-03-26_final
2022-03-26 09:43:42	ga_ls7e_ard_3-2-1_107082_2022-03-26_final
2022-03-27 08:42:48	ga_ls7e_ard_3-2-1_098069_2022-03-26_final
2022-03-27 08:43:12	ga_ls7e_ard_3-2-1_098070_2022-03-26_final
2022-03-27 08:43:36	ga_ls7e_ard_3-2-1_098071_2022-03-26_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-27 08:45:11	ga_ls7e_ard_3-2-1_098075_2022-03-26_final
2022-03-27 08:45:35	ga_ls7e_ard_3-2-1_098076_2022-03-26_final
2022-03-27 08:46:23	ga_ls7e_ard_3-2-1_098078_2022-03-26_final
2022-03-27 08:47:11	ga_ls7e_ard_3-2-1_098080_2022-03-26_final
2022-03-27 08:48:23	ga_ls7e_ard_3-2-1_098083_2022-03-26_final
2022-03-27 08:49:11	ga_ls7e_ard_3-2-1_098085_2022-03-26_final
2022-03-27 10:24:28	ga_ls7e_ard_3-2-1_114076_2022-03-27_final
2022-03-27 10:26:04	ga_ls7e_ard_3-2-1_114080_2022-03-27_final
2022-03-27 10:26:28	ga_ls7e_ard_3-2-1_114081_2022-03-27_final
2022-03-28 07:50:40	ga_ls7e_ard_3-2-1_089078_2022-03-27_final
2022-03-28 07:51:52	ga_ls7e_ard_3-2-1_089081_2022-03-27_final
2022-03-28 07:52:16	ga_ls7e_ard_3-2-1_089082_2022-03-27_final
2022-03-28 07:52:40	ga_ls7e_ard_3-2-1_089083_2022-03-27_final
2022-03-28 07:53:04	ga_ls7e_ard_3-2-1_089084_2022-03-27_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years