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
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-20 09:49:32	ga_ls7e_ard_3-2-1_107073_2021-12-20_final
2021-12-27 09:57:25	ga_ls7e_ard_3-2-1_108079_2021-12-27_final
2021-12-31 09:29:06	ga_ls7e_ard_3-2-1_104071_2021-12-30_final
2021-12-31 09:29:30	ga_ls7e_ard_3-2-1_104072_2021-12-30_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-01 08:37:22	ga_ls7e_ard_3-2-1_095081_2021-12-31_final
2022-01-01 08:37:46	ga_ls7e_ard_3-2-1_095082_2021-12-31_final
2022-01-12 08:16:10	ga_ls7e_ard_3-2-1_092077_2022-01-11_final
2022-01-13 09:01:20	ga_ls7e_ard_3-2-1_099082_2022-01-12_final
2022-01-13 10:37:49	ga_ls7e_ard_3-2-1_115076_2022-01-13_final
2022-01-14 09:42:30	ga_ls7e_ard_3-2-1_106077_2022-01-14_final
2022-01-15 08:45:12	ga_ls7e_ard_3-2-1_097073_2022-01-14_final
2022-01-15 10:26:52	ga_ls7e_ard_3-2-1_113080_2022-01-15_final
2022-01-21 08:10:20	ga_ls7e_ard_3-2-1_091080_2022-01-20_final
2022-01-21 09:50:01	ga_ls7e_ard_3-2-1_107082_2022-01-21_final
2022-01-24 08:40:33	ga_ls7e_ard_3-2-1_096079_2022-01-23_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-25 09:23:42	ga_ls7e_ard_3-2-1_103079_2022-01-24_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-28 09:55:06	ga_ls7e_ard_3-2-1_108081_2022-01-28_final
2022-01-29 10:35:52	ga_ls7e_ard_3-2-1_115075_2022-01-29_final
2022-02-01 09:26:00	ga_ls7e_ard_3-2-1_104071_2022-01-31_final
2022-02-01 09:26:24	ga_ls7e_ard_3-2-1_104072_2022-01-31_final
2022-02-02 08:36:40	ga_ls7e_ard_3-2-1_095087_2022-02-01_final
2022-02-02 10:13:09	ga_ls7e_ard_3-2-1_111081_2022-02-02_final
2022-02-04 08:21:43	ga_ls7e_ard_3-2-1_093081_2022-02-03_final
2022-02-04 08:23:42	ga_ls7e_ard_3-2-1_093086_2022-02-03_final
2022-02-04 10:00:59	ga_ls7e_ard_3-2-1_109082_2022-02-04_final
2022-02-05 09:04:52	ga_ls7e_ard_3-2-1_100081_2022-02-04_final
2022-02-06 08:09:09	ga_ls7e_ard_3-2-1_091081_2022-02-05_final
2022-02-06 08:11:56	ga_ls7e_ard_3-2-1_091088_2022-02-05_final
2022-02-07 08:49:54	ga_ls7e_ard_3-2-1_098075_2022-02-06_final
2022-02-08 07:57:23	ga_ls7e_ard_3-2-1_089083_2022-02-07_final
2022-02-09 08:40:32	ga_ls7e_ard_3-2-1_096083_2022-02-08_final
2022-02-10 09:19:18	ga_ls7e_ard_3-2-1_103072_2022-02-09_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-11 10:06:03	ga_ls7e_ard_3-2-1_110081_2022-02-11_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-12 09:08:19	ga_ls7e_ard_3-2-1_101076_2022-02-11_final
2022-02-12 09:10:19	ga_ls7e_ard_3-2-1_101081_2022-02-11_final
2022-02-13 09:54:40	ga_ls7e_ard_3-2-1_108084_2022-02-13_final
2022-02-14 08:55:21	ga_ls7e_ard_3-2-1_099075_2022-02-13_final
2022-02-14 10:35:26	ga_ls7e_ard_3-2-1_115078_2022-02-14_final
2022-02-14 10:35:50	ga_ls7e_ard_3-2-1_115079_2022-02-14_final
2022-02-15 09:36:55	ga_ls7e_ard_3-2-1_106071_2022-02-15_final
2022-02-16 08:41:35	ga_ls7e_ard_3-2-1_097072_2022-02-15_final
2022-02-17 09:27:57	ga_ls7e_ard_3-2-1_104080_2022-02-16_final
2022-02-18 08:32:14	ga_ls7e_ard_3-2-1_095080_2022-02-17_final
2022-02-18 08:33:26	ga_ls7e_ard_3-2-1_095083_2022-02-17_final
2022-02-20 08:21:17	ga_ls7e_ard_3-2-1_093084_2022-02-19_final
2022-02-21 09:02:27	ga_ls7e_ard_3-2-1_100079_2022-02-20_final
2022-02-22 08:08:20	ga_ls7e_ard_3-2-1_091083_2022-02-21_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-23 08:48:19	ga_ls7e_ard_3-2-1_098075_2022-02-22_final
2022-02-23 10:27:35	ga_ls7e_ard_3-2-1_114076_2022-02-23_final
2022-02-24 09:32:40	ga_ls7e_ard_3-2-1_105078_2022-02-24_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-02-28 09:06:22	ga_ls7e_ard_3-2-1_101075_2022-02-27_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-02-28 09:07:10	ga_ls7e_ard_3-2-1_101077_2022-02-27_final
2022-03-01 09:51:32	ga_ls7e_ard_3-2-1_108080_2022-03-01_final
2022-03-02 08:53:01	ga_ls7e_ard_3-2-1_099073_2022-03-01_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_final
2022-03-04 08:41:16	ga_ls7e_ard_3-2-1_097075_2022-03-03_final
2022-03-06 08:31:54	ga_ls7e_ard_3-2-1_095083_2022-03-05_final
2022-03-06 10:07:35	ga_ls7e_ard_3-2-1_111075_2022-03-06_final
2022-03-07 09:10:40	ga_ls7e_ard_3-2-1_102072_2022-03-06_final
2022-03-08 08:15:45	ga_ls7e_ard_3-2-1_093074_2022-03-07_final
2022-03-08 08:18:33	ga_ls7e_ard_3-2-1_093081_2022-03-07_final
2022-03-10 08:05:35	ga_ls7e_ard_3-2-1_091080_2022-03-09_final
2022-03-11 08:45:57	ga_ls7e_ard_3-2-1_098073_2022-03-10_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-13 10:15:27	ga_ls7e_ard_3-2-1_112081_2022-03-13_final
2022-03-14 09:17:44	ga_ls7e_ard_3-2-1_103076_2022-03-13_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-17 09:46:20	ga_ls7e_ard_3-2-1_108071_2022-03-17_final
2022-03-17 09:50:19	ga_ls7e_ard_3-2-1_108081_2022-03-17_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-19 08:00:29	ga_ls7e_ard_3-2-1_090085_2022-03-18_final
2022-03-20 08:40:52	ga_ls7e_ard_3-2-1_097078_2022-03-19_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-20 08:42:27	ga_ls7e_ard_3-2-1_097082_2022-03-19_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-21 09:24:02	ga_ls7e_ard_3-2-1_104078_2022-03-20_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
2022-03-23 09:09:53	ga_ls7e_ard_3-2-1_102074_2022-03-22_final
2022-03-25 08:59:44	ga_ls7e_ard_3-2-1_100080_2022-03-24_final
2022-03-28 09:29:33	ga_ls7e_ard_3-2-1_105078_2022-03-27_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-29 08:35:50	ga_ls7e_ard_3-2-1_096083_2022-03-28_final
2022-03-30 09:16:36	ga_ls7e_ard_3-2-1_103077_2022-03-29_final
2022-03-31 08:21:41	ga_ls7e_ard_3-2-1_094079_2022-03-30_final
2022-03-31 08:22:29	ga_ls7e_ard_3-2-1_094081_2022-03-30_final
2022-03-31 09:59:46	ga_ls7e_ard_3-2-1_110077_2022-03-31_final
2022-04-01 09:03:39	ga_ls7e_ard_3-2-1_101076_2022-03-31_final
2022-04-01 09:04:03	ga_ls7e_ard_3-2-1_101077_2022-03-31_final
2022-04-03 08:49:54	ga_ls7e_ard_3-2-1_099073_2022-04-02_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