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
2021-09-18 08:53:23	ga_ls7e_ard_3-2-0_096081_2021-09-17_final
2021-09-18 08:53:47	ga_ls7e_ard_3-2-0_096082_2021-09-17_final
2021-09-20 08:38:51	ga_ls7e_ard_3-2-0_094076_2021-09-19_final
2021-09-20 10:16:08	ga_ls7e_ard_3-2-0_110072_2021-09-20_final
2021-09-20 10:18:08	ga_ls7e_ard_3-2-0_110077_2021-09-20_final
2021-09-20 10:18:32	ga_ls7e_ard_3-2-0_110078_2021-09-20_final
2021-11-07 08:35:19	ga_ls7e_ard_3-2-0_094078_2021-11-06_final
2021-11-07 10:14:59	ga_ls7e_ard_3-2-0_110080_2021-11-07_final
2021-11-12 10:32:15	ga_ls7e_ard_3-2-1_113078_2021-11-12_final
2021-11-16 10:08:20	ga_ls7e_ard_3-2-1_109081_2021-11-16_final
2021-11-18 09:52:11	ga_ls7e_ard_3-2-1_107072_2021-11-18_final
2021-11-21 08:47:54	ga_ls7e_ard_3-2-1_096082_2021-11-20_final
2021-11-27 09:44:44	ga_ls7e_ard_3-2-1_106071_2021-11-27_final
2021-12-01 09:20:51	ga_ls7e_ard_3-2-1_102074_2021-11-30_final
2021-12-02 10:03:13	ga_ls7e_ard_3-2-1_109072_2021-12-02_final
2021-12-04 08:15:47	ga_ls7e_ard_3-2-1_091082_2021-12-03_final
2021-12-05 08:55:21	ga_ls7e_ard_3-2-1_098073_2021-12-04_final
2021-12-07 10:23:17	ga_ls7e_ard_3-2-1_112077_2021-12-07_final
2021-12-18 10:01:41	ga_ls7e_ard_3-2-1_109072_2021-12-18_final
2021-12-19 09:07:10	ga_ls7e_ard_3-2-1_100075_2021-12-18_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-20 09:51:08	ga_ls7e_ard_3-2-1_107077_2021-12-20_final
2021-12-23 10:23:44	ga_ls7e_ard_3-2-1_112082_2021-12-23_final
2021-12-27 09:59:25	ga_ls7e_ard_3-2-1_108084_2021-12-27_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 08:47:56	ga_ls7e_ard_3-2-1_097076_2021-12-29_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 10:17:26	ga_ls7e_ard_3-2-1_111084_2022-01-01_final
2022-01-05 08:11:02	ga_ls7e_ard_3-2-1_091078_2022-01-04_final
2022-01-05 08:12:14	ga_ls7e_ard_3-2-1_091081_2022-01-04_final
2022-01-06 08:50:37	ga_ls7e_ard_3-2-1_098069_2022-01-05_final
2022-01-06 08:52:13	ga_ls7e_ard_3-2-1_098073_2022-01-05_final
2022-01-08 10:19:21	ga_ls7e_ard_3-2-1_112075_2022-01-08_final
2022-01-09 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-09 09:26:26	ga_ls7e_ard_3-2-1_103082_2022-01-08_final
2022-01-10 08:29:55	ga_ls7e_ard_3-2-1_094080_2022-01-09_final
2022-01-10 08:31:07	ga_ls7e_ard_3-2-1_094083_2022-01-09_final
2022-01-12 08:16:10	ga_ls7e_ard_3-2-1_092077_2022-01-11_final
2022-01-12 09:55:27	ga_ls7e_ard_3-2-1_108078_2022-01-12_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-17 10:14:43	ga_ls7e_ard_3-2-1_111081_2022-01-17_final
2022-01-23 09:32:40	ga_ls7e_ard_3-2-1_105070_2022-01-23_final
2022-01-26 10:07:16	ga_ls7e_ard_3-2-1_110080_2022-01-26_final
2022-01-27 09:11:57	ga_ls7e_ard_3-2-1_101081_2022-01-26_final
2022-01-31 08:45:14	ga_ls7e_ard_3-2-1_097077_2022-01-30_final
2022-02-02 10:13:09	ga_ls7e_ard_3-2-1_111081_2022-02-02_final
2022-02-03 09:17:50	ga_ls7e_ard_3-2-1_102082_2022-02-02_final
2022-02-04 08:24:06	ga_ls7e_ard_3-2-1_093087_2022-02-03_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-06 08:09:57	ga_ls7e_ard_3-2-1_091083_2022-02-05_final
2022-02-06 09:45:38	ga_ls7e_ard_3-2-1_107075_2022-02-06_final
2022-02-07 08:49:54	ga_ls7e_ard_3-2-1_098075_2022-02-06_final
2022-02-07 08:52:42	ga_ls7e_ard_3-2-1_098082_2022-02-06_final
2022-02-09 08:40:32	ga_ls7e_ard_3-2-1_096083_2022-02-08_final
2022-02-11 08:27:10	ga_ls7e_ard_3-2-1_094081_2022-02-10_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-11 10:07:14	ga_ls7e_ard_3-2-1_110084_2022-02-11_final
2022-02-14 08:54:57	ga_ls7e_ard_3-2-1_099074_2022-02-13_final
2022-02-16 08:43:11	ga_ls7e_ard_3-2-1_097076_2022-02-15_final
2022-02-16 08:43:35	ga_ls7e_ard_3-2-1_097077_2022-02-15_final
2022-02-17 09:25:57	ga_ls7e_ard_3-2-1_104075_2022-02-16_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-18 08:33:02	ga_ls7e_ard_3-2-1_095082_2022-02-17_final
2022-02-18 10:11:31	ga_ls7e_ard_3-2-1_111081_2022-02-18_final
2022-02-18 10:11:55	ga_ls7e_ard_3-2-1_111082_2022-02-18_final
2022-02-19 09:15:00	ga_ls7e_ard_3-2-1_102079_2022-02-18_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-24 09:34:16	ga_ls7e_ard_3-2-1_105082_2022-02-24_final
2022-02-25 08:38:09	ga_ls7e_ard_3-2-1_096081_2022-02-24_final
2022-02-25 08:39:21	ga_ls7e_ard_3-2-1_096084_2022-02-24_final
2022-02-26 09:20:07	ga_ls7e_ard_3-2-1_103078_2022-02-25_final
2022-02-27 08:25:12	ga_ls7e_ard_3-2-1_094080_2022-02-26_final
2022-03-02 08:57:24	ga_ls7e_ard_3-2-1_099084_2022-03-01_final
2022-03-05 09:25:37	ga_ls7e_ard_3-2-1_104078_2022-03-04_final
2022-03-08 08:19:20	ga_ls7e_ard_3-2-1_093083_2022-03-07_final
2022-03-08 09:55:25	ga_ls7e_ard_3-2-1_109076_2022-03-08_final
2022-03-08 09:56:13	ga_ls7e_ard_3-2-1_109078_2022-03-08_final
2022-03-10 09:42:04	ga_ls7e_ard_3-2-1_107074_2022-03-10_final
2022-03-11 08:46:45	ga_ls7e_ard_3-2-1_098075_2022-03-10_final
2022-03-13 08:36:59	ga_ls7e_ard_3-2-1_096082_2022-03-12_final
2022-03-14 09:15:21	ga_ls7e_ard_3-2-1_103070_2022-03-13_final
2022-03-17 09:51:07	ga_ls7e_ard_3-2-1_108083_2022-03-17_final
2022-03-18 08:52:12	ga_ls7e_ard_3-2-1_099075_2022-03-17_final
2022-03-19 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-20 08:39:16	ga_ls7e_ard_3-2-1_097074_2022-03-19_final
2022-03-21 09:22:02	ga_ls7e_ard_3-2-1_104073_2022-03-20_final
2022-03-21 09:22:50	ga_ls7e_ard_3-2-1_104075_2022-03-20_final
2022-03-22 08:27:07	ga_ls7e_ard_3-2-1_095075_2022-03-21_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-24 09:54:15	ga_ls7e_ard_3-2-1_109077_2022-03-24_final
2022-03-25 08:56:56	ga_ls7e_ard_3-2-1_100073_2022-03-24_final
2022-03-25 09:00:32	ga_ls7e_ard_3-2-1_100082_2022-03-24_final
2022-03-26 09:40:30	ga_ls7e_ard_3-2-1_107074_2022-03-26_final
2022-03-30 09:15:00	ga_ls7e_ard_3-2-1_103073_2022-03-29_final
2022-03-30 09:16:36	ga_ls7e_ard_3-2-1_103077_2022-03-29_final
2022-03-31 08:19:41	ga_ls7e_ard_3-2-1_094074_2022-03-30_final
2022-03-31 08:23:41	ga_ls7e_ard_3-2-1_094084_2022-03-30_final
2022-04-04 09:33:27	ga_ls7e_ard_3-2-1_106074_2022-04-04_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