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 08:51:23	ga_ls7e_ard_3-2-0_096076_2021-09-17_final
2021-10-25 09:07:26	ga_ls7e_ard_3-2-0_099078_2021-10-24_final
2021-10-26 08:12:07	ga_ls7e_ard_3-2-0_090079_2021-10-25_final
2021-11-05 08:47:28	ga_ls7e_ard_3-2-0_096077_2021-11-04_final
2021-11-14 08:41:37	ga_ls7e_ard_3-2-1_095080_2021-11-13_final
2021-11-14 08:42:00	ga_ls7e_ard_3-2-1_095081_2021-11-13_final
2021-11-14 10:20:53	ga_ls7e_ard_3-2-1_111081_2021-11-14_final
2021-11-15 09:22:46	ga_ls7e_ard_3-2-1_102075_2021-11-14_final
2021-11-16 10:06:20	ga_ls7e_ard_3-2-1_109076_2021-11-16_final
2021-11-18 08:17:18	ga_ls7e_ard_3-2-1_091082_2021-11-17_final
2021-11-19 08:54:28	ga_ls7e_ard_3-2-1_098067_2021-11-18_final
2021-11-20 08:03:56	ga_ls7e_ard_3-2-1_089080_2021-11-19_final
2021-11-23 08:34:56	ga_ls7e_ard_3-2-1_094081_2021-11-22_final
2021-11-25 09:57:41	ga_ls7e_ard_3-2-1_108072_2021-11-25_final
2021-11-25 10:00:28	ga_ls7e_ard_3-2-1_108079_2021-11-25_final
2021-11-28 10:31:06	ga_ls7e_ard_3-2-1_113079_2021-11-28_final
2021-11-30 10:18:57	ga_ls7e_ard_3-2-1_111080_2021-11-30_final
2021-12-01 09:18:27	ga_ls7e_ard_3-2-1_102068_2021-11-30_final
2021-12-04 09:51:52	ga_ls7e_ard_3-2-1_107075_2021-12-04_final
2021-12-06 09:40:07	ga_ls7e_ard_3-2-1_105077_2021-12-06_final
2021-12-09 08:34:15	ga_ls7e_ard_3-2-1_094083_2021-12-08_final
2021-12-09 10:12:43	ga_ls7e_ard_3-2-1_110082_2021-12-09_final
2021-12-11 09:59:22	ga_ls7e_ard_3-2-1_108080_2021-12-11_final
2021-12-13 08:08:45	ga_ls7e_ard_3-2-1_090082_2021-12-12_final
2021-12-14 08:51:54	ga_ls7e_ard_3-2-1_097082_2021-12-13_final
2021-12-16 08:36:34	ga_ls7e_ard_3-2-1_095075_2021-12-15_final
2021-12-16 08:39:21	ga_ls7e_ard_3-2-1_095082_2021-12-15_final
2021-12-16 08:40:57	ga_ls7e_ard_3-2-1_095086_2021-12-15_final
2021-12-16 10:17:50	ga_ls7e_ard_3-2-1_111081_2021-12-16_final
2021-12-18 08:25:36	ga_ls7e_ard_3-2-1_093079_2021-12-17_final
2021-12-20 08:13:03	ga_ls7e_ard_3-2-1_091079_2021-12-19_final
2021-12-20 08:15:03	ga_ls7e_ard_3-2-1_091084_2021-12-19_final
2021-12-20 09:49:56	ga_ls7e_ard_3-2-1_107074_2021-12-20_final
2021-12-21 08:55:01	ga_ls7e_ard_3-2-1_098076_2021-12-20_final
2021-12-21 08:56:37	ga_ls7e_ard_3-2-1_098080_2021-12-20_final
2021-12-22 09:35:47	ga_ls7e_ard_3-2-1_105070_2021-12-22_final
2021-12-22 09:38:34	ga_ls7e_ard_3-2-1_105077_2021-12-22_final
2021-12-26 09:15:03	ga_ls7e_ard_3-2-1_101081_2021-12-25_final
2021-12-27 09:54:37	ga_ls7e_ard_3-2-1_108072_2021-12-27_final
2021-12-27 09:57:49	ga_ls7e_ard_3-2-1_108080_2021-12-27_final
2021-12-28 09:00:06	ga_ls7e_ard_3-2-1_099075_2021-12-27_final
2022-01-01 10:17:03	ga_ls7e_ard_3-2-1_111083_2022-01-01_final
2022-01-05 09:51:07	ga_ls7e_ard_3-2-1_107081_2022-01-05_final
2022-01-06 08:53:01	ga_ls7e_ard_3-2-1_098075_2022-01-05_final
2022-01-08 10:19:45	ga_ls7e_ard_3-2-1_112076_2022-01-08_final
2022-01-08 10:21:44	ga_ls7e_ard_3-2-1_112081_2022-01-08_final
2022-01-10 08:29:07	ga_ls7e_ard_3-2-1_094078_2022-01-09_final
2022-01-10 10:08:00	ga_ls7e_ard_3-2-1_110078_2022-01-10_final
2022-01-13 08:58:08	ga_ls7e_ard_3-2-1_099074_2022-01-12_final
2022-01-14 09:44:06	ga_ls7e_ard_3-2-1_106081_2022-01-14_final
2022-01-15 08:44:48	ga_ls7e_ard_3-2-1_097072_2022-01-14_final
2022-01-15 10:24:52	ga_ls7e_ard_3-2-1_113075_2022-01-15_final
2022-01-17 10:14:43	ga_ls7e_ard_3-2-1_111081_2022-01-17_final
2022-01-22 08:50:42	ga_ls7e_ard_3-2-1_098073_2022-01-21_final
2022-01-27 09:10:45	ga_ls7e_ard_3-2-1_101078_2022-01-26_final
2022-01-27 09:11:57	ga_ls7e_ard_3-2-1_101081_2022-01-26_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-02-03 09:16:38	ga_ls7e_ard_3-2-1_102079_2022-02-02_final
2022-02-05 09:05:16	ga_ls7e_ard_3-2-1_100082_2022-02-04_final
2022-02-05 09:06:04	ga_ls7e_ard_3-2-1_100084_2022-02-04_final
2022-02-06 09:44:02	ga_ls7e_ard_3-2-1_107071_2022-02-06_final
2022-02-06 09:47:37	ga_ls7e_ard_3-2-1_107080_2022-02-06_final
2022-02-08 07:56:59	ga_ls7e_ard_3-2-1_089082_2022-02-07_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-10 09:21:41	ga_ls7e_ard_3-2-1_103078_2022-02-09_final
2022-02-11 08:28:22	ga_ls7e_ard_3-2-1_094084_2022-02-10_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-13 09:49:05	ga_ls7e_ard_3-2-1_108070_2022-02-13_final
2022-02-14 10:35:26	ga_ls7e_ard_3-2-1_115078_2022-02-14_final
2022-02-18 10:11:07	ga_ls7e_ard_3-2-1_111080_2022-02-18_final
2022-02-19 09:13:00	ga_ls7e_ard_3-2-1_102074_2022-02-18_final
2022-02-20 08:22:29	ga_ls7e_ard_3-2-1_093087_2022-02-19_final
2022-02-21 09:00:51	ga_ls7e_ard_3-2-1_100075_2022-02-20_final
2022-02-27 08:22:49	ga_ls7e_ard_3-2-1_094074_2022-02-26_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-02 10:32:18	ga_ls7e_ard_3-2-1_115074_2022-03-02_final
2022-03-02 10:34:41	ga_ls7e_ard_3-2-1_115080_2022-03-02_final
2022-03-04 08:39:16	ga_ls7e_ard_3-2-1_097070_2022-03-03_final
2022-03-04 10:23:20	ga_ls7e_ard_3-2-1_113083_2022-03-04_final
2022-03-05 09:22:02	ga_ls7e_ard_3-2-1_104069_2022-03-04_final
2022-03-06 08:29:30	ga_ls7e_ard_3-2-1_095077_2022-03-05_final
2022-03-07 09:11:04	ga_ls7e_ard_3-2-1_102073_2022-03-06_final
2022-03-07 09:13:28	ga_ls7e_ard_3-2-1_102079_2022-03-06_final
2022-03-08 08:20:32	ga_ls7e_ard_3-2-1_093086_2022-03-07_final
2022-03-09 09:02:54	ga_ls7e_ard_3-2-1_100084_2022-03-08_final
2022-03-13 10:14:15	ga_ls7e_ard_3-2-1_112078_2022-03-13_final
2022-03-13 10:14:39	ga_ls7e_ard_3-2-1_112079_2022-03-13_final
2022-03-14 09:18:08	ga_ls7e_ard_3-2-1_103077_2022-03-13_final
2022-03-15 08:23:37	ga_ls7e_ard_3-2-1_094080_2022-03-14_final
2022-03-15 09:58:30	ga_ls7e_ard_3-2-1_110070_2022-03-15_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-22 08:29:31	ga_ls7e_ard_3-2-1_095081_2022-03-21_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-26 08:08:01	ga_ls7e_ard_3-2-1_091090_2022-03-25_final
2022-03-29 10:11:55	ga_ls7e_ard_3-2-1_112076_2022-03-29_final
2022-03-31 10:00:10	ga_ls7e_ard_3-2-1_110078_2022-03-31_final
2022-04-01 09:04:51	ga_ls7e_ard_3-2-1_101079_2022-03-31_final
2022-04-03 08:52:41	ga_ls7e_ard_3-2-1_099080_2022-04-02_final
2022-04-03 10:30:46	ga_ls7e_ard_3-2-1_115078_2022-04-03_final
2022-04-04 07:58:34	ga_ls7e_ard_3-2-1_090084_2022-04-03_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