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
2021-03-25 08:24:47	ga_ls7e_ard_3-2-0_089080_2021-03-24_final
2021-09-24 09:51:51	ga_ls7e_ard_3-2-0_106074_2021-09-24_final
2021-09-25 09:00:32	ga_ls7e_ard_3-2-0_097085_2021-09-24_final
2021-09-27 08:47:35	ga_ls7e_ard_3-2-0_095084_2021-09-26_final
2021-09-28 09:27:58	ga_ls7e_ard_3-2-0_102077_2021-09-27_final
2021-09-29 10:12:44	ga_ls7e_ard_3-2-0_109081_2021-09-29_final
2021-10-02 10:40:59	ga_ls7e_ard_3-2-0_114075_2021-10-02_final
2021-10-09 10:48:08	ga_ls7e_ard_3-2-0_115079_2021-10-09_final
2021-10-10 08:14:45	ga_ls7e_ard_3-2-0_090082_2021-10-09_final
2021-10-12 09:36:18	ga_ls7e_ard_3-2-0_104070_2021-10-12_final
2021-10-26 08:14:31	ga_ls7e_ard_3-2-0_090085_2021-10-25_final
2021-10-27 08:52:29	ga_ls7e_ard_3-2-0_097072_2021-10-26_final
2021-10-27 08:53:17	ga_ls7e_ard_3-2-0_097074_2021-10-26_final
2021-10-27 10:32:34	ga_ls7e_ard_3-2-0_113075_2021-10-27_final
2021-10-27 10:36:09	ga_ls7e_ard_3-2-0_113084_2021-10-27_final
2021-10-28 09:34:27	ga_ls7e_ard_3-2-0_104069_2021-10-28_final
2021-10-29 08:44:44	ga_ls7e_ard_3-2-0_095084_2021-10-28_final
2021-10-29 10:22:25	ga_ls7e_ard_3-2-0_111081_2021-10-29_final
2021-10-31 08:33:47	ga_ls7e_ard_3-2-0_093088_2021-10-30_final
2021-11-02 09:55:43	ga_ls7e_ard_3-2-0_107077_2021-11-02_final
2021-11-04 09:41:11	ga_ls7e_ard_3-2-0_105072_2021-11-04_final
2021-11-05 08:50:15	ga_ls7e_ard_3-2-0_096084_2021-11-04_final
2021-11-06 09:29:02	ga_ls7e_ard_3-2-0_103073_2021-11-05_final
2021-11-08 09:16:53	ga_ls7e_ard_3-2-0_101074_2021-11-07_final
2021-11-09 08:25:33	ga_ls7e_ard_3-2-0_092085_2021-11-08_final
2021-11-09 10:00:02	ga_ls7e_ard_3-2-0_108074_2021-11-09_final
2021-11-14 10:15:42	ga_ls7e_ard_3-2-1_111068_2021-11-14_final
2021-11-14 10:18:29	ga_ls7e_ard_3-2-1_111075_2021-11-14_final
2021-11-15 09:20:47	ga_ls7e_ard_3-2-1_102070_2021-11-14_final
2021-11-16 08:27:04	ga_ls7e_ard_3-2-1_093075_2021-11-15_final
2021-11-21 08:43:55	ga_ls7e_ard_3-2-1_096072_2021-11-20_final
2021-11-21 10:27:34	ga_ls7e_ard_3-2-1_112084_2021-11-21_final
2021-11-23 08:34:56	ga_ls7e_ard_3-2-1_094081_2021-11-22_final
2021-11-23 08:35:20	ga_ls7e_ard_3-2-1_094082_2021-11-22_final
2021-11-23 10:11:49	ga_ls7e_ard_3-2-1_110076_2021-11-23_final
2021-11-28 10:29:30	ga_ls7e_ard_3-2-1_113075_2021-11-28_final
2021-11-28 10:31:30	ga_ls7e_ard_3-2-1_113080_2021-11-28_final
2021-11-29 09:35:47	ga_ls7e_ard_3-2-1_104080_2021-11-29_final
2021-11-30 08:40:52	ga_ls7e_ard_3-2-1_095082_2021-11-29_final
2021-12-03 09:11:29	ga_ls7e_ard_3-2-1_100082_2021-12-02_final
2021-12-04 08:15:23	ga_ls7e_ard_3-2-1_091081_2021-12-03_final
2021-12-09 10:12:19	ga_ls7e_ard_3-2-1_110081_2021-12-09_final
2021-12-11 10:00:10	ga_ls7e_ard_3-2-1_108082_2021-12-11_final
2021-12-14 08:48:19	ga_ls7e_ard_3-2-1_097073_2021-12-13_final
2021-12-16 08:38:57	ga_ls7e_ard_3-2-1_095081_2021-12-15_final
2021-12-16 10:12:39	ga_ls7e_ard_3-2-1_111068_2021-12-16_final
2021-12-18 08:27:12	ga_ls7e_ard_3-2-1_093083_2021-12-17_final
2021-12-18 10:02:05	ga_ls7e_ard_3-2-1_109073_2021-12-18_final
2021-12-21 10:33:06	ga_ls7e_ard_3-2-1_114074_2021-12-21_final
2021-12-21 10:35:29	ga_ls7e_ard_3-2-1_114080_2021-12-21_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2021-12-30 10:28:48	ga_ls7e_ard_3-2-1_113081_2021-12-30_final
2022-01-03 10:01:41	ga_ls7e_ard_3-2-1_109076_2022-01-03_final
2022-01-03 10:04:05	ga_ls7e_ard_3-2-1_109082_2022-01-03_final
2022-01-06 08:50:37	ga_ls7e_ard_3-2-1_098069_2022-01-05_final
2022-01-08 08:39:40	ga_ls7e_ard_3-2-1_096073_2022-01-07_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-12 09:57:27	ga_ls7e_ard_3-2-1_108083_2022-01-12_final
2022-01-14 09:41:18	ga_ls7e_ard_3-2-1_106074_2022-01-14_final
2022-01-17 08:33:03	ga_ls7e_ard_3-2-1_095074_2022-01-16_final
2022-01-22 10:31:11	ga_ls7e_ard_3-2-1_114077_2022-01-22_final
2022-02-01 09:25:36	ga_ls7e_ard_3-2-1_104070_2022-01-31_final
2022-02-02 08:31:29	ga_ls7e_ard_3-2-1_095074_2022-02-01_final
2022-02-02 10:07:58	ga_ls7e_ard_3-2-1_111068_2022-02-02_final
2022-02-04 08:23:18	ga_ls7e_ard_3-2-1_093085_2022-02-03_final
2022-02-10 09:23:17	ga_ls7e_ard_3-2-1_103082_2022-02-09_final
2022-02-11 10:03:15	ga_ls7e_ard_3-2-1_110074_2022-02-11_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-21 09:03:15	ga_ls7e_ard_3-2-1_100081_2022-02-20_final
2022-02-22 08:05:57	ga_ls7e_ard_3-2-1_091077_2022-02-21_final
2022-02-22 08:07:56	ga_ls7e_ard_3-2-1_091082_2022-02-21_final
2022-02-23 10:26:47	ga_ls7e_ard_3-2-1_114074_2022-02-23_final
2022-02-23 10:27:59	ga_ls7e_ard_3-2-1_114077_2022-02-23_final
2022-02-24 09:33:52	ga_ls7e_ard_3-2-1_105081_2022-02-24_final
2022-02-27 08:26:00	ga_ls7e_ard_3-2-1_094082_2022-02-26_final
2022-02-28 09:09:10	ga_ls7e_ard_3-2-1_101082_2022-02-27_final
2022-03-04 10:22:32	ga_ls7e_ard_3-2-1_113081_2022-03-04_final
2022-03-04 10:22:56	ga_ls7e_ard_3-2-1_113082_2022-03-04_final
2022-03-06 10:11:10	ga_ls7e_ard_3-2-1_111084_2022-03-06_final
2022-03-09 08:58:54	ga_ls7e_ard_3-2-1_100074_2022-03-08_final
2022-03-09 09:00:54	ga_ls7e_ard_3-2-1_100079_2022-03-08_final
2022-03-10 08:05:11	ga_ls7e_ard_3-2-1_091079_2022-03-09_final
2022-03-10 08:05:59	ga_ls7e_ard_3-2-1_091081_2022-03-09_final
2022-03-11 08:44:21	ga_ls7e_ard_3-2-1_098069_2022-03-10_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-17 08:13:26	ga_ls7e_ard_3-2-1_092086_2022-03-16_final
2022-03-17 09:47:32	ga_ls7e_ard_3-2-1_108074_2022-03-17_final
2022-03-18 10:30:41	ga_ls7e_ard_3-2-1_115074_2022-03-18_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-24 09:52:39	ga_ls7e_ard_3-2-1_109073_2022-03-24_final
2022-03-27 10:25:40	ga_ls7e_ard_3-2-1_114079_2022-03-27_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-31 08:22:53	ga_ls7e_ard_3-2-1_094082_2022-03-30_final
2022-03-31 09:58:58	ga_ls7e_ard_3-2-1_110075_2022-03-31_final
2022-04-01 09:04:03	ga_ls7e_ard_3-2-1_101077_2022-03-31_final
2022-04-02 09:45:37	ga_ls7e_ard_3-2-1_108073_2022-04-02_final
2022-04-04 07:56:10	ga_ls7e_ard_3-2-1_090078_2022-04-03_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_2022-04-03_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_2022-04-04_final
2022-04-05 08:36:56	ga_ls7e_ard_3-2-1_097072_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years