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
2021-10-26 08:14:31	ga_ls7e_ard_3-2-0_090085_2021-10-25_final
2021-10-26 09:49:00	ga_ls7e_ard_3-2-0_106074_2021-10-26_final
2021-10-29 08:42:44	ga_ls7e_ard_3-2-0_095079_2021-10-28_final
2021-11-02 09:58:31	ga_ls7e_ard_3-2-0_107084_2021-11-02_final
2021-11-03 08:58:01	ga_ls7e_ard_3-2-0_098072_2021-11-02_final
2021-11-09 08:26:45	ga_ls7e_ard_3-2-0_092088_2021-11-08_final
2021-11-10 09:05:07	ga_ls7e_ard_3-2-0_099076_2021-11-09_final
2021-11-14 10:18:29	ga_ls7e_ard_3-2-1_111075_2021-11-14_final
2021-11-14 10:18:53	ga_ls7e_ard_3-2-1_111076_2021-11-14_final
2021-11-15 09:19:59	ga_ls7e_ard_3-2-1_102068_2021-11-14_final
2021-11-16 10:07:56	ga_ls7e_ard_3-2-1_109080_2021-11-16_final
2021-11-16 10:08:44	ga_ls7e_ard_3-2-1_109082_2021-11-16_final
2021-11-19 10:36:56	ga_ls7e_ard_3-2-1_114076_2021-11-19_final
2021-11-20 09:38:50	ga_ls7e_ard_3-2-1_105070_2021-11-20_final
2021-11-22 09:25:52	ga_ls7e_ard_3-2-1_103069_2021-11-21_final
2021-11-24 09:16:06	ga_ls7e_ard_3-2-1_101076_2021-11-23_final
2021-11-28 08:49:26	ga_ls7e_ard_3-2-1_097072_2021-11-27_final
2021-12-04 08:15:23	ga_ls7e_ard_3-2-1_091081_2021-12-03_final
2021-12-05 08:53:45	ga_ls7e_ard_3-2-1_098069_2021-12-04_final
2021-12-05 10:36:14	ga_ls7e_ard_3-2-1_114078_2021-12-05_final
2021-12-07 08:47:12	ga_ls7e_ard_3-2-1_096084_2021-12-06_final
2021-12-07 10:22:29	ga_ls7e_ard_3-2-1_112075_2021-12-07_final
2021-12-10 09:13:49	ga_ls7e_ard_3-2-1_101074_2021-12-09_final
2021-12-11 08:20:06	ga_ls7e_ard_3-2-1_092079_2021-12-10_final
2021-12-11 08:22:06	ga_ls7e_ard_3-2-1_092084_2021-12-10_final
2021-12-11 09:55:47	ga_ls7e_ard_3-2-1_108071_2021-12-11_final
2021-12-11 09:56:35	ga_ls7e_ard_3-2-1_108073_2021-12-11_final
2021-12-12 09:03:16	ga_ls7e_ard_3-2-1_099079_2021-12-11_final
2021-12-17 09:19:43	ga_ls7e_ard_3-2-1_102075_2021-12-16_final
2021-12-18 10:05:41	ga_ls7e_ard_3-2-1_109082_2021-12-18_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2021-12-20 08:13:51	ga_ls7e_ard_3-2-1_091081_2021-12-19_final
2021-12-21 08:55:01	ga_ls7e_ard_3-2-1_098076_2021-12-20_final
2021-12-21 10:33:06	ga_ls7e_ard_3-2-1_114074_2021-12-21_final
2021-12-21 10:33:54	ga_ls7e_ard_3-2-1_114076_2021-12-21_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-23 08:44:51	ga_ls7e_ard_3-2-1_096082_2021-12-22_final
2021-12-23 08:46:03	ga_ls7e_ard_3-2-1_096085_2021-12-22_final
2021-12-24 09:28:01	ga_ls7e_ard_3-2-1_103082_2021-12-23_final
2021-12-27 08:21:20	ga_ls7e_ard_3-2-1_092086_2021-12-26_final
2021-12-27 08:22:32	ga_ls7e_ard_3-2-1_092089_2021-12-26_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2021-12-30 08:50:20	ga_ls7e_ard_3-2-1_097082_2021-12-29_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2022-01-02 09:16:32	ga_ls7e_ard_3-2-1_102071_2022-01-01_final
2022-01-03 08:22:48	ga_ls7e_ard_3-2-1_093076_2022-01-02_final
2022-01-04 09:08:21	ga_ls7e_ard_3-2-1_100082_2022-01-03_final
2022-01-06 08:55:48	ga_ls7e_ard_3-2-1_098082_2022-01-05_final
2022-01-08 08:38:28	ga_ls7e_ard_3-2-1_096070_2022-01-07_final
2022-01-10 10:09:12	ga_ls7e_ard_3-2-1_110081_2022-01-10_final
2022-01-11 09:12:17	ga_ls7e_ard_3-2-1_101078_2022-01-10_final
2022-01-12 08:16:34	ga_ls7e_ard_3-2-1_092078_2022-01-11_final
2022-01-12 08:17:46	ga_ls7e_ard_3-2-1_092081_2022-01-11_final
2022-01-15 08:44:24	ga_ls7e_ard_3-2-1_097071_2022-01-14_final
2022-01-15 08:47:59	ga_ls7e_ard_3-2-1_097080_2022-01-14_final
2022-01-15 10:26:52	ga_ls7e_ard_3-2-1_113080_2022-01-15_final
2022-01-15 10:27:16	ga_ls7e_ard_3-2-1_113081_2022-01-15_final
2022-01-16 09:27:58	ga_ls7e_ard_3-2-1_104072_2022-01-15_final
2022-01-18 09:17:24	ga_ls7e_ard_3-2-1_102077_2022-01-17_final
2022-01-21 09:49:13	ga_ls7e_ard_3-2-1_107080_2022-01-21_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-28 09:55:06	ga_ls7e_ard_3-2-1_108081_2022-01-28_final
2022-01-30 09:41:21	ga_ls7e_ard_3-2-1_106078_2022-01-30_final
2022-01-30 09:42:57	ga_ls7e_ard_3-2-1_106082_2022-01-30_final
2022-01-31 08:46:02	ga_ls7e_ard_3-2-1_097079_2022-01-30_final
2022-02-01 09:25:36	ga_ls7e_ard_3-2-1_104070_2022-01-31_final
2022-02-01 09:26:24	ga_ls7e_ard_3-2-1_104072_2022-01-31_final
2022-02-03 09:13:50	ga_ls7e_ard_3-2-1_102072_2022-02-02_final
2022-02-04 08:22:54	ga_ls7e_ard_3-2-1_093084_2022-02-03_final
2022-02-05 09:02:52	ga_ls7e_ard_3-2-1_100076_2022-02-04_final
2022-02-05 09:05:16	ga_ls7e_ard_3-2-1_100082_2022-02-04_final
2022-02-06 08:09:33	ga_ls7e_ard_3-2-1_091082_2022-02-05_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-07 08:52:42	ga_ls7e_ard_3-2-1_098082_2022-02-06_final
2022-02-08 09:34:39	ga_ls7e_ard_3-2-1_105079_2022-02-08_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-11 08:27:10	ga_ls7e_ard_3-2-1_094081_2022-02-10_final
2022-02-11 10:06:03	ga_ls7e_ard_3-2-1_110081_2022-02-11_final
2022-02-11 10:07:14	ga_ls7e_ard_3-2-1_110084_2022-02-11_final
2022-02-14 08:58:09	ga_ls7e_ard_3-2-1_099082_2022-02-13_final
2022-02-14 10:35:26	ga_ls7e_ard_3-2-1_115078_2022-02-14_final
2022-02-15 08:01:14	ga_ls7e_ard_3-2-1_090079_2022-02-14_final
2022-02-15 09:37:43	ga_ls7e_ard_3-2-1_106073_2022-02-15_final
2022-02-15 09:38:06	ga_ls7e_ard_3-2-1_106074_2022-02-15_final
2022-02-21 09:00:51	ga_ls7e_ard_3-2-1_100075_2022-02-20_final
2022-02-27 08:26:00	ga_ls7e_ard_3-2-1_094082_2022-02-26_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-04 10:20:08	ga_ls7e_ard_3-2-1_113075_2022-03-04_final
2022-03-05 09:26:01	ga_ls7e_ard_3-2-1_104079_2022-03-04_final
2022-03-08 08:15:45	ga_ls7e_ard_3-2-1_093074_2022-03-07_final
2022-03-08 08:17:21	ga_ls7e_ard_3-2-1_093078_2022-03-07_final
2022-03-08 08:20:32	ga_ls7e_ard_3-2-1_093086_2022-03-07_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-09 09:00:54	ga_ls7e_ard_3-2-1_100079_2022-03-08_final
2022-03-10 09:40:28	ga_ls7e_ard_3-2-1_107070_2022-03-10_final
2022-03-11 08:47:33	ga_ls7e_ard_3-2-1_098077_2022-03-10_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-19 07:58:54	ga_ls7e_ard_3-2-1_090081_2022-03-18_final
2022-03-22 08:26:43	ga_ls7e_ard_3-2-1_095074_2022-03-21_final
2022-03-26 09:43:18	ga_ls7e_ard_3-2-1_107081_2022-03-26_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