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 10:32:40	ga_ls7e_ard_3-2-0_112082_2021-09-18_final
2021-09-20 08:42:50	ga_ls7e_ard_3-2-0_094086_2021-09-19_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-11-08 09:18:04	ga_ls7e_ard_3-2-0_101077_2021-11-07_final
2021-11-09 08:23:09	ga_ls7e_ard_3-2-0_092079_2021-11-08_final
2021-11-14 10:17:18	ga_ls7e_ard_3-2-1_111072_2021-11-14_final
2021-11-16 08:30:15	ga_ls7e_ard_3-2-1_093083_2021-11-15_final
2021-11-17 09:09:25	ga_ls7e_ard_3-2-1_100073_2021-11-16_final
2021-11-18 08:18:54	ga_ls7e_ard_3-2-1_091086_2021-11-17_final
2021-11-19 08:56:52	ga_ls7e_ard_3-2-1_098073_2021-11-18_final
2021-11-23 08:33:21	ga_ls7e_ard_3-2-1_094077_2021-11-22_final
2021-12-02 10:06:24	ga_ls7e_ard_3-2-1_109080_2021-12-02_final
2021-12-05 08:53:21	ga_ls7e_ard_3-2-1_098068_2021-12-04_final
2021-12-07 08:42:00	ga_ls7e_ard_3-2-1_096071_2021-12-06_final
2021-12-07 08:42:48	ga_ls7e_ard_3-2-1_096073_2021-12-06_final
2021-12-07 08:45:12	ga_ls7e_ard_3-2-1_096079_2021-12-06_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-22 09:39:46	ga_ls7e_ard_3-2-1_105080_2021-12-22_final
2022-01-05 09:50:19	ga_ls7e_ard_3-2-1_107079_2022-01-05_final
2022-01-05 09:51:55	ga_ls7e_ard_3-2-1_107083_2022-01-05_final
2022-01-07 09:34:35	ga_ls7e_ard_3-2-1_105071_2022-01-07_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-09 09:25:38	ga_ls7e_ard_3-2-1_103080_2022-01-08_final
2022-01-10 10:06:48	ga_ls7e_ard_3-2-1_110075_2022-01-10_final
2022-01-11 09:10:41	ga_ls7e_ard_3-2-1_101074_2022-01-10_final
2022-01-11 09:11:05	ga_ls7e_ard_3-2-1_101075_2022-01-10_final
2022-01-11 09:12:41	ga_ls7e_ard_3-2-1_101079_2022-01-10_final
2022-01-12 09:53:27	ga_ls7e_ard_3-2-1_108073_2022-01-12_final
2022-01-13 08:58:56	ga_ls7e_ard_3-2-1_099076_2022-01-12_final
2022-01-14 08:05:13	ga_ls7e_ard_3-2-1_090081_2022-01-13_final
2022-01-15 08:48:23	ga_ls7e_ard_3-2-1_097081_2022-01-14_final
2022-01-15 10:27:16	ga_ls7e_ard_3-2-1_113081_2022-01-15_final
2022-01-15 10:27:40	ga_ls7e_ard_3-2-1_113082_2022-01-15_final
2022-01-19 08:24:53	ga_ls7e_ard_3-2-1_093085_2022-01-18_final
2022-01-21 08:13:08	ga_ls7e_ard_3-2-1_091087_2022-01-20_final
2022-01-22 08:51:06	ga_ls7e_ard_3-2-1_098074_2022-01-21_final
2022-01-23 09:36:15	ga_ls7e_ard_3-2-1_105079_2022-01-23_final
2022-01-24 08:40:09	ga_ls7e_ard_3-2-1_096078_2022-01-23_final
2022-01-24 08:42:56	ga_ls7e_ard_3-2-1_096085_2022-01-23_final
2022-01-26 08:28:47	ga_ls7e_ard_3-2-1_094081_2022-01-25_final
2022-01-26 08:30:23	ga_ls7e_ard_3-2-1_094085_2022-01-25_final
2022-02-02 08:34:40	ga_ls7e_ard_3-2-1_095082_2022-02-01_final
2022-02-02 10:13:33	ga_ls7e_ard_3-2-1_111082_2022-02-02_final
2022-02-03 09:12:38	ga_ls7e_ard_3-2-1_102069_2022-02-02_final
2022-02-06 08:07:09	ga_ls7e_ard_3-2-1_091076_2022-02-05_final
2022-02-06 08:08:21	ga_ls7e_ard_3-2-1_091079_2022-02-05_final
2022-02-06 08:09:33	ga_ls7e_ard_3-2-1_091082_2022-02-05_final
2022-02-07 08:53:06	ga_ls7e_ard_3-2-1_098083_2022-02-06_final
2022-02-08 09:31:52	ga_ls7e_ard_3-2-1_105072_2022-02-08_final
2022-02-09 08:40:56	ga_ls7e_ard_3-2-1_096084_2022-02-08_final
2022-02-11 10:03:15	ga_ls7e_ard_3-2-1_110074_2022-02-11_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-15 09:39:18	ga_ls7e_ard_3-2-1_106077_2022-02-15_final
2022-02-16 08:41:35	ga_ls7e_ard_3-2-1_097072_2022-02-15_final
2022-02-20 08:22:29	ga_ls7e_ard_3-2-1_093087_2022-02-19_final
2022-02-23 08:47:31	ga_ls7e_ard_3-2-1_098073_2022-02-22_final
2022-02-23 08:51:30	ga_ls7e_ard_3-2-1_098083_2022-02-22_final
2022-02-24 09:30:17	ga_ls7e_ard_3-2-1_105072_2022-02-24_final
2022-02-26 09:19:43	ga_ls7e_ard_3-2-1_103077_2022-02-25_final
2022-02-27 10:01:41	ga_ls7e_ard_3-2-1_110074_2022-02-27_final
2022-02-27 10:02:29	ga_ls7e_ard_3-2-1_110076_2022-02-27_final
2022-02-27 10:04:53	ga_ls7e_ard_3-2-1_110082_2022-02-27_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-02-28 09:07:58	ga_ls7e_ard_3-2-1_101079_2022-02-27_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-04 08:42:04	ga_ls7e_ard_3-2-1_097077_2022-03-03_final
2022-03-04 08:43:39	ga_ls7e_ard_3-2-1_097081_2022-03-03_final
2022-03-04 10:20:56	ga_ls7e_ard_3-2-1_113077_2022-03-04_final
2022-03-04 10:22:32	ga_ls7e_ard_3-2-1_113081_2022-03-04_final
2022-03-06 08:27:54	ga_ls7e_ard_3-2-1_095073_2022-03-05_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
2022-03-09 08:58:30	ga_ls7e_ard_3-2-1_100073_2022-03-08_final
2022-03-10 09:40:52	ga_ls7e_ard_3-2-1_107071_2022-03-10_final
2022-03-10 09:42:52	ga_ls7e_ard_3-2-1_107076_2022-03-10_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-13 08:34:11	ga_ls7e_ard_3-2-1_096075_2022-03-12_final
2022-03-13 10:16:15	ga_ls7e_ard_3-2-1_112083_2022-03-13_final
2022-03-15 08:22:01	ga_ls7e_ard_3-2-1_094076_2022-03-14_final
2022-03-17 09:47:32	ga_ls7e_ard_3-2-1_108074_2022-03-17_final
2022-03-18 08:52:36	ga_ls7e_ard_3-2-1_099076_2022-03-17_final
2022-03-19 07:58:06	ga_ls7e_ard_3-2-1_090079_2022-03-18_final
2022-03-20 08:41:40	ga_ls7e_ard_3-2-1_097080_2022-03-19_final
2022-03-20 08:43:15	ga_ls7e_ard_3-2-1_097084_2022-03-19_final
2022-03-20 10:19:20	ga_ls7e_ard_3-2-1_113077_2022-03-20_final
2022-03-20 10:20:08	ga_ls7e_ard_3-2-1_113079_2022-03-20_final
2022-03-21 09:21:14	ga_ls7e_ard_3-2-1_104071_2022-03-20_final
2022-03-22 08:30:43	ga_ls7e_ard_3-2-1_095084_2022-03-21_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-27 08:44:24	ga_ls7e_ard_3-2-1_098073_2022-03-26_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-03-29 08:35:50	ga_ls7e_ard_3-2-1_096083_2022-03-28_final
2022-03-30 09:17:00	ga_ls7e_ard_3-2-1_103078_2022-03-29_final
2022-03-31 10:00:34	ga_ls7e_ard_3-2-1_110079_2022-03-31_final
2022-04-01 09:06:03	ga_ls7e_ard_3-2-1_101082_2022-03-31_final
2022-04-02 09:44:01	ga_ls7e_ard_3-2-1_108069_2022-04-02_final
2022-04-02 09:46:01	ga_ls7e_ard_3-2-1_108074_2022-04-02_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_2022-04-04_final
2022-04-05 08:40:31	ga_ls7e_ard_3-2-1_097081_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