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 10:29:28	ga_ls7e_ard_3-2-0_112074_2021-09-18_final
2021-10-25 09:06:14	ga_ls7e_ard_3-2-0_099075_2021-10-24_final
2021-10-26 09:48:12	ga_ls7e_ard_3-2-0_106072_2021-10-26_final
2021-10-26 09:50:12	ga_ls7e_ard_3-2-0_106077_2021-10-26_final
2021-10-26 09:50:36	ga_ls7e_ard_3-2-0_106078_2021-10-26_final
2021-11-15 09:21:35	ga_ls7e_ard_3-2-1_102072_2021-11-14_final
2021-11-16 10:05:08	ga_ls7e_ard_3-2-1_109073_2021-11-16_final
2021-11-17 09:10:13	ga_ls7e_ard_3-2-1_100075_2021-11-16_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-12-02 10:06:00	ga_ls7e_ard_3-2-1_109079_2021-12-02_final
2021-12-07 08:43:12	ga_ls7e_ard_3-2-1_096074_2021-12-06_final
2021-12-08 09:26:46	ga_ls7e_ard_3-2-1_103075_2021-12-07_final
2021-12-09 08:32:39	ga_ls7e_ard_3-2-1_094079_2021-12-08_final
2021-12-09 08:33:03	ga_ls7e_ard_3-2-1_094080_2021-12-08_final
2021-12-10 09:13:25	ga_ls7e_ard_3-2-1_101073_2021-12-09_final
2021-12-11 09:57:47	ga_ls7e_ard_3-2-1_108076_2021-12-11_final
2021-12-12 09:04:28	ga_ls7e_ard_3-2-1_099082_2021-12-11_final
2021-12-14 08:48:19	ga_ls7e_ard_3-2-1_097073_2021-12-13_final
2021-12-18 08:24:01	ga_ls7e_ard_3-2-1_093075_2021-12-17_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-18 10:01:17	ga_ls7e_ard_3-2-1_109071_2021-12-18_final
2021-12-18 10:01:41	ga_ls7e_ard_3-2-1_109072_2021-12-18_final
2021-12-18 10:03:17	ga_ls7e_ard_3-2-1_109076_2021-12-18_final
2021-12-20 08:15:03	ga_ls7e_ard_3-2-1_091084_2021-12-19_final
2021-12-20 09:53:55	ga_ls7e_ard_3-2-1_107084_2021-12-20_final
2021-12-21 08:54:13	ga_ls7e_ard_3-2-1_098074_2021-12-20_final
2021-12-21 10:33:54	ga_ls7e_ard_3-2-1_114076_2021-12-21_final
2021-12-22 09:35:23	ga_ls7e_ard_3-2-1_105069_2021-12-22_final
2021-12-23 08:42:51	ga_ls7e_ard_3-2-1_096077_2021-12-22_final
2021-12-24 09:24:01	ga_ls7e_ard_3-2-1_103072_2021-12-23_final
2021-12-24 09:27:13	ga_ls7e_ard_3-2-1_103080_2021-12-23_final
2021-12-25 08:31:06	ga_ls7e_ard_3-2-1_094079_2021-12-24_final
2021-12-25 10:07:11	ga_ls7e_ard_3-2-1_110072_2021-12-25_final
2021-12-30 10:26:25	ga_ls7e_ard_3-2-1_113075_2021-12-30_final
2021-12-31 09:28:42	ga_ls7e_ard_3-2-1_104070_2021-12-30_final
2022-01-01 08:36:58	ga_ls7e_ard_3-2-1_095080_2021-12-31_final
2022-01-02 09:15:20	ga_ls7e_ard_3-2-1_102068_2022-01-01_final
2022-01-03 08:26:48	ga_ls7e_ard_3-2-1_093086_2022-01-02_final
2022-01-03 08:27:12	ga_ls7e_ard_3-2-1_093087_2022-01-02_final
2022-01-05 08:12:38	ga_ls7e_ard_3-2-1_091082_2022-01-04_final
2022-01-08 08:38:52	ga_ls7e_ard_3-2-1_096071_2022-01-07_final
2022-01-08 08:43:16	ga_ls7e_ard_3-2-1_096082_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 10:05:12	ga_ls7e_ard_3-2-1_110071_2022-01-10_final
2022-01-11 09:10:41	ga_ls7e_ard_3-2-1_101074_2022-01-10_final
2022-01-11 09:11:53	ga_ls7e_ard_3-2-1_101077_2022-01-10_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-15 08:44:24	ga_ls7e_ard_3-2-1_097071_2022-01-14_final
2022-01-15 10:24:28	ga_ls7e_ard_3-2-1_113074_2022-01-15_final
2022-01-16 09:26:22	ga_ls7e_ard_3-2-1_104068_2022-01-15_final
2022-01-18 09:13:49	ga_ls7e_ard_3-2-1_102068_2022-01-17_final
2022-01-18 09:15:48	ga_ls7e_ard_3-2-1_102073_2022-01-17_final
2022-01-18 09:16:36	ga_ls7e_ard_3-2-1_102075_2022-01-17_final
2022-01-22 08:52:18	ga_ls7e_ard_3-2-1_098077_2022-01-21_final
2022-01-28 08:15:50	ga_ls7e_ard_3-2-1_092080_2022-01-27_final
2022-01-31 08:46:02	ga_ls7e_ard_3-2-1_097079_2022-01-30_final
2022-02-02 08:30:41	ga_ls7e_ard_3-2-1_095072_2022-02-01_final
2022-02-02 08:31:29	ga_ls7e_ard_3-2-1_095074_2022-02-01_final
2022-02-04 08:19:43	ga_ls7e_ard_3-2-1_093076_2022-02-03_final
2022-02-04 08:22:06	ga_ls7e_ard_3-2-1_093082_2022-02-03_final
2022-02-04 08:24:30	ga_ls7e_ard_3-2-1_093088_2022-02-03_final
2022-02-06 08:09:33	ga_ls7e_ard_3-2-1_091082_2022-02-05_final
2022-02-07 08:50:18	ga_ls7e_ard_3-2-1_098076_2022-02-06_final
2022-02-07 10:31:11	ga_ls7e_ard_3-2-1_114081_2022-02-07_final
2022-02-17 09:23:34	ga_ls7e_ard_3-2-1_104069_2022-02-16_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-24 09:32:40	ga_ls7e_ard_3-2-1_105078_2022-02-24_final
2022-02-25 08:35:46	ga_ls7e_ard_3-2-1_096075_2022-02-24_final
2022-02-26 09:16:56	ga_ls7e_ard_3-2-1_103070_2022-02-25_final
2022-02-26 09:18:07	ga_ls7e_ard_3-2-1_103073_2022-02-25_final
2022-02-26 09:21:43	ga_ls7e_ard_3-2-1_103082_2022-02-25_final
2022-02-27 08:23:12	ga_ls7e_ard_3-2-1_094075_2022-02-26_final
2022-02-27 08:25:36	ga_ls7e_ard_3-2-1_094081_2022-02-26_final
2022-02-27 10:02:05	ga_ls7e_ard_3-2-1_110075_2022-02-27_final
2022-02-27 10:05:17	ga_ls7e_ard_3-2-1_110083_2022-02-27_final
2022-03-03 09:40:10	ga_ls7e_ard_3-2-1_106083_2022-03-03_final
2022-03-04 08:41:40	ga_ls7e_ard_3-2-1_097076_2022-03-03_final
2022-03-04 08:44:03	ga_ls7e_ard_3-2-1_097082_2022-03-03_final
2022-03-04 10:19:44	ga_ls7e_ard_3-2-1_113074_2022-03-04_final
2022-03-07 09:10:40	ga_ls7e_ard_3-2-1_102072_2022-03-06_final
2022-03-07 09:11:52	ga_ls7e_ard_3-2-1_102075_2022-03-06_final
2022-03-11 08:46:45	ga_ls7e_ard_3-2-1_098075_2022-03-10_final
2022-03-11 08:49:56	ga_ls7e_ard_3-2-1_098083_2022-03-10_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-15 10:03:41	ga_ls7e_ard_3-2-1_110083_2022-03-15_final
2022-03-18 08:51:01	ga_ls7e_ard_3-2-1_099072_2022-03-17_final
2022-03-18 08:53:24	ga_ls7e_ard_3-2-1_099078_2022-03-17_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-20 08:40:04	ga_ls7e_ard_3-2-1_097076_2022-03-19_final
2022-03-20 08:42:27	ga_ls7e_ard_3-2-1_097082_2022-03-19_final
2022-03-22 10:05:36	ga_ls7e_ard_3-2-1_111074_2022-03-22_final
2022-03-23 09:09:05	ga_ls7e_ard_3-2-1_102072_2022-03-22_final
2022-03-27 08:45:35	ga_ls7e_ard_3-2-1_098076_2022-03-26_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-03-31 08:19:17	ga_ls7e_ard_3-2-1_094073_2022-03-30_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_final
2022-04-02 09:48:48	ga_ls7e_ard_3-2-1_108081_2022-04-02_final
2022-04-04 09:32:39	ga_ls7e_ard_3-2-1_106072_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