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 08:55:23	ga_ls7e_ard_3-2-0_096086_2021-09-17_final
2021-09-20 10:15:44	ga_ls7e_ard_3-2-0_110071_2021-09-20_final
2021-10-09 09:06:04	ga_ls7e_ard_3-2-0_099071_2021-10-08_final
2021-10-09 09:08:28	ga_ls7e_ard_3-2-0_099077_2021-10-08_final
2021-10-09 10:46:09	ga_ls7e_ard_3-2-0_115074_2021-10-09_final
2021-10-09 10:47:45	ga_ls7e_ard_3-2-0_115078_2021-10-09_final
2021-10-10 09:53:14	ga_ls7e_ard_3-2-0_106081_2021-10-10_final
2021-10-13 08:46:35	ga_ls7e_ard_3-2-0_095085_2021-10-12_final
2021-10-13 10:21:04	ga_ls7e_ard_3-2-0_111074_2021-10-13_final
2021-10-13 10:24:40	ga_ls7e_ard_3-2-0_111083_2021-10-13_final
2021-10-15 08:34:27	ga_ls7e_ard_3-2-0_093086_2021-10-14_final
2021-10-25 09:03:26	ga_ls7e_ard_3-2-0_099068_2021-10-24_final
2021-10-25 10:44:42	ga_ls7e_ard_3-2-0_115074_2021-10-25_final
2021-10-26 09:51:23	ga_ls7e_ard_3-2-0_106080_2021-10-26_final
2021-10-26 09:51:47	ga_ls7e_ard_3-2-0_106081_2021-10-26_final
2021-10-29 10:16:50	ga_ls7e_ard_3-2-0_111067_2021-10-29_final
2021-10-30 09:21:31	ga_ls7e_ard_3-2-0_102068_2021-10-29_final
2021-10-30 09:23:54	ga_ls7e_ard_3-2-0_102074_2021-10-29_final
2021-10-30 09:27:06	ga_ls7e_ard_3-2-0_102082_2021-10-29_final
2021-11-02 08:18:27	ga_ls7e_ard_3-2-0_091081_2021-11-01_final
2021-11-03 08:56:49	ga_ls7e_ard_3-2-0_098069_2021-11-02_final
2021-11-05 08:50:15	ga_ls7e_ard_3-2-0_096084_2021-11-04_final
2021-11-05 08:51:03	ga_ls7e_ard_3-2-0_096086_2021-11-04_final
2021-11-18 08:18:06	ga_ls7e_ard_3-2-1_091084_2021-11-17_final
2021-11-21 08:43:07	ga_ls7e_ard_3-2-1_096070_2021-11-20_final
2021-11-21 08:43:31	ga_ls7e_ard_3-2-1_096071_2021-11-20_final
2021-11-23 10:11:01	ga_ls7e_ard_3-2-1_110074_2021-11-23_final
2021-11-25 09:56:53	ga_ls7e_ard_3-2-1_108070_2021-11-25_final
2021-11-28 08:54:13	ga_ls7e_ard_3-2-1_097084_2021-11-27_final
2021-11-29 09:31:00	ga_ls7e_ard_3-2-1_104068_2021-11-29_final
2021-12-02 10:07:36	ga_ls7e_ard_3-2-1_109083_2021-12-02_final
2021-12-03 09:09:54	ga_ls7e_ard_3-2-1_100078_2021-12-02_final
2021-12-06 09:41:19	ga_ls7e_ard_3-2-1_105080_2021-12-06_final
2021-12-08 09:26:22	ga_ls7e_ard_3-2-1_103074_2021-12-07_final
2021-12-10 09:17:24	ga_ls7e_ard_3-2-1_101083_2021-12-09_final
2021-12-11 09:55:47	ga_ls7e_ard_3-2-1_108071_2021-12-11_final
2021-12-18 08:28:48	ga_ls7e_ard_3-2-1_093087_2021-12-17_final
2021-12-20 08:11:51	ga_ls7e_ard_3-2-1_091076_2021-12-19_final
2021-12-20 08:15:27	ga_ls7e_ard_3-2-1_091085_2021-12-19_final
2021-12-22 08:01:18	ga_ls7e_ard_3-2-1_089081_2021-12-21_final
2021-12-25 10:08:23	ga_ls7e_ard_3-2-1_110075_2021-12-25_final
2021-12-27 08:18:56	ga_ls7e_ard_3-2-1_092080_2021-12-26_final
2021-12-27 09:53:49	ga_ls7e_ard_3-2-1_108070_2021-12-27_final
2021-12-27 09:55:01	ga_ls7e_ard_3-2-1_108073_2021-12-27_final
2021-12-28 09:02:06	ga_ls7e_ard_3-2-1_099080_2021-12-27_final
2021-12-30 08:46:44	ga_ls7e_ard_3-2-1_097073_2021-12-29_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2021-12-30 08:51:32	ga_ls7e_ard_3-2-1_097085_2021-12-29_final
2021-12-30 10:29:12	ga_ls7e_ard_3-2-1_113082_2021-12-30_final
2022-01-07 09:34:11	ga_ls7e_ard_3-2-1_105070_2022-01-07_final
2022-01-11 09:09:53	ga_ls7e_ard_3-2-1_101072_2022-01-10_final
2022-01-11 09:10:17	ga_ls7e_ard_3-2-1_101073_2022-01-10_final
2022-01-13 09:02:08	ga_ls7e_ard_3-2-1_099084_2022-01-12_final
2022-01-14 08:08:49	ga_ls7e_ard_3-2-1_090090_2022-01-13_final
2022-01-19 08:25:41	ga_ls7e_ard_3-2-1_093087_2022-01-18_final
2022-01-19 09:57:46	ga_ls7e_ard_3-2-1_109070_2022-01-19_final
2022-01-19 10:00:10	ga_ls7e_ard_3-2-1_109076_2022-01-19_final
2022-01-21 08:13:32	ga_ls7e_ard_3-2-1_091088_2022-01-20_final
2022-01-21 08:14:20	ga_ls7e_ard_3-2-1_091090_2022-01-20_final
2022-01-22 08:52:18	ga_ls7e_ard_3-2-1_098077_2022-01-21_final
2022-01-23 09:32:40	ga_ls7e_ard_3-2-1_105070_2022-01-23_final
2022-01-26 08:26:23	ga_ls7e_ard_3-2-1_094075_2022-01-25_final
2022-01-26 08:26:47	ga_ls7e_ard_3-2-1_094076_2022-01-25_final
2022-01-26 08:31:11	ga_ls7e_ard_3-2-1_094087_2022-01-25_final
2022-01-28 08:17:26	ga_ls7e_ard_3-2-1_092084_2022-01-27_final
2022-01-28 09:55:54	ga_ls7e_ard_3-2-1_108083_2022-01-28_final
2022-01-30 08:06:52	ga_ls7e_ard_3-2-1_090089_2022-01-29_final
2022-01-31 08:48:26	ga_ls7e_ard_3-2-1_097085_2022-01-30_final
2022-02-02 08:34:40	ga_ls7e_ard_3-2-1_095082_2022-02-01_final
2022-02-06 08:12:44	ga_ls7e_ard_3-2-1_091090_2022-02-05_final
2022-02-06 09:46:02	ga_ls7e_ard_3-2-1_107076_2022-02-06_final
2022-02-07 08:46:43	ga_ls7e_ard_3-2-1_098067_2022-02-06_final
2022-02-09 10:15:49	ga_ls7e_ard_3-2-1_112074_2022-02-09_final
2022-02-11 10:03:15	ga_ls7e_ard_3-2-1_110074_2022-02-11_final
2022-02-12 09:08:43	ga_ls7e_ard_3-2-1_101077_2022-02-11_final
2022-02-12 09:11:07	ga_ls7e_ard_3-2-1_101083_2022-02-11_final
2022-02-15 08:04:01	ga_ls7e_ard_3-2-1_090086_2022-02-14_final
2022-02-16 08:45:59	ga_ls7e_ard_3-2-1_097083_2022-02-15_final
2022-02-18 10:09:07	ga_ls7e_ard_3-2-1_111075_2022-02-18_final
2022-02-22 08:07:32	ga_ls7e_ard_3-2-1_091081_2022-02-21_final
2022-03-02 10:33:53	ga_ls7e_ard_3-2-1_115078_2022-03-02_final
2022-03-03 08:01:18	ga_ls7e_ard_3-2-1_090083_2022-03-02_final
2022-03-03 09:34:59	ga_ls7e_ard_3-2-1_106070_2022-03-03_final
2022-03-06 08:32:42	ga_ls7e_ard_3-2-1_095085_2022-03-05_final
2022-03-07 09:11:04	ga_ls7e_ard_3-2-1_102073_2022-03-06_final
2022-03-11 08:45:09	ga_ls7e_ard_3-2-1_098071_2022-03-10_final
2022-03-12 07:55:01	ga_ls7e_ard_3-2-1_089085_2022-03-11_final
2022-03-13 10:16:15	ga_ls7e_ard_3-2-1_112083_2022-03-13_final
2022-03-15 10:00:06	ga_ls7e_ard_3-2-1_110074_2022-03-15_final
2022-03-19 09:38:34	ga_ls7e_ard_3-2-1_106083_2022-03-19_final
2022-03-22 08:25:55	ga_ls7e_ard_3-2-1_095072_2022-03-21_final
2022-03-22 10:05:36	ga_ls7e_ard_3-2-1_111074_2022-03-22_final
2022-03-23 09:08:41	ga_ls7e_ard_3-2-1_102071_2022-03-22_final
2022-03-24 08:18:58	ga_ls7e_ard_3-2-1_093086_2022-03-23_final
2022-03-24 09:52:39	ga_ls7e_ard_3-2-1_109073_2022-03-24_final
2022-03-26 09:38:55	ga_ls7e_ard_3-2-1_107070_2022-03-26_final
2022-03-27 10:24:28	ga_ls7e_ard_3-2-1_114076_2022-03-27_final
2022-03-29 10:13:07	ga_ls7e_ard_3-2-1_112079_2022-03-29_final
2022-03-31 09:58:58	ga_ls7e_ard_3-2-1_110075_2022-03-31_final
2022-04-03 10:29:34	ga_ls7e_ard_3-2-1_115075_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