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
2021-08-24 10:39:50	ga_ls7e_ard_3-2-0_113079_2021-08-24_final
2021-08-26 08:46:26	ga_ls7e_ard_3-2-0_095074_2021-08-25_final
2021-08-27 09:30:48	ga_ls7e_ard_3-2-0_102077_2021-08-27_final
2021-08-29 09:17:04	ga_ls7e_ard_3-2-0_100074_2021-08-28_final
2021-08-29 09:17:28	ga_ls7e_ard_3-2-0_100075_2021-08-28_final
2021-08-29 09:17:52	ga_ls7e_ard_3-2-0_100076_2021-08-28_final
2021-08-30 08:23:22	ga_ls7e_ard_3-2-0_091079_2021-08-29_final
2021-09-09 10:38:51	ga_ls7e_ard_3-2-0_113080_2021-09-09_final
2021-09-18 10:32:40	ga_ls7e_ard_3-2-0_112082_2021-09-18_final
2021-09-20 08:38:27	ga_ls7e_ard_3-2-0_094075_2021-09-19_final
2021-09-20 10:19:43	ga_ls7e_ard_3-2-0_110081_2021-09-20_final
2021-09-22 10:06:23	ga_ls7e_ard_3-2-0_108079_2021-09-22_final
2021-09-25 08:58:56	ga_ls7e_ard_3-2-0_097081_2021-09-24_final
2021-09-25 10:39:01	ga_ls7e_ard_3-2-0_113084_2021-09-25_final
2021-09-27 08:46:00	ga_ls7e_ard_3-2-0_095080_2021-09-26_final
2021-09-28 09:28:46	ga_ls7e_ard_3-2-0_102079_2021-09-27_final
2021-09-29 08:36:39	ga_ls7e_ard_3-2-0_093088_2021-09-28_final
2021-10-03 09:43:17	ga_ls7e_ard_3-2-0_105070_2021-10-03_final
2021-10-04 08:47:58	ga_ls7e_ard_3-2-0_096071_2021-10-03_final
2021-10-04 10:28:27	ga_ls7e_ard_3-2-0_112075_2021-10-04_final
2021-10-06 10:17:54	ga_ls7e_ard_3-2-0_110080_2021-10-06_final
2021-10-11 08:57:31	ga_ls7e_ard_3-2-0_097081_2021-10-10_final
2021-10-13 08:44:59	ga_ls7e_ard_3-2-0_095081_2021-10-12_final
2021-10-13 08:45:23	ga_ls7e_ard_3-2-0_095082_2021-10-12_final
2021-10-14 09:25:46	ga_ls7e_ard_3-2-0_102075_2021-10-13_final
2021-10-15 08:31:39	ga_ls7e_ard_3-2-0_093079_2021-10-14_final
2021-10-17 09:57:59	ga_ls7e_ard_3-2-0_107079_2021-10-17_final
2021-10-18 08:59:53	ga_ls7e_ard_3-2-0_098073_2021-10-17_final
2021-10-19 09:45:27	ga_ls7e_ard_3-2-0_105079_2021-10-19_final
2021-10-20 10:27:25	ga_ls7e_ard_3-2-0_112076_2021-10-20_final
2021-10-22 08:38:48	ga_ls7e_ard_3-2-0_094083_2021-10-21_final
2021-10-22 10:16:05	ga_ls7e_ard_3-2-0_110079_2021-10-22_final
2021-10-24 08:24:39	ga_ls7e_ard_3-2-0_092079_2021-10-23_final
2021-10-25 09:08:37	ga_ls7e_ard_3-2-0_099081_2021-10-24_final
2021-10-27 10:33:46	ga_ls7e_ard_3-2-0_113078_2021-10-27_final
2021-10-28 09:37:15	ga_ls7e_ard_3-2-0_104076_2021-10-28_final
2021-10-28 09:38:03	ga_ls7e_ard_3-2-0_104078_2021-10-28_final
2021-11-05 10:25:56	ga_ls7e_ard_3-2-0_112076_2021-11-05_final
2021-11-08 09:17:16	ga_ls7e_ard_3-2-0_101075_2021-11-07_final
2021-11-09 10:00:50	ga_ls7e_ard_3-2-0_108076_2021-11-09_final
2021-11-14 08:41:13	ga_ls7e_ard_3-2-1_095079_2021-11-13_final
2021-11-16 08:29:51	ga_ls7e_ard_3-2-1_093082_2021-11-15_final
2021-11-20 09:39:14	ga_ls7e_ard_3-2-1_105071_2021-11-20_final
2021-11-23 08:32:33	ga_ls7e_ard_3-2-1_094075_2021-11-22_final
2021-11-29 09:36:11	ga_ls7e_ard_3-2-1_104081_2021-11-29_final
2021-12-01 09:22:26	ga_ls7e_ard_3-2-1_102078_2021-11-30_final
2021-12-05 08:56:33	ga_ls7e_ard_3-2-1_098076_2021-12-04_final
2021-12-07 10:24:05	ga_ls7e_ard_3-2-1_112079_2021-12-07_final
2021-12-11 09:59:22	ga_ls7e_ard_3-2-1_108080_2021-12-11_final
2021-12-13 09:47:13	ga_ls7e_ard_3-2-1_106081_2021-12-13_final
2021-12-16 08:36:58	ga_ls7e_ard_3-2-1_095076_2021-12-15_final
2021-12-16 10:17:50	ga_ls7e_ard_3-2-1_111081_2021-12-16_final
2021-12-18 10:04:29	ga_ls7e_ard_3-2-1_109079_2021-12-18_final
2021-12-23 08:41:16	ga_ls7e_ard_3-2-1_096073_2021-12-22_final
2021-12-23 08:45:15	ga_ls7e_ard_3-2-1_096083_2021-12-22_final
2021-12-30 08:47:32	ga_ls7e_ard_3-2-1_097075_2021-12-29_final
2022-01-01 10:14:15	ga_ls7e_ard_3-2-1_111076_2022-01-01_final
2022-01-01 10:17:26	ga_ls7e_ard_3-2-1_111084_2022-01-01_final
2022-01-02 09:18:32	ga_ls7e_ard_3-2-1_102076_2022-01-01_final
2022-01-03 08:24:00	ga_ls7e_ard_3-2-1_093079_2022-01-02_final
2022-01-06 08:53:01	ga_ls7e_ard_3-2-1_098075_2022-01-05_final
2022-01-08 08:42:28	ga_ls7e_ard_3-2-1_096080_2022-01-07_final
2022-01-08 10:21:20	ga_ls7e_ard_3-2-1_112080_2022-01-08_final
2022-01-10 08:29:55	ga_ls7e_ard_3-2-1_094080_2022-01-09_final
2022-01-14 09:43:18	ga_ls7e_ard_3-2-1_106079_2022-01-14_final
2022-01-17 08:35:02	ga_ls7e_ard_3-2-1_095079_2022-01-16_final
2022-01-18 09:15:25	ga_ls7e_ard_3-2-1_102072_2022-01-17_final
2022-01-21 09:48:01	ga_ls7e_ard_3-2-1_107077_2022-01-21_final
2022-01-21 09:48:49	ga_ls7e_ard_3-2-1_107079_2022-01-21_final
2022-01-24 10:19:49	ga_ls7e_ard_3-2-1_112080_2022-01-24_final
2022-01-27 09:09:57	ga_ls7e_ard_3-2-1_101076_2022-01-26_final
2022-02-02 08:32:40	ga_ls7e_ard_3-2-1_095077_2022-02-01_final
2022-02-07 08:50:18	ga_ls7e_ard_3-2-1_098076_2022-02-06_final
2022-02-08 09:34:15	ga_ls7e_ard_3-2-1_105078_2022-02-08_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-09 10:18:37	ga_ls7e_ard_3-2-1_112081_2022-02-09_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-16 08:43:11	ga_ls7e_ard_3-2-1_097076_2022-02-15_final
2022-02-18 10:10:19	ga_ls7e_ard_3-2-1_111078_2022-02-18_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-22 09:45:37	ga_ls7e_ard_3-2-1_107079_2022-02-22_final
2022-02-22 09:46:49	ga_ls7e_ard_3-2-1_107082_2022-02-22_final
2022-02-23 08:50:42	ga_ls7e_ard_3-2-1_098081_2022-02-22_final
2022-02-24 09:32:40	ga_ls7e_ard_3-2-1_105078_2022-02-24_final
2022-03-06 08:30:18	ga_ls7e_ard_3-2-1_095079_2022-03-05_final
2022-03-06 10:04:47	ga_ls7e_ard_3-2-1_111068_2022-03-06_final
2022-03-07 09:11:28	ga_ls7e_ard_3-2-1_102074_2022-03-06_final
2022-03-10 09:43:16	ga_ls7e_ard_3-2-1_107077_2022-03-10_final
2022-03-13 10:15:03	ga_ls7e_ard_3-2-1_112080_2022-03-13_final
2022-03-15 08:22:25	ga_ls7e_ard_3-2-1_094077_2022-03-14_final
2022-03-19 07:58:30	ga_ls7e_ard_3-2-1_090080_2022-03-18_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-27 08:44:24	ga_ls7e_ard_3-2-1_098073_2022-03-26_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-03-31 08:21:41	ga_ls7e_ard_3-2-1_094079_2022-03-30_final
2022-04-01 09:02:03	ga_ls7e_ard_3-2-1_101072_2022-03-31_final
2022-04-02 08:09:08	ga_ls7e_ard_3-2-1_092079_2022-04-01_final
2022-04-03 08:50:41	ga_ls7e_ard_3-2-1_099075_2022-04-02_final
2022-04-06 09:18:54	ga_ls7e_ard_3-2-1_104069_2022-04-05_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