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
2021-08-28 08:39:29	ga_ls7e_ard_3-2-0_093088_2021-08-27_final
2021-08-30 08:24:33	ga_ls7e_ard_3-2-0_091082_2021-08-29_final
2021-08-31 09:02:32	ga_ls7e_ard_3-2-0_098069_2021-08-30_final
2021-08-31 09:06:32	ga_ls7e_ard_3-2-0_098079_2021-08-30_final
2021-09-05 09:23:50	ga_ls7e_ard_3-2-0_101077_2021-09-04_final
2021-09-15 08:25:09	ga_ls7e_ard_3-2-0_091087_2021-09-14_final
2021-09-16 10:43:36	ga_ls7e_ard_3-2-0_114078_2021-09-16_final
2021-09-26 09:42:06	ga_ls7e_ard_3-2-0_104081_2021-09-26_final
2021-09-27 08:42:48	ga_ls7e_ard_3-2-0_095072_2021-09-26_final
2021-09-28 09:24:22	ga_ls7e_ard_3-2-0_102068_2021-09-27_final
2021-10-01 09:57:48	ga_ls7e_ard_3-2-0_107075_2021-10-01_final
2021-10-02 09:02:54	ga_ls7e_ard_3-2-0_098077_2021-10-01_final
2021-10-07 09:20:12	ga_ls7e_ard_3-2-0_101075_2021-10-06_final
2021-10-07 09:23:24	ga_ls7e_ard_3-2-0_101083_2021-10-06_final
2021-10-09 10:46:57	ga_ls7e_ard_3-2-0_115076_2021-10-09_final
2021-10-11 08:52:44	ga_ls7e_ard_3-2-0_097069_2021-10-10_final
2021-10-13 10:19:53	ga_ls7e_ard_3-2-0_111071_2021-10-13_final
2021-10-18 09:02:41	ga_ls7e_ard_3-2-0_098080_2021-10-17_final
2021-10-19 09:43:51	ga_ls7e_ard_3-2-0_105075_2021-10-19_final
2021-10-20 08:44:57	ga_ls7e_ard_3-2-0_096067_2021-10-19_final
2021-10-22 10:14:53	ga_ls7e_ard_3-2-0_110076_2021-10-22_final
2021-10-22 10:17:40	ga_ls7e_ard_3-2-0_110083_2021-10-22_final
2021-10-23 09:21:58	ga_ls7e_ard_3-2-0_101083_2021-10-22_final
2021-10-25 10:45:06	ga_ls7e_ard_3-2-0_115075_2021-10-25_final
2021-10-27 10:32:10	ga_ls7e_ard_3-2-0_113074_2021-10-27_final
2021-10-29 10:20:01	ga_ls7e_ard_3-2-0_111075_2021-10-29_final
2021-11-03 10:38:05	ga_ls7e_ard_3-2-0_114075_2021-11-03_final
2021-11-05 10:28:20	ga_ls7e_ard_3-2-0_112082_2021-11-05_final
2021-11-07 08:38:06	ga_ls7e_ard_3-2-0_094085_2021-11-06_final
2021-11-07 10:11:24	ga_ls7e_ard_3-2-0_110071_2021-11-07_final
2021-11-07 10:16:11	ga_ls7e_ard_3-2-0_110083_2021-11-07_final
2021-11-09 08:24:21	ga_ls7e_ard_3-2-0_092082_2021-11-08_final
2021-11-10 09:06:43	ga_ls7e_ard_3-2-0_099080_2021-11-09_final
2021-11-11 08:13:00	ga_ls7e_ard_3-2-0_090085_2021-11-10_final
2021-11-11 09:47:29	ga_ls7e_ard_3-2-0_106074_2021-11-11_final
2021-11-11 09:48:41	ga_ls7e_ard_3-2-0_106077_2021-11-11_final
2021-11-14 10:18:29	ga_ls7e_ard_3-2-1_111075_2021-11-14_final
2021-11-15 09:19:59	ga_ls7e_ard_3-2-1_102068_2021-11-14_final
2021-11-19 08:59:39	ga_ls7e_ard_3-2-1_098080_2021-11-18_final
2021-11-26 09:05:34	ga_ls7e_ard_3-2-1_099081_2021-11-25_final
2021-11-28 08:51:49	ga_ls7e_ard_3-2-1_097078_2021-11-27_final
2021-11-28 08:52:13	ga_ls7e_ard_3-2-1_097079_2021-11-27_final
2021-11-28 10:29:30	ga_ls7e_ard_3-2-1_113075_2021-11-28_final
2021-11-28 10:32:42	ga_ls7e_ard_3-2-1_113083_2021-11-28_final
2021-12-03 09:12:17	ga_ls7e_ard_3-2-1_100084_2021-12-02_final
2021-12-04 09:50:16	ga_ls7e_ard_3-2-1_107071_2021-12-04_final
2021-12-05 08:54:33	ga_ls7e_ard_3-2-1_098071_2021-12-04_final
2021-12-05 10:35:50	ga_ls7e_ard_3-2-1_114077_2021-12-05_final
2021-12-08 09:24:22	ga_ls7e_ard_3-2-1_103069_2021-12-07_final
2021-12-11 09:56:11	ga_ls7e_ard_3-2-1_108072_2021-12-11_final
2021-12-14 08:50:19	ga_ls7e_ard_3-2-1_097078_2021-12-13_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2021-12-24 09:26:25	ga_ls7e_ard_3-2-1_103078_2021-12-23_final
2021-12-25 10:06:47	ga_ls7e_ard_3-2-1_110071_2021-12-25_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-02 09:16:32	ga_ls7e_ard_3-2-1_102071_2022-01-01_final
2022-01-06 08:54:36	ga_ls7e_ard_3-2-1_098079_2022-01-05_final
2022-01-06 10:33:53	ga_ls7e_ard_3-2-1_114080_2022-01-06_final
2022-01-07 09:33:47	ga_ls7e_ard_3-2-1_105069_2022-01-07_final
2022-01-07 09:36:11	ga_ls7e_ard_3-2-1_105075_2022-01-07_final
2022-01-08 08:38:52	ga_ls7e_ard_3-2-1_096071_2022-01-07_final
2022-01-10 10:07:12	ga_ls7e_ard_3-2-1_110076_2022-01-10_final
2022-01-12 09:52:15	ga_ls7e_ard_3-2-1_108070_2022-01-12_final
2022-01-16 09:26:46	ga_ls7e_ard_3-2-1_104069_2022-01-15_final
2022-01-19 09:58:58	ga_ls7e_ard_3-2-1_109073_2022-01-19_final
2022-01-23 07:57:47	ga_ls7e_ard_3-2-1_089080_2022-01-22_final
2022-01-23 07:58:11	ga_ls7e_ard_3-2-1_089081_2022-01-22_final
2022-01-23 07:58:59	ga_ls7e_ard_3-2-1_089083_2022-01-22_final
2022-01-23 09:35:04	ga_ls7e_ard_3-2-1_105076_2022-01-23_final
2022-01-24 08:40:56	ga_ls7e_ard_3-2-1_096080_2022-01-23_final
2022-01-26 08:26:23	ga_ls7e_ard_3-2-1_094075_2022-01-25_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-30 09:40:57	ga_ls7e_ard_3-2-1_106077_2022-01-30_final
2022-01-31 10:25:19	ga_ls7e_ard_3-2-1_113080_2022-01-31_final
2022-01-31 10:26:30	ga_ls7e_ard_3-2-1_113083_2022-01-31_final
2022-02-06 08:08:45	ga_ls7e_ard_3-2-1_091080_2022-02-05_final
2022-02-08 07:57:47	ga_ls7e_ard_3-2-1_089084_2022-02-07_final
2022-02-10 09:17:42	ga_ls7e_ard_3-2-1_103068_2022-02-09_final
2022-02-14 08:54:09	ga_ls7e_ard_3-2-1_099072_2022-02-13_final
2022-02-16 10:24:51	ga_ls7e_ard_3-2-1_113083_2022-02-16_final
2022-02-19 09:11:25	ga_ls7e_ard_3-2-1_102070_2022-02-18_final
2022-02-19 09:12:13	ga_ls7e_ard_3-2-1_102072_2022-02-18_final
2022-02-22 08:08:44	ga_ls7e_ard_3-2-1_091084_2022-02-21_final
2022-02-22 09:47:13	ga_ls7e_ard_3-2-1_107083_2022-02-22_final
2022-02-22 09:47:37	ga_ls7e_ard_3-2-1_107084_2022-02-22_final
2022-02-23 10:28:47	ga_ls7e_ard_3-2-1_114079_2022-02-23_final
2022-02-24 09:31:04	ga_ls7e_ard_3-2-1_105074_2022-02-24_final
2022-02-25 10:17:26	ga_ls7e_ard_3-2-1_112082_2022-02-25_final
2022-03-02 10:32:18	ga_ls7e_ard_3-2-1_115074_2022-03-02_final
2022-03-02 10:32:42	ga_ls7e_ard_3-2-1_115075_2022-03-02_final
2022-03-03 08:03:17	ga_ls7e_ard_3-2-1_090088_2022-03-02_final
2022-03-08 08:20:08	ga_ls7e_ard_3-2-1_093085_2022-03-07_final
2022-03-10 08:04:23	ga_ls7e_ard_3-2-1_091077_2022-03-09_final
2022-03-10 08:09:11	ga_ls7e_ard_3-2-1_091089_2022-03-09_final
2022-03-12 09:29:54	ga_ls7e_ard_3-2-1_105075_2022-03-11_final
2022-03-18 10:31:53	ga_ls7e_ard_3-2-1_115077_2022-03-18_final
2022-03-19 08:01:41	ga_ls7e_ard_3-2-1_090088_2022-03-18_final
2022-03-25 08:56:32	ga_ls7e_ard_3-2-1_100072_2022-03-24_final
2022-03-25 09:01:20	ga_ls7e_ard_3-2-1_100084_2022-03-24_final
2022-03-29 10:15:07	ga_ls7e_ard_3-2-1_112084_2022-03-29_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