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
2021-03-25 10:04:27	ga_ls7e_ard_3-2-0_105082_2021-03-25_final
2021-07-21 09:12:19	ga_ls7e_ard_3-2-0_099069_2021-07-20_final
2021-07-21 09:17:30	ga_ls7e_ard_3-2-0_099082_2021-07-20_final
2021-07-23 08:59:47	ga_ls7e_ard_3-2-0_097069_2021-07-22_final
2021-07-24 09:48:08	ga_ls7e_ard_3-2-0_104082_2021-07-24_final
2021-07-27 10:14:23	ga_ls7e_ard_3-2-0_109071_2021-07-27_final
2021-07-27 10:18:22	ga_ls7e_ard_3-2-0_109081_2021-07-27_final
2021-07-28 09:19:05	ga_ls7e_ard_3-2-0_100072_2021-07-27_final
2021-07-29 10:01:27	ga_ls7e_ard_3-2-0_107070_2021-07-29_final
2021-08-05 08:32:55	ga_ls7e_ard_3-2-0_092082_2021-08-04_final
2021-08-05 10:07:25	ga_ls7e_ard_3-2-0_108071_2021-08-05_final
2021-08-07 09:54:29	ga_ls7e_ard_3-2-0_106070_2021-08-07_final
2021-08-07 09:56:04	ga_ls7e_ard_3-2-0_106074_2021-08-07_final
2021-08-08 09:04:21	ga_ls7e_ard_3-2-0_097084_2021-08-07_final
2021-08-25 09:39:44	ga_ls7e_ard_3-2-0_104068_2021-08-25_final
2021-08-30 08:26:09	ga_ls7e_ard_3-2-0_091086_2021-08-29_final
2021-08-31 09:08:08	ga_ls7e_ard_3-2-0_098083_2021-08-30_final
2021-09-04 08:39:04	ga_ls7e_ard_3-2-0_094073_2021-09-03_final
2021-09-06 10:04:37	ga_ls7e_ard_3-2-0_108071_2021-09-06_final
2021-09-07 09:08:55	ga_ls7e_ard_3-2-0_099071_2021-09-06_final
2021-09-08 09:51:41	ga_ls7e_ard_3-2-0_106070_2021-09-08_final
2021-09-08 09:52:29	ga_ls7e_ard_3-2-0_106072_2021-09-08_final
2021-09-09 10:36:27	ga_ls7e_ard_3-2-0_113074_2021-09-09_final
2021-09-13 10:12:10	ga_ls7e_ard_3-2-0_109076_2021-09-13_final
2021-09-13 10:15:22	ga_ls7e_ard_3-2-0_109084_2021-09-13_final
2021-09-15 09:57:14	ga_ls7e_ard_3-2-0_107070_2021-09-15_final
2021-09-17 09:43:54	ga_ls7e_ard_3-2-0_105068_2021-09-17_final
2021-10-02 08:59:18	ga_ls7e_ard_3-2-0_098068_2021-10-01_final
2021-10-07 09:23:00	ga_ls7e_ard_3-2-0_101082_2021-10-06_final
2021-10-08 08:28:53	ga_ls7e_ard_3-2-0_092086_2021-10-07_final
2021-10-09 10:46:09	ga_ls7e_ard_3-2-0_115074_2021-10-09_final
2021-10-10 09:49:38	ga_ls7e_ard_3-2-0_106072_2021-10-10_final
2021-10-13 10:21:28	ga_ls7e_ard_3-2-0_111075_2021-10-13_final
2021-10-19 08:06:10	ga_ls7e_ard_3-2-0_089078_2021-10-18_final
2021-10-23 09:21:58	ga_ls7e_ard_3-2-0_101083_2021-10-22_final
2021-10-24 10:00:21	ga_ls7e_ard_3-2-0_108071_2021-10-24_final
2021-10-26 08:14:54	ga_ls7e_ard_3-2-0_090086_2021-10-25_final
2021-10-27 10:35:21	ga_ls7e_ard_3-2-0_113082_2021-10-27_final
2021-11-03 08:56:49	ga_ls7e_ard_3-2-0_098069_2021-11-02_final
2021-11-03 09:01:12	ga_ls7e_ard_3-2-0_098080_2021-11-02_final
2021-11-12 10:33:50	ga_ls7e_ard_3-2-1_113082_2021-11-12_final
2021-11-16 08:27:04	ga_ls7e_ard_3-2-1_093075_2021-11-15_final
2021-11-17 09:10:37	ga_ls7e_ard_3-2-1_100076_2021-11-16_final
2021-11-21 10:24:23	ga_ls7e_ard_3-2-1_112076_2021-11-21_final
2021-11-23 10:11:49	ga_ls7e_ard_3-2-1_110076_2021-11-23_final
2021-11-25 09:56:53	ga_ls7e_ard_3-2-1_108070_2021-11-25_final
2021-11-26 09:03:10	ga_ls7e_ard_3-2-1_099075_2021-11-25_final
2021-11-28 08:49:02	ga_ls7e_ard_3-2-1_097071_2021-11-27_final
2021-11-28 08:54:13	ga_ls7e_ard_3-2-1_097084_2021-11-27_final
2021-11-30 08:42:28	ga_ls7e_ard_3-2-1_095086_2021-11-29_final
2021-12-01 09:18:51	ga_ls7e_ard_3-2-1_102069_2021-11-30_final
2021-12-01 09:22:03	ga_ls7e_ard_3-2-1_102077_2021-11-30_final
2021-12-02 10:04:01	ga_ls7e_ard_3-2-1_109074_2021-12-02_final
2021-12-04 08:17:23	ga_ls7e_ard_3-2-1_091086_2021-12-03_final
2021-12-10 09:12:37	ga_ls7e_ard_3-2-1_101071_2021-12-09_final
2021-12-11 09:56:35	ga_ls7e_ard_3-2-1_108073_2021-12-11_final
2021-12-12 09:00:28	ga_ls7e_ard_3-2-1_099072_2021-12-11_final
2021-12-13 09:42:26	ga_ls7e_ard_3-2-1_106069_2021-12-13_final
2021-12-16 10:19:02	ga_ls7e_ard_3-2-1_111084_2021-12-16_final
2021-12-18 10:01:17	ga_ls7e_ard_3-2-1_109071_2021-12-18_final
2021-12-19 09:10:46	ga_ls7e_ard_3-2-1_100084_2021-12-18_final
2021-12-21 10:33:54	ga_ls7e_ard_3-2-1_114076_2021-12-21_final
2021-12-23 08:40:04	ga_ls7e_ard_3-2-1_096070_2021-12-22_final
2021-12-29 09:41:40	ga_ls7e_ard_3-2-1_106071_2021-12-29_final
2021-12-29 09:44:27	ga_ls7e_ard_3-2-1_106078_2021-12-29_final
2021-12-30 08:45:33	ga_ls7e_ard_3-2-1_097070_2021-12-29_final
2022-01-03 09:59:17	ga_ls7e_ard_3-2-1_109070_2022-01-03_final
2022-01-05 08:13:02	ga_ls7e_ard_3-2-1_091083_2022-01-04_final
2022-01-05 09:48:19	ga_ls7e_ard_3-2-1_107074_2022-01-05_final
2022-01-06 10:32:41	ga_ls7e_ard_3-2-1_114077_2022-01-06_final
2022-01-10 10:10:23	ga_ls7e_ard_3-2-1_110084_2022-01-10_final
2022-01-13 09:02:08	ga_ls7e_ard_3-2-1_099084_2022-01-12_final
2022-01-13 10:38:37	ga_ls7e_ard_3-2-1_115078_2022-01-13_final
2022-01-15 08:49:35	ga_ls7e_ard_3-2-1_097084_2022-01-14_final
2022-01-17 08:36:38	ga_ls7e_ard_3-2-1_095083_2022-01-16_final
2022-01-17 08:37:26	ga_ls7e_ard_3-2-1_095085_2022-01-16_final
2022-01-19 08:22:05	ga_ls7e_ard_3-2-1_093078_2022-01-18_final
2022-01-22 10:32:22	ga_ls7e_ard_3-2-1_114080_2022-01-22_final
2022-01-23 09:33:04	ga_ls7e_ard_3-2-1_105071_2022-01-23_final
2022-01-28 09:56:18	ga_ls7e_ard_3-2-1_108084_2022-01-28_final
2022-01-29 10:35:52	ga_ls7e_ard_3-2-1_115075_2022-01-29_final
2022-02-04 10:01:23	ga_ls7e_ard_3-2-1_109083_2022-02-04_final
2022-02-07 08:51:30	ga_ls7e_ard_3-2-1_098079_2022-02-06_final
2022-02-09 08:36:33	ga_ls7e_ard_3-2-1_096073_2022-02-08_final
2022-02-11 10:07:14	ga_ls7e_ard_3-2-1_110084_2022-02-11_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-21 09:01:15	ga_ls7e_ard_3-2-1_100076_2022-02-20_final
2022-02-22 08:08:44	ga_ls7e_ard_3-2-1_091084_2022-02-21_final
2022-02-23 10:29:11	ga_ls7e_ard_3-2-1_114080_2022-02-23_final
2022-02-27 10:01:41	ga_ls7e_ard_3-2-1_110074_2022-02-27_final
2022-03-01 08:13:51	ga_ls7e_ard_3-2-1_092083_2022-02-28_final
2022-03-02 08:55:49	ga_ls7e_ard_3-2-1_099080_2022-03-01_final
2022-03-04 10:19:44	ga_ls7e_ard_3-2-1_113074_2022-03-04_final
2022-03-11 08:43:57	ga_ls7e_ard_3-2-1_098068_2022-03-10_final
2022-03-12 07:53:49	ga_ls7e_ard_3-2-1_089082_2022-03-11_final
2022-03-18 10:32:17	ga_ls7e_ard_3-2-1_115078_2022-03-18_final
2022-03-22 08:26:19	ga_ls7e_ard_3-2-1_095073_2022-03-21_final
2022-03-23 09:08:41	ga_ls7e_ard_3-2-1_102071_2022-03-22_final
2022-03-25 09:01:20	ga_ls7e_ard_3-2-1_100084_2022-03-24_final
2022-03-26 09:38:55	ga_ls7e_ard_3-2-1_107070_2022-03-26_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