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 08:54:35	ga_ls7e_ard_3-2-0_096084_2021-09-17_final
2021-10-25 09:03:02	ga_ls7e_ard_3-2-0_099067_2021-10-24_final
2021-10-25 09:06:14	ga_ls7e_ard_3-2-0_099075_2021-10-24_final
2021-10-26 08:12:07	ga_ls7e_ard_3-2-0_090079_2021-10-25_final
2021-11-15 09:20:23	ga_ls7e_ard_3-2-1_102069_2021-11-14_final
2021-11-16 10:03:56	ga_ls7e_ard_3-2-1_109070_2021-11-16_final
2021-11-18 09:51:47	ga_ls7e_ard_3-2-1_107071_2021-11-18_final
2021-11-28 08:49:26	ga_ls7e_ard_3-2-1_097072_2021-11-27_final
2021-11-28 08:53:25	ga_ls7e_ard_3-2-1_097082_2021-11-27_final
2021-11-30 08:41:40	ga_ls7e_ard_3-2-1_095084_2021-11-29_final
2021-11-30 08:42:04	ga_ls7e_ard_3-2-1_095085_2021-11-29_final
2021-12-03 09:08:42	ga_ls7e_ard_3-2-1_100075_2021-12-02_final
2021-12-04 08:14:59	ga_ls7e_ard_3-2-1_091080_2021-12-03_final
2021-12-04 08:15:23	ga_ls7e_ard_3-2-1_091081_2021-12-03_final
2021-12-05 10:34:38	ga_ls7e_ard_3-2-1_114074_2021-12-05_final
2021-12-05 10:36:37	ga_ls7e_ard_3-2-1_114079_2021-12-05_final
2021-12-10 09:15:01	ga_ls7e_ard_3-2-1_101077_2021-12-09_final
2021-12-11 08:20:30	ga_ls7e_ard_3-2-1_092080_2021-12-10_final
2021-12-11 09:55:47	ga_ls7e_ard_3-2-1_108071_2021-12-11_final
2021-12-11 09:59:46	ga_ls7e_ard_3-2-1_108081_2021-12-11_final
2021-12-13 08:09:33	ga_ls7e_ard_3-2-1_090084_2021-12-12_final
2021-12-13 09:42:50	ga_ls7e_ard_3-2-1_106070_2021-12-13_final
2021-12-18 08:28:48	ga_ls7e_ard_3-2-1_093087_2021-12-17_final
2021-12-20 09:51:08	ga_ls7e_ard_3-2-1_107077_2021-12-20_final
2021-12-21 10:34:18	ga_ls7e_ard_3-2-1_114077_2021-12-21_final
2021-12-21 10:34:41	ga_ls7e_ard_3-2-1_114078_2021-12-21_final
2021-12-23 08:40:52	ga_ls7e_ard_3-2-1_096072_2021-12-22_final
2021-12-24 09:23:13	ga_ls7e_ard_3-2-1_103070_2021-12-23_final
2021-12-24 09:27:13	ga_ls7e_ard_3-2-1_103080_2021-12-23_final
2021-12-26 09:13:27	ga_ls7e_ard_3-2-1_101077_2021-12-25_final
2021-12-27 08:18:56	ga_ls7e_ard_3-2-1_092080_2021-12-26_final
2021-12-27 08:20:56	ga_ls7e_ard_3-2-1_092085_2021-12-26_final
2021-12-27 09:57:25	ga_ls7e_ard_3-2-1_108079_2021-12-27_final
2021-12-27 09:58:37	ga_ls7e_ard_3-2-1_108082_2021-12-27_final
2021-12-28 09:00:30	ga_ls7e_ard_3-2-1_099076_2021-12-27_final
2021-12-29 09:45:39	ga_ls7e_ard_3-2-1_106081_2021-12-29_final
2021-12-30 10:28:25	ga_ls7e_ard_3-2-1_113080_2021-12-30_final
2022-01-03 10:03:17	ga_ls7e_ard_3-2-1_109080_2022-01-03_final
2022-01-04 09:08:45	ga_ls7e_ard_3-2-1_100083_2022-01-03_final
2022-01-05 08:15:26	ga_ls7e_ard_3-2-1_091089_2022-01-04_final
2022-01-08 08:39:16	ga_ls7e_ard_3-2-1_096072_2022-01-07_final
2022-01-08 08:39:40	ga_ls7e_ard_3-2-1_096073_2022-01-07_final
2022-01-08 08:40:04	ga_ls7e_ard_3-2-1_096074_2022-01-07_final
2022-01-09 09:25:38	ga_ls7e_ard_3-2-1_103080_2022-01-08_final
2022-01-11 09:12:17	ga_ls7e_ard_3-2-1_101078_2022-01-10_final
2022-01-15 08:44:24	ga_ls7e_ard_3-2-1_097071_2022-01-14_final
2022-01-15 10:26:04	ga_ls7e_ard_3-2-1_113078_2022-01-15_final
2022-01-19 08:20:54	ga_ls7e_ard_3-2-1_093075_2022-01-18_final
2022-01-19 08:21:17	ga_ls7e_ard_3-2-1_093076_2022-01-18_final
2022-01-19 08:24:53	ga_ls7e_ard_3-2-1_093085_2022-01-18_final
2022-01-19 09:59:22	ga_ls7e_ard_3-2-1_109074_2022-01-19_final
2022-01-21 08:10:20	ga_ls7e_ard_3-2-1_091080_2022-01-20_final
2022-01-22 10:31:35	ga_ls7e_ard_3-2-1_114078_2022-01-22_final
2022-01-29 08:57:00	ga_ls7e_ard_3-2-1_099075_2022-01-28_final
2022-01-29 10:36:40	ga_ls7e_ard_3-2-1_115077_2022-01-29_final
2022-02-01 09:25:36	ga_ls7e_ard_3-2-1_104070_2022-01-31_final
2022-02-03 09:15:02	ga_ls7e_ard_3-2-1_102075_2022-02-02_final
2022-02-06 08:07:09	ga_ls7e_ard_3-2-1_091076_2022-02-05_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-16 10:21:16	ga_ls7e_ard_3-2-1_113074_2022-02-16_final
2022-02-18 08:33:50	ga_ls7e_ard_3-2-1_095084_2022-02-17_final
2022-02-18 10:07:55	ga_ls7e_ard_3-2-1_111072_2022-02-18_final
2022-02-20 08:22:29	ga_ls7e_ard_3-2-1_093087_2022-02-19_final
2022-02-20 09:59:22	ga_ls7e_ard_3-2-1_109082_2022-02-20_final
2022-02-21 09:03:15	ga_ls7e_ard_3-2-1_100081_2022-02-20_final
2022-02-22 09:44:01	ga_ls7e_ard_3-2-1_107075_2022-02-22_final
2022-02-25 08:39:45	ga_ls7e_ard_3-2-1_096085_2022-02-24_final
2022-02-28 09:05:34	ga_ls7e_ard_3-2-1_101073_2022-02-27_final
2022-02-28 09:07:10	ga_ls7e_ard_3-2-1_101077_2022-02-27_final
2022-03-01 09:53:07	ga_ls7e_ard_3-2-1_108084_2022-03-01_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-04 08:38:52	ga_ls7e_ard_3-2-1_097069_2022-03-03_final
2022-03-04 08:40:52	ga_ls7e_ard_3-2-1_097074_2022-03-03_final
2022-03-06 08:27:54	ga_ls7e_ard_3-2-1_095073_2022-03-05_final
2022-03-06 08:28:18	ga_ls7e_ard_3-2-1_095074_2022-03-05_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-10 08:05:11	ga_ls7e_ard_3-2-1_091079_2022-03-09_final
2022-03-10 09:42:52	ga_ls7e_ard_3-2-1_107076_2022-03-10_final
2022-03-11 10:26:49	ga_ls7e_ard_3-2-1_114078_2022-03-11_final
2022-03-11 10:27:13	ga_ls7e_ard_3-2-1_114079_2022-03-11_final
2022-03-13 08:37:46	ga_ls7e_ard_3-2-1_096084_2022-03-12_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-15 10:00:06	ga_ls7e_ard_3-2-1_110074_2022-03-15_final
2022-03-18 08:55:24	ga_ls7e_ard_3-2-1_099083_2022-03-17_final
2022-03-20 08:38:28	ga_ls7e_ard_3-2-1_097072_2022-03-19_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-20 08:43:15	ga_ls7e_ard_3-2-1_097084_2022-03-19_final
2022-03-20 10:20:32	ga_ls7e_ard_3-2-1_113080_2022-03-20_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
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-25 09:00:56	ga_ls7e_ard_3-2-1_100083_2022-03-24_final
2022-03-26 09:41:18	ga_ls7e_ard_3-2-1_107076_2022-03-26_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-27 08:46:47	ga_ls7e_ard_3-2-1_098079_2022-03-26_final
2022-03-31 09:58:58	ga_ls7e_ard_3-2-1_110075_2022-03-31_final
2022-03-31 10:00:58	ga_ls7e_ard_3-2-1_110080_2022-03-31_final
2022-04-02 09:44:49	ga_ls7e_ard_3-2-1_108071_2022-04-02_final
2022-04-03 08:54:17	ga_ls7e_ard_3-2-1_099084_2022-04-02_final
2022-04-04 07:58:10	ga_ls7e_ard_3-2-1_090083_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