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
2021-09-20 08:38:03	ga_ls7e_ard_3-2-0_094074_2021-09-19_final
2021-09-26 09:38:07	ga_ls7e_ard_3-2-0_104071_2021-09-26_final
2021-09-28 09:27:58	ga_ls7e_ard_3-2-0_102077_2021-09-27_final
2021-09-30 09:17:49	ga_ls7e_ard_3-2-0_100083_2021-09-29_final
2021-10-03 08:07:59	ga_ls7e_ard_3-2-0_089079_2021-10-02_final
2021-10-03 08:09:11	ga_ls7e_ard_3-2-0_089082_2021-10-02_final
2021-10-05 09:35:08	ga_ls7e_ard_3-2-0_103081_2021-10-05_final
2021-10-17 08:22:18	ga_ls7e_ard_3-2-0_091087_2021-10-16_final
2021-10-17 09:58:23	ga_ls7e_ard_3-2-0_107080_2021-10-17_final
2021-10-18 08:57:30	ga_ls7e_ard_3-2-0_098067_2021-10-17_final
2021-10-18 10:40:22	ga_ls7e_ard_3-2-0_114077_2021-10-18_final
2021-10-22 08:35:12	ga_ls7e_ard_3-2-0_094074_2021-10-21_final
2021-10-24 10:04:44	ga_ls7e_ard_3-2-0_108082_2021-10-24_final
2021-10-25 09:03:26	ga_ls7e_ard_3-2-0_099068_2021-10-24_final
2021-10-25 09:03:50	ga_ls7e_ard_3-2-0_099069_2021-10-24_final
2021-10-25 10:46:42	ga_ls7e_ard_3-2-0_115079_2021-10-25_final
2021-10-31 10:10:16	ga_ls7e_ard_3-2-0_109082_2021-10-31_final
2021-11-02 09:53:20	ga_ls7e_ard_3-2-0_107071_2021-11-02_final
2021-11-04 09:39:35	ga_ls7e_ard_3-2-0_105068_2021-11-04_final
2021-11-05 08:49:03	ga_ls7e_ard_3-2-0_096081_2021-11-04_final
2021-11-05 08:49:51	ga_ls7e_ard_3-2-0_096083_2021-11-04_final
2021-11-18 08:18:30	ga_ls7e_ard_3-2-1_091085_2021-11-17_final
2021-11-20 08:03:56	ga_ls7e_ard_3-2-1_089080_2021-11-19_final
2021-11-21 08:44:42	ga_ls7e_ard_3-2-1_096074_2021-11-20_final
2021-11-23 08:35:20	ga_ls7e_ard_3-2-1_094082_2021-11-22_final
2021-11-25 09:56:53	ga_ls7e_ard_3-2-1_108070_2021-11-25_final
2021-11-26 09:01:34	ga_ls7e_ard_3-2-1_099071_2021-11-25_final
2021-11-30 10:15:46	ga_ls7e_ard_3-2-1_111072_2021-11-30_final
2021-12-02 08:27:32	ga_ls7e_ard_3-2-1_093080_2021-12-01_final
2021-12-02 10:07:12	ga_ls7e_ard_3-2-1_109082_2021-12-02_final
2021-12-03 09:07:30	ga_ls7e_ard_3-2-1_100072_2021-12-02_final
2021-12-05 08:52:58	ga_ls7e_ard_3-2-1_098067_2021-12-04_final
2021-12-07 08:42:24	ga_ls7e_ard_3-2-1_096072_2021-12-06_final
2021-12-09 08:32:15	ga_ls7e_ard_3-2-1_094078_2021-12-08_final
2021-12-13 08:11:32	ga_ls7e_ard_3-2-1_090089_2021-12-12_final
2021-12-13 09:45:14	ga_ls7e_ard_3-2-1_106076_2021-12-13_final
2021-12-13 09:47:37	ga_ls7e_ard_3-2-1_106082_2021-12-13_final
2021-12-14 10:28:00	ga_ls7e_ard_3-2-1_113075_2021-12-14_final
2021-12-18 08:24:48	ga_ls7e_ard_3-2-1_093077_2021-12-17_final
2021-12-19 09:05:58	ga_ls7e_ard_3-2-1_100072_2021-12-18_final
2021-12-21 08:53:25	ga_ls7e_ard_3-2-1_098072_2021-12-20_final
2021-12-23 10:23:44	ga_ls7e_ard_3-2-1_112082_2021-12-23_final
2021-12-29 08:06:46	ga_ls7e_ard_3-2-1_090081_2021-12-28_final
2022-01-01 08:39:22	ga_ls7e_ard_3-2-1_095086_2021-12-31_final
2022-01-03 08:24:00	ga_ls7e_ard_3-2-1_093079_2022-01-02_final
2022-01-03 08:24:24	ga_ls7e_ard_3-2-1_093080_2022-01-02_final
2022-01-04 09:04:46	ga_ls7e_ard_3-2-1_100073_2022-01-03_final
2022-01-04 09:07:10	ga_ls7e_ard_3-2-1_100079_2022-01-03_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-05 08:13:02	ga_ls7e_ard_3-2-1_091083_2022-01-04_final
2022-01-08 10:22:56	ga_ls7e_ard_3-2-1_112084_2022-01-08_final
2022-01-10 08:28:43	ga_ls7e_ard_3-2-1_094077_2022-01-09_final
2022-01-10 10:04:48	ga_ls7e_ard_3-2-1_110070_2022-01-10_final
2022-01-10 10:08:24	ga_ls7e_ard_3-2-1_110079_2022-01-10_final
2022-01-12 08:19:22	ga_ls7e_ard_3-2-1_092085_2022-01-11_final
2022-01-17 08:32:39	ga_ls7e_ard_3-2-1_095073_2022-01-16_final
2022-01-19 10:00:58	ga_ls7e_ard_3-2-1_109078_2022-01-19_final
2022-01-19 10:01:22	ga_ls7e_ard_3-2-1_109079_2022-01-19_final
2022-01-25 09:21:43	ga_ls7e_ard_3-2-1_103074_2022-01-24_final
2022-01-25 09:22:30	ga_ls7e_ard_3-2-1_103076_2022-01-24_final
2022-01-26 08:28:47	ga_ls7e_ard_3-2-1_094081_2022-01-25_final
2022-01-26 10:06:52	ga_ls7e_ard_3-2-1_110079_2022-01-26_final
2022-01-28 09:54:18	ga_ls7e_ard_3-2-1_108079_2022-01-28_final
2022-01-31 08:44:02	ga_ls7e_ard_3-2-1_097074_2022-01-30_final
2022-01-31 10:22:55	ga_ls7e_ard_3-2-1_113074_2022-01-31_final
2022-02-02 10:12:21	ga_ls7e_ard_3-2-1_111079_2022-02-02_final
2022-02-04 08:20:07	ga_ls7e_ard_3-2-1_093077_2022-02-03_final
2022-02-04 08:23:18	ga_ls7e_ard_3-2-1_093085_2022-02-03_final
2022-02-04 10:00:11	ga_ls7e_ard_3-2-1_109080_2022-02-04_final
2022-02-04 10:00:59	ga_ls7e_ard_3-2-1_109082_2022-02-04_final
2022-02-05 09:01:16	ga_ls7e_ard_3-2-1_100072_2022-02-04_final
2022-02-06 08:11:08	ga_ls7e_ard_3-2-1_091086_2022-02-05_final
2022-02-11 08:25:58	ga_ls7e_ard_3-2-1_094078_2022-02-10_final
2022-02-13 09:51:53	ga_ls7e_ard_3-2-1_108077_2022-02-13_final
2022-02-19 09:16:12	ga_ls7e_ard_3-2-1_102082_2022-02-18_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-23 08:49:30	ga_ls7e_ard_3-2-1_098078_2022-02-22_final
2022-02-25 08:36:57	ga_ls7e_ard_3-2-1_096078_2022-02-24_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-25 10:14:38	ga_ls7e_ard_3-2-1_112075_2022-02-25_final
2022-02-27 08:24:00	ga_ls7e_ard_3-2-1_094077_2022-02-26_final
2022-02-27 08:24:24	ga_ls7e_ard_3-2-1_094078_2022-02-26_final
2022-02-27 10:01:41	ga_ls7e_ard_3-2-1_110074_2022-02-27_final
2022-03-01 08:12:15	ga_ls7e_ard_3-2-1_092079_2022-02-28_final
2022-03-02 08:55:49	ga_ls7e_ard_3-2-1_099080_2022-03-01_final
2022-03-06 10:06:47	ga_ls7e_ard_3-2-1_111073_2022-03-06_final
2022-03-06 10:09:11	ga_ls7e_ard_3-2-1_111079_2022-03-06_final
2022-03-13 08:36:11	ga_ls7e_ard_3-2-1_096080_2022-03-12_final
2022-03-15 08:26:24	ga_ls7e_ard_3-2-1_094087_2022-03-14_final
2022-03-20 08:43:15	ga_ls7e_ard_3-2-1_097084_2022-03-19_final
2022-03-21 09:20:50	ga_ls7e_ard_3-2-1_104070_2022-03-20_final
2022-03-24 08:15:22	ga_ls7e_ard_3-2-1_093077_2022-03-23_final
2022-03-25 08:59:44	ga_ls7e_ard_3-2-1_100080_2022-03-24_final
2022-03-26 09:42:54	ga_ls7e_ard_3-2-1_107080_2022-03-26_final
2022-03-31 08:20:53	ga_ls7e_ard_3-2-1_094077_2022-03-30_final
2022-03-31 09:58:58	ga_ls7e_ard_3-2-1_110075_2022-03-31_final
2022-04-02 08:08:44	ga_ls7e_ard_3-2-1_092078_2022-04-01_final
2022-04-04 07:55:46	ga_ls7e_ard_3-2-1_090077_2022-04-03_final
2022-04-04 09:31:03	ga_ls7e_ard_3-2-1_106068_2022-04-04_final
2022-04-05 10:16:37	ga_ls7e_ard_3-2-1_113074_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years