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 08:50:59	ga_ls7e_ard_3-2-0_096075_2021-09-17_final
2021-09-18 08:52:11	ga_ls7e_ard_3-2-0_096078_2021-09-17_final
2021-09-18 10:30:16	ga_ls7e_ard_3-2-0_112076_2021-09-18_final
2021-09-18 10:30:40	ga_ls7e_ard_3-2-0_112077_2021-09-18_final
2021-09-20 08:38:27	ga_ls7e_ard_3-2-0_094075_2021-09-19_final
2021-10-25 09:08:37	ga_ls7e_ard_3-2-0_099081_2021-10-24_final
2021-10-26 08:11:43	ga_ls7e_ard_3-2-0_090078_2021-10-25_final
2021-11-01 09:12:10	ga_ls7e_ard_3-2-0_100076_2021-10-31_final
2021-11-05 08:49:03	ga_ls7e_ard_3-2-0_096081_2021-11-04_final
2021-11-05 08:49:27	ga_ls7e_ard_3-2-0_096082_2021-11-04_final
2021-11-05 08:49:51	ga_ls7e_ard_3-2-0_096083_2021-11-04_final
2021-11-09 10:00:50	ga_ls7e_ard_3-2-0_108076_2021-11-09_final
2021-11-13 09:34:56	ga_ls7e_ard_3-2-1_104074_2021-11-13_final
2021-11-14 08:41:13	ga_ls7e_ard_3-2-1_095079_2021-11-13_final
2021-11-16 10:04:44	ga_ls7e_ard_3-2-1_109072_2021-11-16_final
2021-11-21 08:45:30	ga_ls7e_ard_3-2-1_096076_2021-11-20_final
2021-11-25 09:59:16	ga_ls7e_ard_3-2-1_108076_2021-11-25_final
2021-11-25 10:00:04	ga_ls7e_ard_3-2-1_108078_2021-11-25_final
2021-11-29 09:32:36	ga_ls7e_ard_3-2-1_104072_2021-11-29_final
2021-12-04 08:14:35	ga_ls7e_ard_3-2-1_091079_2021-12-03_final
2021-12-04 08:15:47	ga_ls7e_ard_3-2-1_091082_2021-12-03_final
2021-12-06 09:38:31	ga_ls7e_ard_3-2-1_105073_2021-12-06_final
2021-12-07 08:42:24	ga_ls7e_ard_3-2-1_096072_2021-12-06_final
2021-12-10 09:14:37	ga_ls7e_ard_3-2-1_101076_2021-12-09_final
2021-12-11 09:59:22	ga_ls7e_ard_3-2-1_108080_2021-12-11_final
2021-12-14 10:29:35	ga_ls7e_ard_3-2-1_113079_2021-12-14_final
2021-12-16 08:36:34	ga_ls7e_ard_3-2-1_095075_2021-12-15_final
2021-12-16 10:17:02	ga_ls7e_ard_3-2-1_111079_2021-12-16_final
2021-12-22 09:36:59	ga_ls7e_ard_3-2-1_105073_2021-12-22_final
2021-12-22 09:38:58	ga_ls7e_ard_3-2-1_105078_2021-12-22_final
2021-12-25 08:31:06	ga_ls7e_ard_3-2-1_094079_2021-12-24_final
2021-12-25 08:33:53	ga_ls7e_ard_3-2-1_094086_2021-12-24_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-28 08:59:42	ga_ls7e_ard_3-2-1_099074_2021-12-27_final
2021-12-30 08:47:32	ga_ls7e_ard_3-2-1_097075_2021-12-29_final
2021-12-30 10:27:13	ga_ls7e_ard_3-2-1_113077_2021-12-30_final
2021-12-31 09:30:18	ga_ls7e_ard_3-2-1_104074_2021-12-31_final
2022-01-01 08:36:34	ga_ls7e_ard_3-2-1_095079_2021-12-31_final
2022-01-01 10:14:39	ga_ls7e_ard_3-2-1_111077_2022-01-01_final
2022-01-03 08:25:12	ga_ls7e_ard_3-2-1_093082_2022-01-02_final
2022-01-03 10:02:05	ga_ls7e_ard_3-2-1_109077_2022-01-03_final
2022-01-04 09:07:33	ga_ls7e_ard_3-2-1_100080_2022-01-03_final
2022-01-05 08:11:02	ga_ls7e_ard_3-2-1_091078_2022-01-04_final
2022-01-09 09:23:14	ga_ls7e_ard_3-2-1_103074_2022-01-08_final
2022-01-12 09:55:27	ga_ls7e_ard_3-2-1_108078_2022-01-12_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-17 10:13:55	ga_ls7e_ard_3-2-1_111079_2022-01-17_final
2022-01-18 09:15:25	ga_ls7e_ard_3-2-1_102072_2022-01-17_final
2022-01-20 09:06:27	ga_ls7e_ard_3-2-1_100081_2022-01-19_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-30 09:42:33	ga_ls7e_ard_3-2-1_106081_2022-01-30_final
2022-02-02 08:33:04	ga_ls7e_ard_3-2-1_095078_2022-02-01_final
2022-02-02 08:35:28	ga_ls7e_ard_3-2-1_095084_2022-02-01_final
2022-02-04 08:22:30	ga_ls7e_ard_3-2-1_093083_2022-02-03_final
2022-02-05 09:04:04	ga_ls7e_ard_3-2-1_100079_2022-02-04_final
2022-02-05 09:04:52	ga_ls7e_ard_3-2-1_100081_2022-02-04_final
2022-02-06 09:47:37	ga_ls7e_ard_3-2-1_107080_2022-02-06_final
2022-02-09 08:38:56	ga_ls7e_ard_3-2-1_096079_2022-02-08_final
2022-02-09 08:40:08	ga_ls7e_ard_3-2-1_096082_2022-02-08_final
2022-02-11 08:26:46	ga_ls7e_ard_3-2-1_094080_2022-02-10_final
2022-02-12 09:09:31	ga_ls7e_ard_3-2-1_101079_2022-02-11_final
2022-02-12 09:10:19	ga_ls7e_ard_3-2-1_101081_2022-02-11_final
2022-02-18 08:32:38	ga_ls7e_ard_3-2-1_095081_2022-02-17_final
2022-02-19 09:13:24	ga_ls7e_ard_3-2-1_102075_2022-02-18_final
2022-02-19 09:15:00	ga_ls7e_ard_3-2-1_102079_2022-02-18_final
2022-02-20 08:17:18	ga_ls7e_ard_3-2-1_093074_2022-02-19_final
2022-02-20 08:20:53	ga_ls7e_ard_3-2-1_093083_2022-02-19_final
2022-02-21 09:02:27	ga_ls7e_ard_3-2-1_100079_2022-02-20_final
2022-02-22 09:45:37	ga_ls7e_ard_3-2-1_107079_2022-02-22_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-24 09:32:16	ga_ls7e_ard_3-2-1_105077_2022-02-24_final
2022-02-24 09:32:40	ga_ls7e_ard_3-2-1_105078_2022-02-24_final
2022-02-25 10:15:02	ga_ls7e_ard_3-2-1_112076_2022-02-25_final
2022-02-25 10:15:50	ga_ls7e_ard_3-2-1_112078_2022-02-25_final
2022-02-25 10:16:38	ga_ls7e_ard_3-2-1_112080_2022-02-25_final
2022-02-26 09:17:20	ga_ls7e_ard_3-2-1_103071_2022-02-25_final
2022-02-28 09:08:22	ga_ls7e_ard_3-2-1_101080_2022-02-27_final
2022-03-01 08:12:39	ga_ls7e_ard_3-2-1_092080_2022-02-28_final
2022-03-02 08:56:13	ga_ls7e_ard_3-2-1_099081_2022-03-01_final
2022-03-03 07:59:42	ga_ls7e_ard_3-2-1_090079_2022-03-02_final
2022-03-03 08:00:30	ga_ls7e_ard_3-2-1_090081_2022-03-02_final
2022-03-04 08:41:16	ga_ls7e_ard_3-2-1_097075_2022-03-03_final
2022-03-04 10:21:44	ga_ls7e_ard_3-2-1_113079_2022-03-04_final
2022-03-06 08:29:06	ga_ls7e_ard_3-2-1_095076_2022-03-05_final
2022-03-07 09:11:28	ga_ls7e_ard_3-2-1_102074_2022-03-06_final
2022-03-07 09:11:52	ga_ls7e_ard_3-2-1_102075_2022-03-06_final
2022-03-07 09:13:04	ga_ls7e_ard_3-2-1_102078_2022-03-06_final
2022-03-08 09:57:01	ga_ls7e_ard_3-2-1_109080_2022-03-08_final
2022-03-10 09:41:40	ga_ls7e_ard_3-2-1_107073_2022-03-10_final
2022-03-13 08:32:59	ga_ls7e_ard_3-2-1_096072_2022-03-12_final
2022-03-15 10:02:29	ga_ls7e_ard_3-2-1_110080_2022-03-15_final
2022-03-22 10:06:24	ga_ls7e_ard_3-2-1_111076_2022-03-22_final
2022-03-24 08:15:22	ga_ls7e_ard_3-2-1_093077_2022-03-23_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-24 08:17:46	ga_ls7e_ard_3-2-1_093083_2022-03-23_final
2022-03-25 08:59:44	ga_ls7e_ard_3-2-1_100080_2022-03-24_final
2022-03-28 09:29:09	ga_ls7e_ard_3-2-1_105077_2022-03-27_final
2022-03-31 08:20:05	ga_ls7e_ard_3-2-1_094075_2022-03-30_final
2022-04-01 09:03:15	ga_ls7e_ard_3-2-1_101075_2022-03-31_final
2022-04-03 08:50:18	ga_ls7e_ard_3-2-1_099074_2022-04-02_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