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 08:51:23	ga_ls7e_ard_3-2-0_096076_2021-09-17_final
2021-09-18 08:54:11	ga_ls7e_ard_3-2-0_096083_2021-09-17_final
2021-09-18 10:32:16	ga_ls7e_ard_3-2-0_112081_2021-09-18_final
2021-09-20 08:37:39	ga_ls7e_ard_3-2-0_094073_2021-09-19_final
2021-09-20 10:17:20	ga_ls7e_ard_3-2-0_110075_2021-09-20_final
2021-12-12 10:40:33	ga_ls7e_ard_3-2-1_115075_2021-12-12_final
2021-12-17 09:17:20	ga_ls7e_ard_3-2-1_102069_2021-12-16_final
2021-12-17 09:21:19	ga_ls7e_ard_3-2-1_102079_2021-12-16_final
2021-12-17 09:22:07	ga_ls7e_ard_3-2-1_102081_2021-12-16_final
2021-12-21 08:53:49	ga_ls7e_ard_3-2-1_098073_2021-12-20_final
2021-12-21 08:56:37	ga_ls7e_ard_3-2-1_098080_2021-12-20_final
2021-12-22 09:38:58	ga_ls7e_ard_3-2-1_105078_2021-12-22_final
2021-12-25 08:30:42	ga_ls7e_ard_3-2-1_094078_2021-12-24_final
2021-12-26 09:14:39	ga_ls7e_ard_3-2-1_101080_2021-12-25_final
2021-12-27 09:57:01	ga_ls7e_ard_3-2-1_108078_2021-12-27_final
2021-12-28 09:00:30	ga_ls7e_ard_3-2-1_099076_2021-12-27_final
2021-12-29 09:43:15	ga_ls7e_ard_3-2-1_106075_2021-12-29_final
2022-01-01 10:15:03	ga_ls7e_ard_3-2-1_111078_2022-01-01_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-04 09:05:10	ga_ls7e_ard_3-2-1_100074_2022-01-03_final
2022-01-08 08:38:52	ga_ls7e_ard_3-2-1_096071_2022-01-07_final
2022-01-08 08:42:52	ga_ls7e_ard_3-2-1_096081_2022-01-07_final
2022-01-09 09:22:02	ga_ls7e_ard_3-2-1_103071_2022-01-08_final
2022-01-11 09:11:05	ga_ls7e_ard_3-2-1_101075_2022-01-10_final
2022-01-14 08:04:01	ga_ls7e_ard_3-2-1_090078_2022-01-13_final
2022-01-14 08:04:25	ga_ls7e_ard_3-2-1_090079_2022-01-13_final
2022-01-14 08:05:37	ga_ls7e_ard_3-2-1_090082_2022-01-13_final
2022-01-14 08:06:01	ga_ls7e_ard_3-2-1_090083_2022-01-13_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-01-20 09:06:27	ga_ls7e_ard_3-2-1_100081_2022-01-19_final
2022-01-24 10:17:49	ga_ls7e_ard_3-2-1_112075_2022-01-24_final
2022-01-26 10:05:40	ga_ls7e_ard_3-2-1_110076_2022-01-26_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-29 09:00:11	ga_ls7e_ard_3-2-1_099083_2022-01-28_final
2022-01-30 08:06:28	ga_ls7e_ard_3-2-1_090088_2022-01-29_final
2022-01-31 08:46:26	ga_ls7e_ard_3-2-1_097080_2022-01-30_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-02-06 09:45:14	ga_ls7e_ard_3-2-1_107074_2022-02-06_final
2022-02-07 08:52:18	ga_ls7e_ard_3-2-1_098081_2022-02-06_final
2022-02-09 08:36:56	ga_ls7e_ard_3-2-1_096074_2022-02-08_final
2022-02-10 09:20:30	ga_ls7e_ard_3-2-1_103075_2022-02-09_final
2022-02-12 09:10:43	ga_ls7e_ard_3-2-1_101082_2022-02-11_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-15 09:39:18	ga_ls7e_ard_3-2-1_106077_2022-02-15_final
2022-02-16 08:40:48	ga_ls7e_ard_3-2-1_097070_2022-02-15_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-17 09:23:34	ga_ls7e_ard_3-2-1_104069_2022-02-16_final
2022-02-17 09:27:33	ga_ls7e_ard_3-2-1_104079_2022-02-16_final
2022-02-17 09:28:21	ga_ls7e_ard_3-2-1_104081_2022-02-16_final
2022-02-18 10:10:19	ga_ls7e_ard_3-2-1_111078_2022-02-18_final
2022-02-19 09:13:48	ga_ls7e_ard_3-2-1_102076_2022-02-18_final
2022-02-20 08:21:17	ga_ls7e_ard_3-2-1_093084_2022-02-19_final
2022-02-20 09:56:10	ga_ls7e_ard_3-2-1_109074_2022-02-20_final
2022-02-22 09:44:01	ga_ls7e_ard_3-2-1_107075_2022-02-22_final
2022-02-22 09:45:37	ga_ls7e_ard_3-2-1_107079_2022-02-22_final
2022-02-24 09:33:04	ga_ls7e_ard_3-2-1_105079_2022-02-24_final
2022-02-26 09:18:07	ga_ls7e_ard_3-2-1_103073_2022-02-25_final
2022-02-27 08:23:12	ga_ls7e_ard_3-2-1_094075_2022-02-26_final
2022-02-27 08:26:24	ga_ls7e_ard_3-2-1_094083_2022-02-26_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-02-28 09:09:10	ga_ls7e_ard_3-2-1_101082_2022-02-27_final
2022-03-01 08:13:27	ga_ls7e_ard_3-2-1_092082_2022-02-28_final
2022-03-01 09:49:56	ga_ls7e_ard_3-2-1_108076_2022-03-01_final
2022-03-03 09:34:11	ga_ls7e_ard_3-2-1_106068_2022-03-03_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-06 08:28:42	ga_ls7e_ard_3-2-1_095075_2022-03-05_final
2022-03-07 09:12:16	ga_ls7e_ard_3-2-1_102076_2022-03-06_final
2022-03-07 09:12:40	ga_ls7e_ard_3-2-1_102077_2022-03-06_final
2022-03-07 09:13:28	ga_ls7e_ard_3-2-1_102079_2022-03-06_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-10 09:42:04	ga_ls7e_ard_3-2-1_107074_2022-03-10_final
2022-03-10 09:44:04	ga_ls7e_ard_3-2-1_107079_2022-03-10_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-13 08:37:23	ga_ls7e_ard_3-2-1_096083_2022-03-12_final
2022-03-13 10:13:04	ga_ls7e_ard_3-2-1_112075_2022-03-13_final
2022-03-13 10:14:39	ga_ls7e_ard_3-2-1_112079_2022-03-13_final
2022-03-13 10:15:03	ga_ls7e_ard_3-2-1_112080_2022-03-13_final
2022-03-13 10:16:15	ga_ls7e_ard_3-2-1_112083_2022-03-13_final
2022-03-14 09:18:08	ga_ls7e_ard_3-2-1_103077_2022-03-13_final
2022-03-17 08:09:51	ga_ls7e_ard_3-2-1_092077_2022-03-16_final
2022-03-20 08:41:40	ga_ls7e_ard_3-2-1_097080_2022-03-19_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-22 08:27:31	ga_ls7e_ard_3-2-1_095076_2022-03-21_final
2022-03-22 10:06:00	ga_ls7e_ard_3-2-1_111075_2022-03-22_final
2022-03-23 09:08:41	ga_ls7e_ard_3-2-1_102071_2022-03-22_final
2022-03-23 09:12:17	ga_ls7e_ard_3-2-1_102080_2022-03-22_final
2022-03-24 08:18:34	ga_ls7e_ard_3-2-1_093085_2022-03-23_final
2022-03-26 08:07:13	ga_ls7e_ard_3-2-1_091088_2022-03-25_final
2022-03-29 08:31:27	ga_ls7e_ard_3-2-1_096072_2022-03-28_final
2022-03-31 08:20:05	ga_ls7e_ard_3-2-1_094075_2022-03-30_final
2022-03-31 10:00:58	ga_ls7e_ard_3-2-1_110080_2022-03-31_final
2022-04-01 09:03:39	ga_ls7e_ard_3-2-1_101076_2022-03-31_final
2022-04-02 09:45:13	ga_ls7e_ard_3-2-1_108072_2022-04-02_final
2022-04-03 08:53:53	ga_ls7e_ard_3-2-1_099083_2022-04-02_final
2022-04-03 10:30:22	ga_ls7e_ard_3-2-1_115077_2022-04-03_final
2022-04-04 07:56:58	ga_ls7e_ard_3-2-1_090080_2022-04-03_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_2022-04-03_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_2022-04-04_final
2022-04-05 08:36:56	ga_ls7e_ard_3-2-1_097072_2022-04-04_final
2022-04-05 08:40:55	ga_ls7e_ard_3-2-1_097082_2022-04-04_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