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
2019-02-28 09:28:17	ga_ls7e_ard_3-1-0_093074_2019-02-27_final
2019-02-28 09:29:04	ga_ls7e_ard_3-1-0_093076_2019-02-27_final
2019-03-02 09:17:51	ga_ls7e_ard_3-1-0_091079_2019-03-01_final
2019-03-02 09:18:15	ga_ls7e_ard_3-1-0_091080_2019-03-01_final
2019-03-02 09:18:39	ga_ls7e_ard_3-1-0_091081_2019-03-01_final
2019-03-02 09:19:03	ga_ls7e_ard_3-1-0_091082_2019-03-01_final
2019-03-02 09:19:27	ga_ls7e_ard_3-1-0_091083_2019-03-01_final
2019-03-02 09:19:51	ga_ls7e_ard_3-1-0_091084_2019-03-01_final
2019-03-02 09:20:15	ga_ls7e_ard_3-1-0_091085_2019-03-01_final
2019-04-01 09:27:37	ga_ls7e_ard_3-0-0_093075_2019-03-31_final
2019-04-01 09:28:01	ga_ls7e_ard_3-0-0_093076_2019-03-31_final
2019-04-03 09:16:47	ga_ls7e_ard_3-0-0_091079_2019-04-02_final
2019-04-03 09:17:11	ga_ls7e_ard_3-0-0_091080_2019-04-02_final
2019-04-03 09:17:35	ga_ls7e_ard_3-0-0_091081_2019-04-02_final
2019-04-03 09:17:59	ga_ls7e_ard_3-0-0_091082_2019-04-02_final
2019-04-03 09:18:23	ga_ls7e_ard_3-0-0_091083_2019-04-02_final
2019-04-03 09:18:47	ga_ls7e_ard_3-0-0_091084_2019-04-02_final
2019-04-03 09:19:11	ga_ls7e_ard_3-0-0_091085_2019-04-02_final
2019-06-06 09:14:25	ga_ls7e_ard_3-0-0_091079_2019-06-05_final
2019-06-06 09:14:49	ga_ls7e_ard_3-0-0_091080_2019-06-05_final
2019-06-06 09:15:13	ga_ls7e_ard_3-1-0_091081_2019-06-05_final
2019-06-06 09:15:37	ga_ls7e_ard_3-0-0_091082_2019-06-05_final
2019-06-06 09:16:01	ga_ls7e_ard_3-0-0_091083_2019-06-05_final
2019-06-06 09:16:25	ga_ls7e_ard_3-0-0_091084_2019-06-05_final
2019-06-06 09:16:49	ga_ls7e_ard_3-0-0_091085_2019-06-05_final
2019-06-11 09:28:00	ga_ls7e_ard_3-1-0_094067_2019-06-10_final
2019-06-13 09:18:45	ga_ls7e_ard_3-0-0_092075_2019-06-12_final
2019-06-13 09:19:09	ga_ls7e_ard_3-0-0_092076_2019-06-12_final
2019-06-13 09:19:33	ga_ls7e_ard_3-0-0_092077_2019-06-12_final
2019-06-13 09:19:57	ga_ls7e_ard_3-0-0_092078_2019-06-12_final
2019-06-13 09:20:21	ga_ls7e_ard_3-0-0_092079_2019-06-12_final
2019-06-13 09:20:45	ga_ls7e_ard_3-0-0_092080_2019-06-12_final
2019-08-18 09:06:59	ga_ls7e_ard_3-0-0_090083_2019-08-17_final
2019-08-18 09:07:23	ga_ls7e_ard_3-0-0_090084_2019-08-17_final
2019-08-18 09:08:59	ga_ls7e_ard_3-0-0_090088_2019-08-17_final
2019-08-18 09:09:23	ga_ls7e_ard_3-0-0_090089_2019-08-17_final
2019-09-06 09:30:41	ga_ls7e_ard_3-1-0_095067_2019-09-06_final
2019-09-08 09:21:02	ga_ls7e_ard_3-1-0_093074_2019-09-07_final
2019-09-08 09:21:26	ga_ls7e_ard_3-1-0_093075_2019-09-07_final
2019-09-08 09:21:50	ga_ls7e_ard_3-1-0_093076_2019-09-07_final
2019-09-10 09:10:35	ga_ls7e_ard_3-1-0_091079_2019-09-09_final
2019-09-10 09:10:59	ga_ls7e_ard_3-1-0_091080_2019-09-09_final
2019-09-10 09:11:23	ga_ls7e_ard_3-1-0_091081_2019-09-09_final
2019-09-10 09:11:47	ga_ls7e_ard_3-1-0_091082_2019-09-09_final
2019-09-10 09:12:11	ga_ls7e_ard_3-1-0_091083_2019-09-09_final
2019-09-10 09:12:35	ga_ls7e_ard_3-1-0_091084_2019-09-09_final
2019-09-10 09:12:59	ga_ls7e_ard_3-1-0_091085_2019-09-09_final
2019-11-18 09:21:20	ga_ls7e_ard_3-1-0_094067_2019-11-17_final
2019-11-20 09:12:04	ga_ls7e_ard_3-1-0_092075_2019-11-19_final
2019-11-20 09:12:28	ga_ls7e_ard_3-1-0_092076_2019-11-19_final
2019-11-20 09:12:52	ga_ls7e_ard_3-1-0_092077_2019-11-19_final
2019-11-20 09:13:16	ga_ls7e_ard_3-1-0_092078_2019-11-19_final
2019-11-20 09:13:40	ga_ls7e_ard_3-1-0_092079_2019-11-19_final
2019-11-20 09:14:04	ga_ls7e_ard_3-1-0_092080_2019-11-19_final
2019-11-20 09:14:27	ga_ls7e_ard_3-1-0_092081_2019-11-19_final
2019-12-08 09:02:01	ga_ls7e_ard_3-1-0_090083_2019-12-07_final
2019-12-08 09:02:25	ga_ls7e_ard_3-1-0_090084_2019-12-07_final
2019-12-08 09:02:49	ga_ls7e_ard_3-1-0_090085_2019-12-07_final
2019-12-08 09:03:13	ga_ls7e_ard_3-1-0_090086_2019-12-07_final
2019-12-08 09:04:01	ga_ls7e_ard_3-1-0_090088_2019-12-07_final
2019-12-08 09:04:25	ga_ls7e_ard_3-1-0_090089_2019-12-07_final
2020-01-05 09:18:55	ga_ls7e_ard_3-1-0_094067_2020-01-04_final
2020-01-14 09:15:05	ga_ls7e_ard_3-1-0_093074_2020-01-13_final
2020-01-14 09:15:29	ga_ls7e_ard_3-1-0_093075_2020-01-13_final
2020-01-14 09:15:53	ga_ls7e_ard_3-1-0_093076_2020-01-13_final
2020-02-24 09:09:37	ga_ls7e_ard_3-1-0_092081_2020-02-23_final
2020-02-26 08:57:57	ga_ls7e_ard_3-1-0_090083_2020-02-25_final
2020-02-26 08:58:20	ga_ls7e_ard_3-1-0_090084_2020-02-25_final
2020-02-26 08:58:44	ga_ls7e_ard_3-1-0_090085_2020-02-25_final
2020-02-26 08:59:08	ga_ls7e_ard_3-1-0_090086_2020-02-25_final
2020-03-18 09:11:45	ga_ls7e_ard_3-1-0_093074_2020-03-17_final
2020-03-18 09:12:09	ga_ls7e_ard_3-1-0_093075_2020-03-17_final
2020-06-01 08:52:23	ga_ls7e_ard_3-1-0_090083_2020-05-31_final
2020-06-01 08:52:47	ga_ls7e_ard_3-1-0_090084_2020-05-31_final
2020-06-01 08:53:11	ga_ls7e_ard_3-1-0_090085_2020-05-31_final
2020-06-01 08:53:35	ga_ls7e_ard_3-1-0_090086_2020-05-31_final
2020-06-01 08:54:23	ga_ls7e_ard_3-1-0_090088_2020-05-31_final
2020-06-01 08:54:47	ga_ls7e_ard_3-1-0_090089_2020-05-31_final
2020-08-07 09:12:52	ga_ls7e_ard_3-1-0_095067_2020-08-06_final
2020-08-09 09:03:10	ga_ls7e_ard_3-1-0_093074_2020-08-08_final
2020-08-09 09:03:34	ga_ls7e_ard_3-1-0_093075_2020-08-08_final
2020-08-09 09:03:58	ga_ls7e_ard_3-1-0_093076_2020-08-08_final
2020-09-10 09:01:06	ga_ls7e_ard_3-1-0_093074_2020-09-09_final
2020-09-10 09:01:30	ga_ls7e_ard_3-1-0_093075_2020-09-09_final
2020-09-10 09:01:53	ga_ls7e_ard_3-1-0_093076_2020-09-09_final
2020-12-13 09:04:17	ga_ls7e_ard_3-1-0_095067_2020-12-12_final
2020-12-15 08:54:33	ga_ls7e_ard_3-1-0_093074_2020-12-14_final
2020-12-15 08:54:57	ga_ls7e_ard_3-1-0_093075_2020-12-14_final
2020-12-15 08:55:21	ga_ls7e_ard_3-1-0_093076_2020-12-14_final
2020-12-17 08:44:02	ga_ls7e_ard_3-1-0_091079_2020-12-16_final
2020-12-17 08:44:26	ga_ls7e_ard_3-1-0_091080_2020-12-16_final
2020-12-17 08:45:14	ga_ls7e_ard_3-1-0_091082_2020-12-16_final
2020-12-17 08:46:26	ga_ls7e_ard_3-1-0_091085_2020-12-16_final
2020-12-22 08:57:24	ga_ls7e_ard_3-1-0_094067_2020-12-21_final
2020-12-24 08:48:54	ga_ls7e_ard_3-1-0_092077_2020-12-23_final
2020-12-24 08:49:18	ga_ls7e_ard_3-1-0_092078_2020-12-23_final
2020-12-24 08:50:29	ga_ls7e_ard_3-1-0_092081_2020-12-23_final
2020-12-26 08:39:12	ga_ls7e_ard_3-1-0_090084_2020-12-25_final
2020-12-26 08:39:59	ga_ls7e_ard_3-1-0_090086_2020-12-25_final
2020-12-26 08:40:47	ga_ls7e_ard_3-1-0_090088_2020-12-25_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