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
2015-06-11 09:24:04	ga_ls7e_ard_3-0-0_091079_2015-06-10_final
2015-06-11 09:24:28	ga_ls7e_ard_3-0-0_091080_2015-06-10_final
2015-06-11 09:24:52	ga_ls7e_ard_3-0-0_091081_2015-06-10_final
2015-06-11 09:25:16	ga_ls7e_ard_3-0-0_091082_2015-06-10_final
2015-06-11 09:25:40	ga_ls7e_ard_3-0-0_091083_2015-06-10_final
2015-06-11 09:26:04	ga_ls7e_ard_3-0-0_091084_2015-06-10_final
2015-06-11 09:26:28	ga_ls7e_ard_3-0-0_091085_2015-06-10_final
2015-06-13 09:15:43	ga_ls7e_ard_3-0-0_089089_2015-06-12_final
2015-06-13 09:16:07	ga_ls7e_ard_3-0-0_089090_2015-06-12_final
2017-06-05 09:40:48	ga_ls7e_ard_3-1-0_094067_2017-06-05_final
2017-09-25 09:40:49	ga_ls7e_ard_3-1-0_094067_2017-09-25_final
2017-12-30 09:40:25	ga_ls7e_ard_3-1-0_094067_2017-12-30_final
2018-04-30 09:35:19	ga_ls7e_ard_3-0-0_093074_2018-04-30_final
2018-04-30 09:35:43	ga_ls7e_ard_3-0-0_093075_2018-04-30_final
2018-04-30 09:36:07	ga_ls7e_ard_3-0-0_093076_2018-04-30_final
2018-05-02 09:24:55	ga_ls7e_ard_3-0-0_091079_2018-05-01_final
2018-05-02 09:25:19	ga_ls7e_ard_3-0-0_091080_2018-05-01_final
2018-05-02 09:25:43	ga_ls7e_ard_3-0-0_091081_2018-05-01_final
2018-05-02 09:26:07	ga_ls7e_ard_3-0-0_091082_2018-05-01_final
2018-05-02 09:26:31	ga_ls7e_ard_3-0-0_091083_2018-05-01_final
2018-05-02 09:26:55	ga_ls7e_ard_3-0-0_091084_2018-05-01_final
2018-05-14 09:44:39	ga_ls7e_ard_3-0-0_095067_2018-05-14_final
2018-05-16 09:35:03	ga_ls7e_ard_3-0-0_093074_2018-05-16_final
2018-05-16 09:35:27	ga_ls7e_ard_3-0-0_093075_2018-05-16_final
2018-05-16 09:35:51	ga_ls7e_ard_3-0-0_093076_2018-05-16_final
2018-05-18 09:24:39	ga_ls7e_ard_3-0-0_091079_2018-05-17_final
2018-05-18 09:25:03	ga_ls7e_ard_3-0-0_091080_2018-05-17_final
2018-05-18 09:25:27	ga_ls7e_ard_3-0-0_091081_2018-05-17_final
2018-05-18 09:25:51	ga_ls7e_ard_3-0-0_091082_2018-05-17_final
2018-05-18 09:26:15	ga_ls7e_ard_3-0-0_091083_2018-05-17_final
2018-05-18 09:26:39	ga_ls7e_ard_3-0-0_091084_2018-05-17_final
2018-05-18 09:27:03	ga_ls7e_ard_3-0-0_091085_2018-05-17_final
2018-06-03 09:24:24	ga_ls7e_ard_3-0-0_091079_2018-06-02_final
2018-06-03 09:24:48	ga_ls7e_ard_3-0-0_091080_2018-06-02_final
2018-06-03 09:25:12	ga_ls7e_ard_3-0-0_091081_2018-06-02_final
2018-06-03 09:25:36	ga_ls7e_ard_3-0-0_091082_2018-06-02_final
2018-06-03 09:26:00	ga_ls7e_ard_3-0-0_091083_2018-06-02_final
2018-06-03 09:26:24	ga_ls7e_ard_3-0-0_091084_2018-06-02_final
2018-06-03 09:26:48	ga_ls7e_ard_3-0-0_091085_2018-06-02_final
2018-07-05 09:23:48	ga_ls7e_ard_3-0-0_091079_2018-07-04_final
2018-07-05 09:24:11	ga_ls7e_ard_3-0-0_091080_2018-07-04_final
2018-07-05 09:24:35	ga_ls7e_ard_3-0-0_091081_2018-07-04_final
2018-07-05 09:24:59	ga_ls7e_ard_3-0-0_091082_2018-07-04_final
2018-07-05 09:25:23	ga_ls7e_ard_3-0-0_091083_2018-07-04_final
2018-07-05 09:25:47	ga_ls7e_ard_3-0-0_091084_2018-07-04_final
2018-07-05 09:26:11	ga_ls7e_ard_3-0-0_091085_2018-07-04_final
2019-01-09 09:39:24	ga_ls7e_ard_3-0-0_095067_2019-01-09_final
2019-01-11 09:30:34	ga_ls7e_ard_3-0-0_093076_2019-01-11_final
2019-05-17 09:35:05	ga_ls7e_ard_3-0-0_095067_2019-05-17_final
2019-05-19 09:25:26	ga_ls7e_ard_3-0-0_093074_2019-05-18_final
2019-05-19 09:25:50	ga_ls7e_ard_3-0-0_093075_2019-05-18_final
2019-05-19 09:26:14	ga_ls7e_ard_3-0-0_093076_2019-05-18_final
2019-05-21 09:14:59	ga_ls7e_ard_3-0-0_091079_2019-05-20_final
2019-05-21 09:15:23	ga_ls7e_ard_3-0-0_091080_2019-05-20_final
2019-05-21 09:15:47	ga_ls7e_ard_3-0-0_091081_2019-05-20_final
2019-05-21 09:16:11	ga_ls7e_ard_3-0-0_091082_2019-05-20_final
2019-05-21 09:16:35	ga_ls7e_ard_3-0-0_091083_2019-05-20_final
2019-05-21 09:16:59	ga_ls7e_ard_3-0-0_091084_2019-05-20_final
2019-05-21 09:17:23	ga_ls7e_ard_3-0-0_091085_2019-05-20_final
2019-06-27 09:27:24	ga_ls7e_ard_3-1-0_094067_2019-06-26_final
2019-06-29 09:18:09	ga_ls7e_ard_3-0-0_092075_2019-06-28_final
2019-06-29 09:18:33	ga_ls7e_ard_3-0-0_092076_2019-06-28_final
2019-06-29 09:18:57	ga_ls7e_ard_3-0-0_092077_2019-06-28_final
2019-06-29 09:19:21	ga_ls7e_ard_3-0-0_092078_2019-06-28_final
2019-06-29 09:19:45	ga_ls7e_ard_3-0-0_092079_2019-06-28_final
2019-06-29 09:20:09	ga_ls7e_ard_3-0-0_092080_2019-06-28_final
2019-06-29 09:20:33	ga_ls7e_ard_3-0-0_092081_2019-06-28_final
2019-07-01 09:08:55	ga_ls7e_ard_3-0-0_090083_2019-06-30_final
2019-07-01 09:09:19	ga_ls7e_ard_3-0-0_090084_2019-06-30_final
2019-07-01 09:09:43	ga_ls7e_ard_3-1-0_090085_2019-06-30_final
2019-07-01 09:10:07	ga_ls7e_ard_3-0-0_090086_2019-06-30_final
2019-09-03 09:06:18	ga_ls7e_ard_3-1-0_090083_2019-09-02_final
2019-09-03 09:06:42	ga_ls7e_ard_3-1-0_090084_2019-09-02_final
2019-09-03 09:07:06	ga_ls7e_ard_3-1-0_090085_2019-09-02_final
2019-09-03 09:07:30	ga_ls7e_ard_3-1-0_090086_2019-09-02_final
2019-09-03 09:08:18	ga_ls7e_ard_3-1-0_090088_2019-09-02_final
2019-09-03 09:08:42	ga_ls7e_ard_3-1-0_090089_2019-09-02_final
2019-09-06 09:30:41	ga_ls7e_ard_3-1-0_095067_2019-09-06_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
2019-12-11 09:26:23	ga_ls7e_ard_3-1-0_095067_2019-12-10_final
2019-12-13 09:16:43	ga_ls7e_ard_3-1-0_093074_2019-12-12_final
2019-12-13 09:17:07	ga_ls7e_ard_3-1-0_093075_2019-12-12_final
2019-12-13 09:17:31	ga_ls7e_ard_3-1-0_093076_2019-12-12_final
2019-12-15 09:06:15	ga_ls7e_ard_3-1-0_091079_2019-12-14_final
2019-12-15 09:06:39	ga_ls7e_ard_3-1-0_091080_2019-12-14_final
2019-12-15 09:07:03	ga_ls7e_ard_3-1-0_091081_2019-12-14_final
2019-12-15 09:07:27	ga_ls7e_ard_3-1-0_091082_2019-12-14_final
2019-12-15 09:07:51	ga_ls7e_ard_3-1-0_091083_2019-12-14_final
2019-12-15 09:08:15	ga_ls7e_ard_3-1-0_091084_2019-12-14_final
2019-12-15 09:08:39	ga_ls7e_ard_3-1-0_091085_2019-12-14_final
2020-02-06 09:17:19	ga_ls7e_ard_3-1-0_094067_2020-02-05_final
2020-02-08 09:08:03	ga_ls7e_ard_3-1-0_092075_2020-02-07_final
2020-02-08 09:08:51	ga_ls7e_ard_3-1-0_092077_2020-02-07_final
2020-02-08 09:09:15	ga_ls7e_ard_3-1-0_092078_2020-02-07_final
2020-02-08 09:09:39	ga_ls7e_ard_3-1-0_092079_2020-02-07_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