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
2019-03-23 09:35:18	ga_ls7e_ard_3-1-0_094078_2019-03-23_final
2019-03-23 09:35:42	ga_ls7e_ard_3-1-0_094079_2019-03-23_final
2019-03-23 09:36:06	ga_ls7e_ard_3-1-0_094080_2019-03-23_final
2019-03-23 09:36:30	ga_ls7e_ard_3-1-0_094081_2019-03-23_final
2019-03-23 09:36:54	ga_ls7e_ard_3-1-0_094082_2019-03-23_final
2019-03-23 09:37:18	ga_ls7e_ard_3-1-0_094083_2019-03-23_final
2019-03-25 09:26:28	ga_ls7e_ard_3-1-0_092087_2019-03-24_final
2019-03-25 09:26:52	ga_ls7e_ard_3-1-0_092088_2019-03-24_final
2019-04-24 09:35:22	ga_ls7e_ard_3-0-0_094081_2019-04-24_final
2019-04-24 09:35:46	ga_ls7e_ard_3-0-0_094082_2019-04-24_final
2019-04-24 09:36:10	ga_ls7e_ard_3-0-0_094083_2019-04-24_final
2019-04-26 09:24:32	ga_ls7e_ard_3-0-0_092085_2019-04-25_final
2019-04-26 09:24:56	ga_ls7e_ard_3-0-0_092086_2019-04-25_final
2019-04-26 09:25:20	ga_ls7e_ard_3-0-0_092087_2019-04-25_final
2019-04-26 09:25:44	ga_ls7e_ard_3-0-0_092088_2019-04-25_final
2019-04-26 09:26:08	ga_ls7e_ard_3-0-0_092089_2019-04-25_final
2019-09-15 09:28:30	ga_ls7e_ard_3-1-0_094078_2019-09-14_final
2019-09-15 09:28:54	ga_ls7e_ard_3-1-0_094079_2019-09-14_final
2019-09-15 09:29:18	ga_ls7e_ard_3-1-0_094080_2019-09-14_final
2019-09-15 09:29:42	ga_ls7e_ard_3-1-0_094081_2019-09-14_final
2019-09-15 09:30:30	ga_ls7e_ard_3-1-0_094083_2019-09-15_final
2019-09-17 09:18:51	ga_ls7e_ard_3-1-0_092085_2019-09-16_final
2019-09-17 09:19:15	ga_ls7e_ard_3-1-0_092086_2019-09-16_final
2019-09-17 09:19:39	ga_ls7e_ard_3-1-0_092087_2019-09-16_final
2019-09-17 09:20:03	ga_ls7e_ard_3-1-0_092088_2019-09-16_final
2019-09-17 09:20:27	ga_ls7e_ard_3-1-0_092089_2019-09-16_final
2019-09-20 09:43:38	ga_ls7e_ard_3-1-0_097070_2019-09-20_final
2019-09-22 09:32:22	ga_ls7e_ard_3-1-0_095073_2019-09-22_final
2019-09-22 09:32:46	ga_ls7e_ard_3-1-0_095074_2019-09-22_final
2019-09-22 09:33:10	ga_ls7e_ard_3-1-0_095075_2019-09-22_final
2019-09-22 09:33:34	ga_ls7e_ard_3-1-0_095076_2019-09-22_final
2019-09-22 09:33:58	ga_ls7e_ard_3-1-0_095077_2019-09-22_final
2019-09-22 09:34:22	ga_ls7e_ard_3-1-0_095078_2019-09-22_final
2019-09-22 09:34:46	ga_ls7e_ard_3-1-0_095079_2019-09-22_final
2019-10-19 09:18:18	ga_ls7e_ard_3-1-0_092087_2019-10-18_final
2019-10-19 09:18:42	ga_ls7e_ard_3-1-0_092088_2019-10-18_final
2019-11-18 09:25:43	ga_ls7e_ard_3-1-0_094078_2019-11-17_final
2019-11-18 09:26:07	ga_ls7e_ard_3-1-0_094079_2019-11-17_final
2019-11-18 09:26:31	ga_ls7e_ard_3-1-0_094080_2019-11-17_final
2019-11-18 09:26:55	ga_ls7e_ard_3-1-0_094081_2019-11-17_final
2019-11-18 09:27:19	ga_ls7e_ard_3-1-0_094082_2019-11-17_final
2019-11-18 09:27:43	ga_ls7e_ard_3-1-0_094083_2019-11-17_final
2019-11-20 09:16:03	ga_ls7e_ard_3-1-0_092085_2019-11-19_final
2019-11-20 09:16:27	ga_ls7e_ard_3-1-0_092086_2019-11-19_final
2019-11-20 09:16:51	ga_ls7e_ard_3-1-0_092087_2019-11-19_final
2019-11-20 09:17:39	ga_ls7e_ard_3-1-0_092089_2019-11-19_final
2019-11-23 09:40:26	ga_ls7e_ard_3-1-0_097069_2019-11-23_final
2019-11-23 09:40:50	ga_ls7e_ard_3-1-0_097070_2019-11-23_final
2019-11-25 09:29:34	ga_ls7e_ard_3-1-0_095073_2019-11-24_final
2019-11-25 09:29:58	ga_ls7e_ard_3-1-0_095074_2019-11-24_final
2019-11-25 09:30:22	ga_ls7e_ard_3-1-0_095075_2019-11-25_final
2019-11-25 09:30:46	ga_ls7e_ard_3-1-0_095076_2019-11-25_final
2019-11-25 09:31:10	ga_ls7e_ard_3-1-0_095077_2019-11-25_final
2019-11-25 09:31:34	ga_ls7e_ard_3-1-0_095078_2019-11-25_final
2019-11-25 09:31:58	ga_ls7e_ard_3-1-0_095079_2019-11-25_final
2019-11-27 09:20:42	ga_ls7e_ard_3-1-0_093082_2019-11-26_final
2019-11-27 09:21:06	ga_ls7e_ard_3-1-0_093083_2019-11-26_final
2019-11-27 09:21:30	ga_ls7e_ard_3-1-0_093084_2019-11-26_final
2019-11-27 09:21:54	ga_ls7e_ard_3-1-0_093085_2019-11-26_final
2019-11-27 09:22:18	ga_ls7e_ard_3-1-0_093086_2019-11-26_final
2019-11-29 09:11:02	ga_ls7e_ard_3-1-0_091089_2019-11-28_final
2019-11-29 09:11:26	ga_ls7e_ard_3-1-0_091090_2019-11-28_final
2020-09-03 08:59:46	ga_ls7e_ard_3-1-0_092085_2020-09-02_final
2020-09-03 09:00:10	ga_ls7e_ard_3-1-0_092086_2020-09-02_final
2020-09-03 09:00:34	ga_ls7e_ard_3-1-0_092087_2020-09-02_final
2020-09-03 09:01:22	ga_ls7e_ard_3-1-0_092089_2020-09-02_final
2020-09-06 09:24:29	ga_ls7e_ard_3-1-0_097070_2020-09-05_final
2020-09-08 09:14:23	ga_ls7e_ard_3-1-0_095076_2020-09-07_final
2020-09-08 09:14:47	ga_ls7e_ard_3-1-0_095077_2020-09-07_final
2020-09-08 09:15:11	ga_ls7e_ard_3-1-0_095078_2020-09-07_final
2020-09-08 09:15:35	ga_ls7e_ard_3-1-0_095079_2020-09-07_final
2020-09-10 09:04:41	ga_ls7e_ard_3-1-0_093083_2020-09-09_final
2020-09-10 09:05:53	ga_ls7e_ard_3-1-0_093086_2020-09-09_final
2020-09-10 09:06:17	ga_ls7e_ard_3-1-0_093087_2020-09-09_final
2020-09-12 08:54:59	ga_ls7e_ard_3-1-0_091090_2020-09-11_final
2020-12-04 09:12:20	ga_ls7e_ard_3-1-0_096070_2020-12-03_final
2020-12-04 09:12:44	ga_ls7e_ard_3-1-0_096071_2020-12-03_final
2020-12-04 09:13:07	ga_ls7e_ard_3-1-0_096072_2020-12-03_final
2020-12-04 09:13:31	ga_ls7e_ard_3-1-0_096073_2020-12-03_final
2020-12-04 09:13:55	ga_ls7e_ard_3-1-0_096074_2020-12-03_final
2020-12-04 09:14:19	ga_ls7e_ard_3-1-0_096075_2020-12-03_final
2020-12-06 09:03:01	ga_ls7e_ard_3-1-0_094078_2020-12-05_final
2020-12-06 09:03:25	ga_ls7e_ard_3-1-0_094079_2020-12-05_final
2020-12-06 09:03:49	ga_ls7e_ard_3-1-0_094080_2020-12-05_final
2020-12-06 09:04:12	ga_ls7e_ard_3-1-0_094081_2020-12-05_final
2020-12-06 09:04:36	ga_ls7e_ard_3-1-0_094082_2020-12-05_final
2020-12-06 09:05:00	ga_ls7e_ard_3-1-0_094083_2020-12-05_final
2021-03-07 08:42:10	ga_ls7e_ard_3-2-0_091089_2021-03-06_final
2021-03-07 08:42:34	ga_ls7e_ard_3-2-0_091090_2021-03-06_final
2021-03-12 08:55:55	ga_ls7e_ard_3-2-0_094078_2021-03-11_final
2021-03-12 08:56:19	ga_ls7e_ard_3-2-0_094079_2021-03-11_final
2021-03-12 08:56:43	ga_ls7e_ard_3-2-0_094080_2021-03-11_final
2021-03-12 08:57:07	ga_ls7e_ard_3-2-0_094081_2021-03-11_final
2021-03-12 08:57:31	ga_ls7e_ard_3-2-0_094082_2021-03-11_final
2021-03-12 08:57:55	ga_ls7e_ard_3-2-0_094083_2021-03-11_final
2021-03-12 08:58:19	ga_ls7e_ard_3-2-0_094084_2021-03-11_final
2021-03-14 08:46:12	ga_ls7e_ard_3-2-0_092085_2021-03-13_final
2021-03-14 08:46:36	ga_ls7e_ard_3-2-0_092086_2021-03-13_final
2021-03-14 08:47:00	ga_ls7e_ard_3-2-0_092087_2021-03-13_final
2021-03-14 08:47:24	ga_ls7e_ard_3-2-0_092088_2021-03-13_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

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

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