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:

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First 100 results (query limit)

Time (local)	Label
2021-12-29 08:06:22	ga_ls7e_ard_3-2-1_090080_2021-12-28_final
2022-01-12 08:15:22	ga_ls7e_ard_3-2-1_092075_2022-01-11_final
2022-01-14 08:02:50	ga_ls7e_ard_3-2-1_090075_2022-01-13_final
2022-01-14 08:03:38	ga_ls7e_ard_3-2-1_090077_2022-01-13_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 08:04:49	ga_ls7e_ard_3-2-1_090080_2022-01-13_final
2022-01-14 08:05:13	ga_ls7e_ard_3-2-1_090081_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
2022-01-21 08:08:44	ga_ls7e_ard_3-2-1_091076_2022-01-20_final
2022-01-21 08:09:08	ga_ls7e_ard_3-2-1_091077_2022-01-20_final
2022-01-21 08:09:32	ga_ls7e_ard_3-2-1_091078_2022-01-20_final
2022-01-21 08:09:56	ga_ls7e_ard_3-2-1_091079_2022-01-20_final
2022-01-23 07:56:35	ga_ls7e_ard_3-2-1_089077_2022-01-22_final
2022-01-23 07:56:59	ga_ls7e_ard_3-2-1_089078_2022-01-22_final
2022-01-23 07:57:23	ga_ls7e_ard_3-2-1_089079_2022-01-22_final
2022-01-23 07:57:47	ga_ls7e_ard_3-2-1_089080_2022-01-22_final
2022-01-23 07:58:11	ga_ls7e_ard_3-2-1_089081_2022-01-22_final
2022-01-23 07:58:35	ga_ls7e_ard_3-2-1_089082_2022-01-22_final
2022-01-23 07:58:59	ga_ls7e_ard_3-2-1_089083_2022-01-22_final
2022-01-23 07:59:23	ga_ls7e_ard_3-2-1_089084_2022-01-22_final
2022-01-28 08:13:50	ga_ls7e_ard_3-2-1_092075_2022-01-27_final
2022-01-30 08:02:28	ga_ls7e_ard_3-2-1_090078_2022-01-29_final
2022-01-30 08:04:28	ga_ls7e_ard_3-2-1_090083_2022-01-29_final
2022-02-06 08:07:09	ga_ls7e_ard_3-2-1_091076_2022-02-05_final
2022-02-06 08:07:33	ga_ls7e_ard_3-2-1_091077_2022-02-05_final
2022-02-06 08:07:57	ga_ls7e_ard_3-2-1_091078_2022-02-05_final
2022-02-06 08:08:21	ga_ls7e_ard_3-2-1_091079_2022-02-05_final
2022-02-08 07:54:59	ga_ls7e_ard_3-2-1_089077_2022-02-07_final
2022-02-08 07:55:23	ga_ls7e_ard_3-2-1_089078_2022-02-07_final
2022-02-08 07:55:47	ga_ls7e_ard_3-2-1_089079_2022-02-07_final
2022-02-08 07:56:11	ga_ls7e_ard_3-2-1_089080_2022-02-07_final
2022-02-08 07:56:35	ga_ls7e_ard_3-2-1_089081_2022-02-07_final
2022-02-08 07:56:59	ga_ls7e_ard_3-2-1_089082_2022-02-07_final
2022-02-08 07:57:23	ga_ls7e_ard_3-2-1_089083_2022-02-07_final
2022-02-08 07:57:47	ga_ls7e_ard_3-2-1_089084_2022-02-07_final
2022-02-08 07:58:11	ga_ls7e_ard_3-2-1_089085_2022-02-07_final
2022-02-08 07:58:35	ga_ls7e_ard_3-2-1_089086_2022-02-07_final
2022-02-13 08:12:12	ga_ls7e_ard_3-2-1_092075_2022-02-12_final
2022-02-15 08:00:26	ga_ls7e_ard_3-2-1_090077_2022-02-14_final
2022-02-15 08:00:50	ga_ls7e_ard_3-2-1_090078_2022-02-14_final
2022-02-15 08:01:14	ga_ls7e_ard_3-2-1_090079_2022-02-14_final
2022-02-15 08:01:38	ga_ls7e_ard_3-2-1_090080_2022-02-14_final
2022-02-15 08:02:01	ga_ls7e_ard_3-2-1_090081_2022-02-14_final
2022-02-15 08:02:25	ga_ls7e_ard_3-2-1_090082_2022-02-14_final
2022-02-15 08:02:49	ga_ls7e_ard_3-2-1_090083_2022-02-14_final
2022-02-22 08:05:33	ga_ls7e_ard_3-2-1_091076_2022-02-21_final
2022-02-22 08:05:57	ga_ls7e_ard_3-2-1_091077_2022-02-21_final
2022-02-22 08:06:21	ga_ls7e_ard_3-2-1_091078_2022-02-21_final
2022-02-22 08:06:44	ga_ls7e_ard_3-2-1_091079_2022-02-21_final
2022-03-01 08:10:39	ga_ls7e_ard_3-2-1_092075_2022-02-28_final
2022-03-03 07:58:06	ga_ls7e_ard_3-2-1_090075_2022-03-02_final
2022-03-03 07:58:30	ga_ls7e_ard_3-2-1_090076_2022-03-02_final
2022-03-03 07:58:54	ga_ls7e_ard_3-2-1_090077_2022-03-02_final
2022-03-03 07:59:18	ga_ls7e_ard_3-2-1_090078_2022-03-02_final
2022-03-03 07:59:42	ga_ls7e_ard_3-2-1_090079_2022-03-02_final
2022-03-03 08:00:06	ga_ls7e_ard_3-2-1_090080_2022-03-02_final
2022-03-03 08:00:30	ga_ls7e_ard_3-2-1_090081_2022-03-02_final
2022-03-03 08:00:54	ga_ls7e_ard_3-2-1_090082_2022-03-02_final
2022-03-03 08:01:18	ga_ls7e_ard_3-2-1_090083_2022-03-02_final
2022-03-10 08:04:23	ga_ls7e_ard_3-2-1_091077_2022-03-09_final
2022-03-10 08:04:47	ga_ls7e_ard_3-2-1_091078_2022-03-09_final
2022-03-10 08:05:11	ga_ls7e_ard_3-2-1_091079_2022-03-09_final
2022-03-12 07:51:49	ga_ls7e_ard_3-2-1_089077_2022-03-11_final
2022-03-12 07:52:13	ga_ls7e_ard_3-2-1_089078_2022-03-11_final
2022-03-12 07:52:37	ga_ls7e_ard_3-2-1_089079_2022-03-11_final
2022-03-12 07:53:01	ga_ls7e_ard_3-2-1_089080_2022-03-11_final
2022-03-12 07:53:25	ga_ls7e_ard_3-2-1_089081_2022-03-11_final
2022-03-12 07:53:49	ga_ls7e_ard_3-2-1_089082_2022-03-11_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-12 07:54:37	ga_ls7e_ard_3-2-1_089084_2022-03-11_final
2022-03-12 07:55:01	ga_ls7e_ard_3-2-1_089085_2022-03-11_final
2022-03-12 07:55:25	ga_ls7e_ard_3-2-1_089086_2022-03-11_final
2022-03-17 08:09:03	ga_ls7e_ard_3-2-1_092075_2022-03-16_final
2022-03-19 07:56:30	ga_ls7e_ard_3-2-1_090075_2022-03-18_final
2022-03-19 07:57:18	ga_ls7e_ard_3-2-1_090077_2022-03-18_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-19 07:58:06	ga_ls7e_ard_3-2-1_090079_2022-03-18_final
2022-03-19 07:58:30	ga_ls7e_ard_3-2-1_090080_2022-03-18_final
2022-03-19 07:58:54	ga_ls7e_ard_3-2-1_090081_2022-03-18_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-26 08:02:26	ga_ls7e_ard_3-2-1_091076_2022-03-25_final
2022-03-26 08:02:49	ga_ls7e_ard_3-2-1_091077_2022-03-25_final
2022-03-26 08:03:13	ga_ls7e_ard_3-2-1_091078_2022-03-25_final
2022-03-26 08:03:37	ga_ls7e_ard_3-2-1_091079_2022-03-25_final
2022-03-28 07:50:40	ga_ls7e_ard_3-2-1_089078_2022-03-27_final
2022-03-28 07:51:52	ga_ls7e_ard_3-2-1_089081_2022-03-27_final
2022-03-28 07:52:16	ga_ls7e_ard_3-2-1_089082_2022-03-27_final
2022-03-28 07:52:40	ga_ls7e_ard_3-2-1_089083_2022-03-27_final
2022-03-28 07:53:04	ga_ls7e_ard_3-2-1_089084_2022-03-27_final
2022-03-28 07:53:52	ga_ls7e_ard_3-2-1_089086_2022-03-27_final
2022-04-02 08:07:32	ga_ls7e_ard_3-2-1_092075_2022-04-01_final
2022-04-04 07:54:58	ga_ls7e_ard_3-2-1_090075_2022-04-03_final
2022-04-04 07:55:46	ga_ls7e_ard_3-2-1_090077_2022-04-03_final
2022-04-04 07:56:10	ga_ls7e_ard_3-2-1_090078_2022-04-03_final
2022-04-04 07:56:34	ga_ls7e_ard_3-2-1_090079_2022-04-03_final
2022-04-04 07:56:58	ga_ls7e_ard_3-2-1_090080_2022-04-03_final
2022-04-04 07:57:22	ga_ls7e_ard_3-2-1_090081_2022-04-03_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_2022-04-03_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