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
2021-09-06 10:03:49	ga_ls7e_ard_3-2-0_108069_2021-09-06_final
2021-09-08 09:51:17	ga_ls7e_ard_3-2-0_106069_2021-09-08_final
2021-09-12 09:27:48	ga_ls7e_ard_3-2-0_102073_2021-09-11_final
2021-09-18 08:54:35	ga_ls7e_ard_3-2-0_096084_2021-09-17_final
2021-09-18 10:29:28	ga_ls7e_ard_3-2-0_112074_2021-09-18_final
2021-09-20 10:15:44	ga_ls7e_ard_3-2-0_110071_2021-09-20_final
2021-09-24 08:18:58	ga_ls7e_ard_3-2-0_090089_2021-09-23_final
2021-09-27 08:42:48	ga_ls7e_ard_3-2-0_095072_2021-09-26_final
2021-10-01 08:22:31	ga_ls7e_ard_3-2-0_091084_2021-09-30_final
2021-10-02 09:00:30	ga_ls7e_ard_3-2-0_098071_2021-10-01_final
2021-10-03 09:42:29	ga_ls7e_ard_3-2-0_105068_2021-10-03_final
2021-10-06 10:15:07	ga_ls7e_ard_3-2-0_110073_2021-10-06_final
2021-10-08 08:28:53	ga_ls7e_ard_3-2-0_092086_2021-10-07_final
2021-10-10 09:50:26	ga_ls7e_ard_3-2-0_106074_2021-10-10_final
2021-10-14 09:23:22	ga_ls7e_ard_3-2-0_102069_2021-10-13_final
2021-10-17 08:22:18	ga_ls7e_ard_3-2-0_091087_2021-10-16_final
2021-10-17 08:23:06	ga_ls7e_ard_3-2-0_091089_2021-10-16_final
2021-10-18 08:57:54	ga_ls7e_ard_3-2-0_098068_2021-10-17_final
2021-10-18 09:02:41	ga_ls7e_ard_3-2-0_098080_2021-10-17_final
2021-10-20 08:46:09	ga_ls7e_ard_3-2-0_096070_2021-10-19_final
2021-10-22 10:13:17	ga_ls7e_ard_3-2-0_110072_2021-10-22_final
2021-10-22 10:16:52	ga_ls7e_ard_3-2-0_110081_2021-10-22_final
2021-10-24 08:23:28	ga_ls7e_ard_3-2-0_092076_2021-10-23_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-10-30 09:22:43	ga_ls7e_ard_3-2-0_102071_2021-10-29_final
2021-11-05 08:50:15	ga_ls7e_ard_3-2-0_096084_2021-11-04_final
2021-11-08 09:15:41	ga_ls7e_ard_3-2-0_101071_2021-11-07_final
2021-11-10 09:03:31	ga_ls7e_ard_3-2-0_099072_2021-11-09_final
2021-11-11 09:46:17	ga_ls7e_ard_3-2-0_106071_2021-11-11_final
2021-11-11 09:47:05	ga_ls7e_ard_3-2-0_106073_2021-11-11_final
2021-11-12 08:50:10	ga_ls7e_ard_3-2-0_097070_2021-11-11_final
2021-11-12 10:31:03	ga_ls7e_ard_3-2-1_113075_2021-11-12_final
2021-11-17 09:09:01	ga_ls7e_ard_3-2-1_100072_2021-11-16_final
2021-11-19 08:56:04	ga_ls7e_ard_3-2-1_098071_2021-11-18_final
2021-11-19 08:56:28	ga_ls7e_ard_3-2-1_098072_2021-11-18_final
2021-11-19 08:59:16	ga_ls7e_ard_3-2-1_098079_2021-11-18_final
2021-11-26 10:42:03	ga_ls7e_ard_3-2-1_115075_2021-11-26_final
2021-11-30 08:42:52	ga_ls7e_ard_3-2-1_095087_2021-11-29_final
2021-12-02 08:25:32	ga_ls7e_ard_3-2-1_093075_2021-12-01_final
2021-12-03 09:07:54	ga_ls7e_ard_3-2-1_100073_2021-12-02_final
2021-12-04 08:16:35	ga_ls7e_ard_3-2-1_091084_2021-12-03_final
2021-12-04 09:52:16	ga_ls7e_ard_3-2-1_107076_2021-12-04_final
2021-12-07 10:25:40	ga_ls7e_ard_3-2-1_112083_2021-12-07_final
2021-12-09 10:09:08	ga_ls7e_ard_3-2-1_110073_2021-12-09_final
2021-12-09 10:12:43	ga_ls7e_ard_3-2-1_110082_2021-12-09_final
2021-12-11 08:24:05	ga_ls7e_ard_3-2-1_092089_2021-12-10_final
2021-12-11 10:00:10	ga_ls7e_ard_3-2-1_108082_2021-12-11_final
2021-12-12 09:03:40	ga_ls7e_ard_3-2-1_099080_2021-12-11_final
2021-12-13 09:43:14	ga_ls7e_ard_3-2-1_106071_2021-12-13_final
2021-12-20 08:15:51	ga_ls7e_ard_3-2-1_091086_2021-12-19_final
2021-12-23 10:24:32	ga_ls7e_ard_3-2-1_112084_2021-12-23_final
2021-12-27 09:57:49	ga_ls7e_ard_3-2-1_108080_2021-12-27_final
2021-12-27 09:59:25	ga_ls7e_ard_3-2-1_108084_2021-12-27_final
2021-12-28 09:03:17	ga_ls7e_ard_3-2-1_099083_2021-12-27_final
2021-12-29 09:41:16	ga_ls7e_ard_3-2-1_106070_2021-12-29_final
2021-12-29 09:42:27	ga_ls7e_ard_3-2-1_106073_2021-12-29_final
2022-01-04 09:05:58	ga_ls7e_ard_3-2-1_100076_2022-01-03_final
2022-01-04 09:08:45	ga_ls7e_ard_3-2-1_100083_2022-01-03_final
2022-01-12 09:52:15	ga_ls7e_ard_3-2-1_108070_2022-01-12_final
2022-01-13 10:39:01	ga_ls7e_ard_3-2-1_115079_2022-01-13_final
2022-01-19 08:24:29	ga_ls7e_ard_3-2-1_093084_2022-01-18_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-21 08:12:20	ga_ls7e_ard_3-2-1_091085_2022-01-20_final
2022-01-21 08:13:08	ga_ls7e_ard_3-2-1_091087_2022-01-20_final
2022-01-21 09:50:48	ga_ls7e_ard_3-2-1_107084_2022-01-21_final
2022-01-23 09:33:04	ga_ls7e_ard_3-2-1_105071_2022-01-23_final
2022-01-25 09:21:43	ga_ls7e_ard_3-2-1_103074_2022-01-24_final
2022-01-28 08:14:14	ga_ls7e_ard_3-2-1_092076_2022-01-27_final
2022-01-28 09:55:54	ga_ls7e_ard_3-2-1_108083_2022-01-28_final
2022-01-29 08:57:00	ga_ls7e_ard_3-2-1_099075_2022-01-28_final
2022-01-29 10:37:04	ga_ls7e_ard_3-2-1_115078_2022-01-29_final
2022-01-30 08:06:52	ga_ls7e_ard_3-2-1_090089_2022-01-29_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-02-01 09:25:12	ga_ls7e_ard_3-2-1_104069_2022-01-31_final
2022-02-02 08:34:40	ga_ls7e_ard_3-2-1_095082_2022-02-01_final
2022-02-02 10:14:21	ga_ls7e_ard_3-2-1_111084_2022-02-02_final
2022-02-03 09:13:02	ga_ls7e_ard_3-2-1_102070_2022-02-02_final
2022-02-03 09:15:02	ga_ls7e_ard_3-2-1_102075_2022-02-02_final
2022-02-06 08:11:56	ga_ls7e_ard_3-2-1_091088_2022-02-05_final
2022-02-06 09:46:02	ga_ls7e_ard_3-2-1_107076_2022-02-06_final
2022-02-07 08:46:43	ga_ls7e_ard_3-2-1_098067_2022-02-06_final
2022-02-07 08:50:42	ga_ls7e_ard_3-2-1_098077_2022-02-06_final
2022-02-07 10:30:47	ga_ls7e_ard_3-2-1_114080_2022-02-07_final
2022-02-08 09:32:16	ga_ls7e_ard_3-2-1_105073_2022-02-08_final
2022-02-13 09:49:05	ga_ls7e_ard_3-2-1_108070_2022-02-13_final
2022-02-13 09:50:17	ga_ls7e_ard_3-2-1_108073_2022-02-13_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-22 08:09:32	ga_ls7e_ard_3-2-1_091086_2022-02-21_final
2022-02-25 08:39:21	ga_ls7e_ard_3-2-1_096084_2022-02-24_final
2022-03-03 08:00:06	ga_ls7e_ard_3-2-1_090080_2022-03-02_final
2022-03-04 08:39:16	ga_ls7e_ard_3-2-1_097070_2022-03-03_final
2022-03-07 09:09:28	ga_ls7e_ard_3-2-1_102069_2022-03-06_final
2022-03-07 09:09:52	ga_ls7e_ard_3-2-1_102070_2022-03-06_final
2022-03-18 08:55:24	ga_ls7e_ard_3-2-1_099083_2022-03-17_final
2022-03-20 10:21:20	ga_ls7e_ard_3-2-1_113082_2022-03-20_final
2022-03-24 09:56:39	ga_ls7e_ard_3-2-1_109083_2022-03-24_final
2022-03-26 08:02:26	ga_ls7e_ard_3-2-1_091076_2022-03-25_final
2022-04-02 08:07:32	ga_ls7e_ard_3-2-1_092075_2022-04-01_final
2022-04-02 09:48:48	ga_ls7e_ard_3-2-1_108081_2022-04-02_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