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
2021-09-18 08:54:59	ga_ls7e_ard_3-2-0_096085_2021-09-17_final
2021-09-20 08:41:39	ga_ls7e_ard_3-2-0_094083_2021-09-19_final
2021-09-20 10:16:32	ga_ls7e_ard_3-2-0_110073_2021-09-20_final
2021-10-09 10:48:08	ga_ls7e_ard_3-2-0_115079_2021-10-09_final
2021-10-14 09:24:34	ga_ls7e_ard_3-2-0_102072_2021-10-13_final
2021-10-15 08:31:15	ga_ls7e_ard_3-2-0_093078_2021-10-14_final
2021-10-17 08:18:19	ga_ls7e_ard_3-2-0_091077_2021-10-16_final
2021-10-17 09:56:00	ga_ls7e_ard_3-2-0_107074_2021-10-17_final
2021-10-26 08:16:06	ga_ls7e_ard_3-2-0_090089_2021-10-25_final
2021-10-26 09:48:36	ga_ls7e_ard_3-2-0_106073_2021-10-26_final
2021-10-27 08:53:17	ga_ls7e_ard_3-2-0_097074_2021-10-26_final
2021-10-27 10:32:34	ga_ls7e_ard_3-2-0_113075_2021-10-27_final
2021-10-29 10:20:01	ga_ls7e_ard_3-2-0_111075_2021-10-29_final
2021-10-30 09:21:55	ga_ls7e_ard_3-2-0_102069_2021-10-29_final
2021-10-30 09:22:43	ga_ls7e_ard_3-2-0_102071_2021-10-29_final
2021-10-31 08:28:36	ga_ls7e_ard_3-2-0_093075_2021-10-30_final
2021-11-02 08:18:27	ga_ls7e_ard_3-2-0_091081_2021-11-01_final
2021-11-02 08:20:50	ga_ls7e_ard_3-2-0_091087_2021-11-01_final
2021-11-03 08:57:37	ga_ls7e_ard_3-2-0_098071_2021-11-02_final
2021-11-03 09:01:36	ga_ls7e_ard_3-2-0_098081_2021-11-02_final
2021-11-04 09:44:22	ga_ls7e_ard_3-2-0_105080_2021-11-04_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-10 10:44:00	ga_ls7e_ard_3-2-0_115076_2021-11-10_final
2021-11-10 10:44:24	ga_ls7e_ard_3-2-0_115077_2021-11-10_final
2021-11-12 10:33:26	ga_ls7e_ard_3-2-1_113081_2021-11-12_final
2021-11-13 09:35:44	ga_ls7e_ard_3-2-1_104076_2021-11-13_final
2021-11-14 10:20:53	ga_ls7e_ard_3-2-1_111081_2021-11-14_final
2021-11-16 10:05:08	ga_ls7e_ard_3-2-1_109073_2021-11-16_final
2021-11-18 08:17:42	ga_ls7e_ard_3-2-1_091083_2021-11-17_final
2021-11-19 08:56:04	ga_ls7e_ard_3-2-1_098071_2021-11-18_final
2021-11-21 10:26:47	ga_ls7e_ard_3-2-1_112082_2021-11-21_final
2021-11-25 10:00:52	ga_ls7e_ard_3-2-1_108080_2021-11-25_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-12-05 10:36:14	ga_ls7e_ard_3-2-1_114078_2021-12-05_final
2021-12-08 09:24:46	ga_ls7e_ard_3-2-1_103070_2021-12-07_final
2021-12-08 09:26:22	ga_ls7e_ard_3-2-1_103074_2021-12-07_final
2021-12-09 10:12:43	ga_ls7e_ard_3-2-1_110082_2021-12-09_final
2021-12-12 09:04:51	ga_ls7e_ard_3-2-1_099083_2021-12-11_final
2021-12-13 08:07:57	ga_ls7e_ard_3-2-1_090080_2021-12-12_final
2021-12-13 08:09:09	ga_ls7e_ard_3-2-1_090083_2021-12-12_final
2021-12-14 08:51:07	ga_ls7e_ard_3-2-1_097080_2021-12-13_final
2021-12-18 08:23:37	ga_ls7e_ard_3-2-1_093074_2021-12-17_final
2021-12-21 10:33:06	ga_ls7e_ard_3-2-1_114074_2021-12-21_final
2022-01-01 10:12:15	ga_ls7e_ard_3-2-1_111071_2022-01-01_final
2022-01-03 08:23:12	ga_ls7e_ard_3-2-1_093077_2022-01-02_final
2022-01-05 08:10:15	ga_ls7e_ard_3-2-1_091076_2022-01-04_final
2022-01-06 08:54:36	ga_ls7e_ard_3-2-1_098079_2022-01-05_final
2022-01-07 09:34:59	ga_ls7e_ard_3-2-1_105072_2022-01-07_final
2022-01-08 10:19:45	ga_ls7e_ard_3-2-1_112076_2022-01-08_final
2022-01-12 08:15:46	ga_ls7e_ard_3-2-1_092076_2022-01-11_final
2022-01-13 08:57:45	ga_ls7e_ard_3-2-1_099073_2022-01-12_final
2022-01-15 08:47:35	ga_ls7e_ard_3-2-1_097079_2022-01-14_final
2022-01-15 10:27:16	ga_ls7e_ard_3-2-1_113081_2022-01-15_final
2022-01-22 08:51:06	ga_ls7e_ard_3-2-1_098074_2022-01-21_final
2022-01-23 09:32:40	ga_ls7e_ard_3-2-1_105070_2022-01-23_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-30 09:43:21	ga_ls7e_ard_3-2-1_106083_2022-01-30_final
2022-01-31 10:24:31	ga_ls7e_ard_3-2-1_113078_2022-01-31_final
2022-02-02 08:31:53	ga_ls7e_ard_3-2-1_095075_2022-02-01_final
2022-02-02 08:36:16	ga_ls7e_ard_3-2-1_095086_2022-02-01_final
2022-02-06 09:44:50	ga_ls7e_ard_3-2-1_107073_2022-02-06_final
2022-02-06 09:45:14	ga_ls7e_ard_3-2-1_107074_2022-02-06_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-08 09:34:39	ga_ls7e_ard_3-2-1_105079_2022-02-08_final
2022-02-11 10:06:27	ga_ls7e_ard_3-2-1_110082_2022-02-11_final
2022-02-13 09:49:05	ga_ls7e_ard_3-2-1_108070_2022-02-13_final
2022-02-15 09:37:19	ga_ls7e_ard_3-2-1_106072_2022-02-15_final
2022-02-15 09:39:42	ga_ls7e_ard_3-2-1_106078_2022-02-15_final
2022-02-16 08:44:23	ga_ls7e_ard_3-2-1_097079_2022-02-15_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-23 08:51:30	ga_ls7e_ard_3-2-1_098083_2022-02-22_final
2022-02-23 10:27:59	ga_ls7e_ard_3-2-1_114077_2022-02-23_final
2022-02-24 09:33:52	ga_ls7e_ard_3-2-1_105081_2022-02-24_final
2022-02-25 08:39:21	ga_ls7e_ard_3-2-1_096084_2022-02-24_final
2022-02-27 10:02:05	ga_ls7e_ard_3-2-1_110075_2022-02-27_final
2022-02-27 10:02:53	ga_ls7e_ard_3-2-1_110077_2022-02-27_final
2022-03-06 10:10:23	ga_ls7e_ard_3-2-1_111082_2022-03-06_final
2022-03-09 08:58:54	ga_ls7e_ard_3-2-1_100074_2022-03-08_final
2022-03-10 08:05:35	ga_ls7e_ard_3-2-1_091080_2022-03-09_final
2022-03-11 08:47:09	ga_ls7e_ard_3-2-1_098076_2022-03-10_final
2022-03-11 08:48:21	ga_ls7e_ard_3-2-1_098079_2022-03-10_final
2022-03-13 08:33:23	ga_ls7e_ard_3-2-1_096073_2022-03-12_final
2022-03-13 08:38:34	ga_ls7e_ard_3-2-1_096086_2022-03-12_final
2022-03-14 09:15:45	ga_ls7e_ard_3-2-1_103071_2022-03-13_final
2022-03-18 10:30:41	ga_ls7e_ard_3-2-1_115074_2022-03-18_final
2022-03-18 10:31:53	ga_ls7e_ard_3-2-1_115077_2022-03-18_final
2022-03-22 08:26:43	ga_ls7e_ard_3-2-1_095074_2022-03-21_final
2022-03-24 08:14:34	ga_ls7e_ard_3-2-1_093075_2022-03-23_final
2022-03-24 09:52:39	ga_ls7e_ard_3-2-1_109073_2022-03-24_final
2022-03-26 08:02:26	ga_ls7e_ard_3-2-1_091076_2022-03-25_final
2022-03-26 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-27 08:47:11	ga_ls7e_ard_3-2-1_098080_2022-03-26_final
2022-03-28 09:25:58	ga_ls7e_ard_3-2-1_105069_2022-03-27_final
2022-04-02 09:45:37	ga_ls7e_ard_3-2-1_108073_2022-04-02_final
2022-04-05 08:36:56	ga_ls7e_ard_3-2-1_097072_2022-04-04_final
2022-04-05 08:40:08	ga_ls7e_ard_3-2-1_097080_2022-04-04_final
2022-04-05 10:19:00	ga_ls7e_ard_3-2-1_113080_2022-04-05_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