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 08:50:12	ga_ls7e_ard_3-2-0_096073_2021-09-17_final
2021-09-18 08:51:23	ga_ls7e_ard_3-2-0_096076_2021-09-17_final
2021-09-18 08:53:47	ga_ls7e_ard_3-2-0_096082_2021-09-17_final
2021-09-18 08:54:35	ga_ls7e_ard_3-2-0_096084_2021-09-17_final
2021-09-18 10:32:16	ga_ls7e_ard_3-2-0_112081_2021-09-18_final
2021-09-20 08:37:39	ga_ls7e_ard_3-2-0_094073_2021-09-19_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-10-26 09:49:48	ga_ls7e_ard_3-2-0_106076_2021-10-26_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-20 09:53:32	ga_ls7e_ard_3-2-1_107083_2021-12-20_final
2021-12-30 08:47:32	ga_ls7e_ard_3-2-1_097075_2021-12-29_final
2022-01-01 08:36:34	ga_ls7e_ard_3-2-1_095079_2021-12-31_final
2022-01-08 08:39:16	ga_ls7e_ard_3-2-1_096072_2022-01-07_final
2022-01-08 10:18:57	ga_ls7e_ard_3-2-1_112074_2022-01-08_final
2022-01-09 09:23:38	ga_ls7e_ard_3-2-1_103075_2022-01-08_final
2022-01-10 08:31:07	ga_ls7e_ard_3-2-1_094083_2022-01-09_final
2022-01-12 09:53:03	ga_ls7e_ard_3-2-1_108072_2022-01-12_final
2022-01-13 08:56:09	ga_ls7e_ard_3-2-1_099069_2022-01-12_final
2022-01-14 08:06:49	ga_ls7e_ard_3-2-1_090085_2022-01-13_final
2022-01-15 08:46:00	ga_ls7e_ard_3-2-1_097075_2022-01-14_final
2022-01-17 10:13:55	ga_ls7e_ard_3-2-1_111079_2022-01-17_final
2022-01-17 10:14:43	ga_ls7e_ard_3-2-1_111081_2022-01-17_final
2022-01-19 08:20:30	ga_ls7e_ard_3-2-1_093074_2022-01-18_final
2022-01-19 08:22:05	ga_ls7e_ard_3-2-1_093078_2022-01-18_final
2022-01-19 08:24:29	ga_ls7e_ard_3-2-1_093084_2022-01-18_final
2022-01-21 09:50:48	ga_ls7e_ard_3-2-1_107084_2022-01-21_final
2022-01-22 10:29:59	ga_ls7e_ard_3-2-1_114074_2022-01-22_final
2022-01-22 10:32:22	ga_ls7e_ard_3-2-1_114080_2022-01-22_final
2022-01-23 09:32:40	ga_ls7e_ard_3-2-1_105070_2022-01-23_final
2022-01-26 10:07:40	ga_ls7e_ard_3-2-1_110081_2022-01-26_final
2022-01-27 09:09:57	ga_ls7e_ard_3-2-1_101076_2022-01-26_final
2022-01-27 09:11:33	ga_ls7e_ard_3-2-1_101080_2022-01-26_final
2022-02-04 08:22:54	ga_ls7e_ard_3-2-1_093084_2022-02-03_final
2022-02-06 08:07:09	ga_ls7e_ard_3-2-1_091076_2022-02-05_final
2022-02-06 09:45:14	ga_ls7e_ard_3-2-1_107074_2022-02-06_final
2022-02-06 09:45:38	ga_ls7e_ard_3-2-1_107075_2022-02-06_final
2022-02-07 10:30:47	ga_ls7e_ard_3-2-1_114080_2022-02-07_final
2022-02-08 09:35:51	ga_ls7e_ard_3-2-1_105082_2022-02-08_final
2022-02-09 08:37:44	ga_ls7e_ard_3-2-1_096076_2022-02-08_final
2022-02-09 08:40:32	ga_ls7e_ard_3-2-1_096083_2022-02-08_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-12 09:07:32	ga_ls7e_ard_3-2-1_101074_2022-02-11_final
2022-02-14 08:53:22	ga_ls7e_ard_3-2-1_099070_2022-02-13_final
2022-02-14 08:57:21	ga_ls7e_ard_3-2-1_099080_2022-02-13_final
2022-02-15 08:05:13	ga_ls7e_ard_3-2-1_090089_2022-02-14_final
2022-02-15 09:37:19	ga_ls7e_ard_3-2-1_106072_2022-02-15_final
2022-02-17 09:28:21	ga_ls7e_ard_3-2-1_104081_2022-02-16_final
2022-02-18 08:30:38	ga_ls7e_ard_3-2-1_095076_2022-02-17_final
2022-02-19 09:11:25	ga_ls7e_ard_3-2-1_102070_2022-02-18_final
2022-02-19 09:11:49	ga_ls7e_ard_3-2-1_102071_2022-02-18_final
2022-02-23 08:47:07	ga_ls7e_ard_3-2-1_098072_2022-02-22_final
2022-02-26 09:21:43	ga_ls7e_ard_3-2-1_103082_2022-02-25_final
2022-02-27 08:25:12	ga_ls7e_ard_3-2-1_094080_2022-02-26_final
2022-02-27 08:26:24	ga_ls7e_ard_3-2-1_094083_2022-02-26_final
2022-02-28 09:07:34	ga_ls7e_ard_3-2-1_101078_2022-02-27_final
2022-03-01 08:13:51	ga_ls7e_ard_3-2-1_092083_2022-02-28_final
2022-03-04 08:38:52	ga_ls7e_ard_3-2-1_097069_2022-03-03_final
2022-03-04 08:39:16	ga_ls7e_ard_3-2-1_097070_2022-03-03_final
2022-03-04 08:42:51	ga_ls7e_ard_3-2-1_097079_2022-03-03_final
2022-03-04 08:43:39	ga_ls7e_ard_3-2-1_097081_2022-03-03_final
2022-03-04 10:19:44	ga_ls7e_ard_3-2-1_113074_2022-03-04_final
2022-03-08 08:18:56	ga_ls7e_ard_3-2-1_093082_2022-03-07_final
2022-03-08 09:58:13	ga_ls7e_ard_3-2-1_109083_2022-03-08_final
2022-03-09 09:02:06	ga_ls7e_ard_3-2-1_100082_2022-03-08_final
2022-03-10 08:05:59	ga_ls7e_ard_3-2-1_091081_2022-03-09_final
2022-03-10 09:40:28	ga_ls7e_ard_3-2-1_107070_2022-03-10_final
2022-03-10 09:42:28	ga_ls7e_ard_3-2-1_107075_2022-03-10_final
2022-03-10 09:44:52	ga_ls7e_ard_3-2-1_107081_2022-03-10_final
2022-03-10 09:45:39	ga_ls7e_ard_3-2-1_107083_2022-03-10_final
2022-03-13 08:32:35	ga_ls7e_ard_3-2-1_096071_2022-03-12_final
2022-03-13 08:36:59	ga_ls7e_ard_3-2-1_096082_2022-03-12_final
2022-03-14 09:18:32	ga_ls7e_ard_3-2-1_103078_2022-03-13_final
2022-03-15 08:23:13	ga_ls7e_ard_3-2-1_094079_2022-03-14_final
2022-03-17 09:45:56	ga_ls7e_ard_3-2-1_108070_2022-03-17_final
2022-03-17 09:46:44	ga_ls7e_ard_3-2-1_108072_2022-03-17_final
2022-03-17 09:51:07	ga_ls7e_ard_3-2-1_108083_2022-03-17_final
2022-03-18 08:51:48	ga_ls7e_ard_3-2-1_099074_2022-03-17_final
2022-03-18 08:54:12	ga_ls7e_ard_3-2-1_099080_2022-03-17_final
2022-03-19 09:37:46	ga_ls7e_ard_3-2-1_106081_2022-03-19_final
2022-03-20 08:39:40	ga_ls7e_ard_3-2-1_097075_2022-03-19_final
2022-03-20 08:42:27	ga_ls7e_ard_3-2-1_097082_2022-03-19_final
2022-03-23 09:09:53	ga_ls7e_ard_3-2-1_102074_2022-03-22_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-27 08:47:35	ga_ls7e_ard_3-2-1_098081_2022-03-26_final
2022-03-28 09:25:34	ga_ls7e_ard_3-2-1_105068_2022-03-27_final
2022-03-28 09:27:09	ga_ls7e_ard_3-2-1_105072_2022-03-27_final
2022-03-29 08:31:27	ga_ls7e_ard_3-2-1_096072_2022-03-28_final
2022-03-29 08:37:02	ga_ls7e_ard_3-2-1_096086_2022-03-28_final
2022-03-31 08:19:17	ga_ls7e_ard_3-2-1_094073_2022-03-30_final
2022-03-31 08:21:41	ga_ls7e_ard_3-2-1_094079_2022-03-30_final
2022-03-31 08:23:41	ga_ls7e_ard_3-2-1_094084_2022-03-30_final
2022-03-31 08:24:29	ga_ls7e_ard_3-2-1_094086_2022-03-30_final
2022-04-01 09:04:51	ga_ls7e_ard_3-2-1_101079_2022-03-31_final
2022-04-01 09:05:39	ga_ls7e_ard_3-2-1_101081_2022-03-31_final
2022-04-02 09:44:01	ga_ls7e_ard_3-2-1_108069_2022-04-02_final
2022-04-02 09:49:36	ga_ls7e_ard_3-2-1_108083_2022-04-02_final
2022-04-04 07:56:10	ga_ls7e_ard_3-2-1_090078_2022-04-03_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_2022-04-03_final
2022-04-04 09:36:15	ga_ls7e_ard_3-2-1_106081_2022-04-04_final
2022-04-05 08:38:08	ga_ls7e_ard_3-2-1_097075_2022-04-04_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