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
2020-10-06 09:37:17	ga_ls7e_ard_3-2-0_099076_2020-10-06_final
2021-09-18 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-18 08:49:48	ga_ls7e_ard_3-2-0_096072_2021-09-17_final
2021-09-18 08:50:59	ga_ls7e_ard_3-2-0_096075_2021-09-17_final
2021-09-18 08:53:47	ga_ls7e_ard_3-2-0_096082_2021-09-17_final
2021-09-20 08:41:39	ga_ls7e_ard_3-2-0_094083_2021-09-19_final
2021-09-20 10:17:44	ga_ls7e_ard_3-2-0_110076_2021-09-20_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-10-13 10:18:17	ga_ls7e_ard_3-2-0_111067_2021-10-13_final
2021-10-13 10:23:52	ga_ls7e_ard_3-2-0_111081_2021-10-13_final
2021-10-13 10:24:40	ga_ls7e_ard_3-2-0_111083_2021-10-13_final
2021-10-15 10:07:44	ga_ls7e_ard_3-2-0_109072_2021-10-15_final
2021-10-17 09:56:48	ga_ls7e_ard_3-2-0_107076_2021-10-17_final
2021-10-17 09:58:47	ga_ls7e_ard_3-2-0_107081_2021-10-17_final
2021-10-26 09:50:36	ga_ls7e_ard_3-2-0_106078_2021-10-26_final
2021-10-28 09:36:27	ga_ls7e_ard_3-2-0_104074_2021-10-28_final
2021-10-30 09:27:06	ga_ls7e_ard_3-2-0_102082_2021-10-29_final
2021-10-31 08:29:48	ga_ls7e_ard_3-2-0_093078_2021-10-30_final
2021-10-31 08:32:11	ga_ls7e_ard_3-2-0_093084_2021-10-30_final
2021-11-02 08:20:26	ga_ls7e_ard_3-2-0_091086_2021-11-01_final
2021-11-02 09:53:44	ga_ls7e_ard_3-2-0_107072_2021-11-02_final
2021-11-05 08:48:16	ga_ls7e_ard_3-2-0_096079_2021-11-04_final
2021-11-05 08:49:03	ga_ls7e_ard_3-2-0_096081_2021-11-04_final
2021-11-05 08:49:51	ga_ls7e_ard_3-2-0_096083_2021-11-04_final
2021-11-13 09:34:08	ga_ls7e_ard_3-2-1_104072_2021-11-13_final
2021-11-14 08:42:00	ga_ls7e_ard_3-2-1_095081_2021-11-13_final
2021-11-16 10:07:08	ga_ls7e_ard_3-2-1_109078_2021-11-16_final
2021-11-19 10:37:20	ga_ls7e_ard_3-2-1_114077_2021-11-19_final
2021-11-21 08:48:18	ga_ls7e_ard_3-2-1_096083_2021-11-20_final
2021-11-21 10:26:47	ga_ls7e_ard_3-2-1_112082_2021-11-21_final
2021-11-22 09:26:40	ga_ls7e_ard_3-2-1_103071_2021-11-21_final
2021-12-06 09:40:31	ga_ls7e_ard_3-2-1_105078_2021-12-06_final
2021-12-07 08:44:48	ga_ls7e_ard_3-2-1_096078_2021-12-06_final
2021-12-09 10:11:55	ga_ls7e_ard_3-2-1_110080_2021-12-09_final
2021-12-09 10:13:07	ga_ls7e_ard_3-2-1_110083_2021-12-09_final
2021-12-10 09:17:01	ga_ls7e_ard_3-2-1_101082_2021-12-09_final
2021-12-13 09:46:49	ga_ls7e_ard_3-2-1_106080_2021-12-13_final
2021-12-14 08:48:43	ga_ls7e_ard_3-2-1_097074_2021-12-13_final
2021-12-14 08:51:07	ga_ls7e_ard_3-2-1_097080_2021-12-13_final
2021-12-14 10:28:23	ga_ls7e_ard_3-2-1_113076_2021-12-14_final
2021-12-20 08:13:03	ga_ls7e_ard_3-2-1_091079_2021-12-19_final
2021-12-23 08:43:39	ga_ls7e_ard_3-2-1_096079_2021-12-22_final
2021-12-25 08:33:53	ga_ls7e_ard_3-2-1_094086_2021-12-24_final
2021-12-25 10:11:10	ga_ls7e_ard_3-2-1_110082_2021-12-25_final
2022-01-01 08:38:58	ga_ls7e_ard_3-2-1_095085_2021-12-31_final
2022-01-02 09:17:44	ga_ls7e_ard_3-2-1_102074_2022-01-01_final
2022-01-02 09:20:31	ga_ls7e_ard_3-2-1_102081_2022-01-01_final
2022-01-04 09:05:10	ga_ls7e_ard_3-2-1_100074_2022-01-03_final
2022-01-08 08:43:16	ga_ls7e_ard_3-2-1_096082_2022-01-07_final
2022-01-08 10:21:44	ga_ls7e_ard_3-2-1_112081_2022-01-08_final
2022-01-12 09:55:27	ga_ls7e_ard_3-2-1_108078_2022-01-12_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-14 09:42:30	ga_ls7e_ard_3-2-1_106077_2022-01-14_final
2022-01-16 09:27:10	ga_ls7e_ard_3-2-1_104070_2022-01-15_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-17 10:15:31	ga_ls7e_ard_3-2-1_111083_2022-01-17_final
2022-01-18 09:15:25	ga_ls7e_ard_3-2-1_102072_2022-01-17_final
2022-01-19 10:00:58	ga_ls7e_ard_3-2-1_109078_2022-01-19_final
2022-01-19 10:02:34	ga_ls7e_ard_3-2-1_109082_2022-01-19_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-22 08:51:54	ga_ls7e_ard_3-2-1_098076_2022-01-21_final
2022-01-22 10:31:35	ga_ls7e_ard_3-2-1_114078_2022-01-22_final
2022-01-25 09:23:42	ga_ls7e_ard_3-2-1_103079_2022-01-24_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-28 08:15:26	ga_ls7e_ard_3-2-1_092079_2022-01-27_final
2022-01-28 08:17:50	ga_ls7e_ard_3-2-1_092085_2022-01-27_final
2022-02-01 09:26:24	ga_ls7e_ard_3-2-1_104072_2022-01-31_final
2022-02-02 08:31:53	ga_ls7e_ard_3-2-1_095075_2022-02-01_final
2022-02-02 08:32:40	ga_ls7e_ard_3-2-1_095077_2022-02-01_final
2022-02-02 08:35:52	ga_ls7e_ard_3-2-1_095085_2022-02-01_final
2022-02-04 08:21:19	ga_ls7e_ard_3-2-1_093080_2022-02-03_final
2022-02-04 08:22:30	ga_ls7e_ard_3-2-1_093083_2022-02-03_final
2022-02-06 09:47:37	ga_ls7e_ard_3-2-1_107080_2022-02-06_final
2022-02-09 08:39:44	ga_ls7e_ard_3-2-1_096081_2022-02-08_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-12 09:08:19	ga_ls7e_ard_3-2-1_101076_2022-02-11_final
2022-02-14 10:33:50	ga_ls7e_ard_3-2-1_115074_2022-02-14_final
2022-02-15 09:39:42	ga_ls7e_ard_3-2-1_106078_2022-02-15_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-16 08:44:47	ga_ls7e_ard_3-2-1_097080_2022-02-15_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-18 08:32:14	ga_ls7e_ard_3-2-1_095080_2022-02-17_final
2022-03-03 08:04:05	ga_ls7e_ard_3-2-1_090090_2022-03-02_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-13 08:34:11	ga_ls7e_ard_3-2-1_096075_2022-03-12_final
2022-03-15 10:00:06	ga_ls7e_ard_3-2-1_110074_2022-03-15_final
2022-03-17 08:11:27	ga_ls7e_ard_3-2-1_092081_2022-03-16_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-20 08:38:28	ga_ls7e_ard_3-2-1_097072_2022-03-19_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-24 09:55:51	ga_ls7e_ard_3-2-1_109081_2022-03-24_final
2022-03-26 09:43:18	ga_ls7e_ard_3-2-1_107081_2022-03-26_final
2022-03-27 10:25:16	ga_ls7e_ard_3-2-1_114078_2022-03-27_final
2022-03-28 09:26:22	ga_ls7e_ard_3-2-1_105070_2022-03-27_final
2022-03-31 08:23:41	ga_ls7e_ard_3-2-1_094084_2022-03-30_final
2022-03-31 08:24:53	ga_ls7e_ard_3-2-1_094087_2022-03-30_final
2022-04-02 08:10:44	ga_ls7e_ard_3-2-1_092083_2022-04-01_final
2022-04-02 09:44:01	ga_ls7e_ard_3-2-1_108069_2022-04-02_final
2022-04-03 08:49:54	ga_ls7e_ard_3-2-1_099073_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years