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
2021-09-05 09:21:51	ga_ls7e_ard_3-2-0_101072_2021-09-04_final
2021-09-08 08:17:36	ga_ls7e_ard_3-2-0_090082_2021-09-07_final
2021-09-08 09:55:16	ga_ls7e_ard_3-2-0_106079_2021-09-08_final
2021-09-09 08:58:46	ga_ls7e_ard_3-2-0_097077_2021-09-08_final
2021-09-11 08:45:50	ga_ls7e_ard_3-2-0_095076_2021-09-10_final
2021-09-11 08:46:14	ga_ls7e_ard_3-2-0_095077_2021-09-10_final
2021-09-11 10:25:07	ga_ls7e_ard_3-2-0_111077_2021-09-11_final
2021-09-13 08:35:17	ga_ls7e_ard_3-2-0_093081_2021-09-12_final
2021-09-20 08:40:03	ga_ls7e_ard_3-2-0_094079_2021-09-19_final
2021-09-24 08:15:46	ga_ls7e_ard_3-2-0_090081_2021-09-23_final
2021-09-25 08:56:56	ga_ls7e_ard_3-2-0_097076_2021-09-24_final
2021-09-25 08:57:20	ga_ls7e_ard_3-2-0_097077_2021-09-24_final
2021-09-27 08:44:48	ga_ls7e_ard_3-2-0_095077_2021-09-26_final
2021-10-01 09:59:00	ga_ls7e_ard_3-2-0_107078_2021-10-01_final
2021-10-06 08:39:49	ga_ls7e_ard_3-2-0_094082_2021-10-05_final
2021-10-08 08:27:41	ga_ls7e_ard_3-2-0_092083_2021-10-07_final
2021-10-08 10:04:34	ga_ls7e_ard_3-2-0_108078_2021-10-08_final
2021-10-09 09:07:40	ga_ls7e_ard_3-2-0_099075_2021-10-08_final
2021-10-10 08:14:21	ga_ls7e_ard_3-2-0_090081_2021-10-09_final
2021-10-10 09:52:02	ga_ls7e_ard_3-2-0_106078_2021-10-10_final
2021-10-13 08:42:36	ga_ls7e_ard_3-2-0_095075_2021-10-12_final
2021-10-13 08:43:00	ga_ls7e_ard_3-2-0_095076_2021-10-12_final
2021-10-13 10:23:04	ga_ls7e_ard_3-2-0_111079_2021-10-13_final
2021-10-14 09:26:10	ga_ls7e_ard_3-2-0_102076_2021-10-13_final
2021-10-17 09:57:35	ga_ls7e_ard_3-2-0_107078_2021-10-17_final
2021-10-18 09:00:17	ga_ls7e_ard_3-2-0_098074_2021-10-17_final
2021-10-19 09:45:03	ga_ls7e_ard_3-2-0_105078_2021-10-19_final
2021-10-20 10:29:01	ga_ls7e_ard_3-2-0_112080_2021-10-20_final
2021-10-23 09:18:22	ga_ls7e_ard_3-2-0_101074_2021-10-22_final
2021-10-23 09:19:10	ga_ls7e_ard_3-2-0_101076_2021-10-22_final
2021-10-23 09:21:10	ga_ls7e_ard_3-2-0_101081_2021-10-22_final
2021-10-26 08:13:43	ga_ls7e_ard_3-2-0_090083_2021-10-25_final
2021-10-27 10:33:22	ga_ls7e_ard_3-2-0_113077_2021-10-27_final
2021-10-31 10:09:28	ga_ls7e_ard_3-2-0_109080_2021-10-31_final
2021-11-02 09:54:55	ga_ls7e_ard_3-2-0_107075_2021-11-02_final
2021-11-09 10:01:38	ga_ls7e_ard_3-2-0_108078_2021-11-09_final
2021-11-12 08:52:34	ga_ls7e_ard_3-2-0_097076_2021-11-11_final
2021-11-14 08:40:25	ga_ls7e_ard_3-2-1_095077_2021-11-13_final
2021-11-14 08:40:49	ga_ls7e_ard_3-2-1_095078_2021-11-13_final
2021-11-15 09:25:34	ga_ls7e_ard_3-2-1_102082_2021-11-14_final
2021-11-19 08:58:04	ga_ls7e_ard_3-2-1_098076_2021-11-18_final
2021-11-20 09:42:01	ga_ls7e_ard_3-2-1_105078_2021-11-20_final
2021-11-23 08:33:21	ga_ls7e_ard_3-2-1_094077_2021-11-22_final
2021-11-23 08:35:44	ga_ls7e_ard_3-2-1_094083_2021-11-22_final
2021-11-28 08:51:01	ga_ls7e_ard_3-2-1_097076_2021-11-27_final
2021-11-30 08:39:16	ga_ls7e_ard_3-2-1_095078_2021-11-29_final
2021-12-01 09:22:50	ga_ls7e_ard_3-2-1_102079_2021-11-30_final
2021-12-09 08:32:39	ga_ls7e_ard_3-2-1_094079_2021-12-08_final
2021-12-09 10:11:08	ga_ls7e_ard_3-2-1_110078_2021-12-09_final
2021-12-14 10:29:35	ga_ls7e_ard_3-2-1_113079_2021-12-14_final
2021-12-23 10:22:08	ga_ls7e_ard_3-2-1_112078_2021-12-23_final
2021-12-26 09:12:40	ga_ls7e_ard_3-2-1_101075_2021-12-25_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2022-01-01 08:35:22	ga_ls7e_ard_3-2-1_095076_2021-12-31_final
2022-01-01 08:36:10	ga_ls7e_ard_3-2-1_095078_2021-12-31_final
2022-01-01 10:17:26	ga_ls7e_ard_3-2-1_111084_2022-01-01_final
2022-01-02 09:20:07	ga_ls7e_ard_3-2-1_102080_2022-01-01_final
2022-01-05 09:51:31	ga_ls7e_ard_3-2-1_107082_2022-01-05_final
2022-01-07 09:37:46	ga_ls7e_ard_3-2-1_105079_2022-01-07_final
2022-01-08 08:41:16	ga_ls7e_ard_3-2-1_096077_2022-01-07_final
2022-01-08 08:41:40	ga_ls7e_ard_3-2-1_096078_2022-01-07_final
2022-01-10 08:29:07	ga_ls7e_ard_3-2-1_094078_2022-01-09_final
2022-01-11 09:12:41	ga_ls7e_ard_3-2-1_101079_2022-01-10_final
2022-01-14 09:44:06	ga_ls7e_ard_3-2-1_106081_2022-01-14_final
2022-01-17 08:33:51	ga_ls7e_ard_3-2-1_095076_2022-01-16_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-24 08:38:33	ga_ls7e_ard_3-2-1_096074_2022-01-23_final
2022-01-31 08:44:50	ga_ls7e_ard_3-2-1_097076_2022-01-30_final
2022-01-31 08:45:14	ga_ls7e_ard_3-2-1_097077_2022-01-30_final
2022-02-04 08:22:06	ga_ls7e_ard_3-2-1_093082_2022-02-03_final
2022-02-04 10:00:11	ga_ls7e_ard_3-2-1_109080_2022-02-04_final
2022-02-06 09:46:25	ga_ls7e_ard_3-2-1_107077_2022-02-06_final
2022-02-10 09:20:30	ga_ls7e_ard_3-2-1_103075_2022-02-09_final
2022-02-11 08:25:34	ga_ls7e_ard_3-2-1_094077_2022-02-10_final
2022-02-11 08:26:22	ga_ls7e_ard_3-2-1_094079_2022-02-10_final
2022-02-12 09:10:19	ga_ls7e_ard_3-2-1_101081_2022-02-11_final
2022-02-16 08:43:35	ga_ls7e_ard_3-2-1_097077_2022-02-15_final
2022-02-17 09:24:21	ga_ls7e_ard_3-2-1_104071_2022-02-16_final
2022-02-18 08:31:02	ga_ls7e_ard_3-2-1_095077_2022-02-17_final
2022-02-19 09:14:36	ga_ls7e_ard_3-2-1_102078_2022-02-18_final
2022-02-19 09:15:00	ga_ls7e_ard_3-2-1_102079_2022-02-18_final
2022-02-22 09:46:25	ga_ls7e_ard_3-2-1_107081_2022-02-22_final
2022-02-25 08:35:46	ga_ls7e_ard_3-2-1_096075_2022-02-24_final
2022-02-26 09:20:31	ga_ls7e_ard_3-2-1_103079_2022-02-25_final
2022-02-28 09:07:58	ga_ls7e_ard_3-2-1_101079_2022-02-27_final
2022-03-04 08:41:40	ga_ls7e_ard_3-2-1_097076_2022-03-03_final
2022-03-05 09:23:37	ga_ls7e_ard_3-2-1_104073_2022-03-04_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-06 10:08:23	ga_ls7e_ard_3-2-1_111077_2022-03-06_final
2022-03-08 08:17:45	ga_ls7e_ard_3-2-1_093079_2022-03-07_final
2022-03-11 08:49:08	ga_ls7e_ard_3-2-1_098081_2022-03-10_final
2022-03-12 09:31:54	ga_ls7e_ard_3-2-1_105080_2022-03-12_final
2022-03-13 08:35:23	ga_ls7e_ard_3-2-1_096078_2022-03-12_final
2022-03-13 10:13:52	ga_ls7e_ard_3-2-1_112077_2022-03-13_final
2022-03-17 09:46:44	ga_ls7e_ard_3-2-1_108072_2022-03-17_final
2022-03-23 09:11:53	ga_ls7e_ard_3-2-1_102079_2022-03-22_final
2022-03-24 08:15:46	ga_ls7e_ard_3-2-1_093078_2022-03-23_final
2022-03-29 08:35:26	ga_ls7e_ard_3-2-1_096082_2022-03-28_final
2022-03-29 10:13:07	ga_ls7e_ard_3-2-1_112079_2022-03-29_final
2022-03-30 09:14:12	ga_ls7e_ard_3-2-1_103071_2022-03-29_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