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
2021-03-25 08:23:59	ga_ls7e_ard_3-2-0_089078_2021-03-24_final
2021-10-25 09:09:01	ga_ls7e_ard_3-2-0_099082_2021-10-24_final
2021-10-25 10:45:54	ga_ls7e_ard_3-2-0_115077_2021-10-25_final
2021-10-25 10:46:18	ga_ls7e_ard_3-2-0_115078_2021-10-25_final
2021-10-26 09:48:12	ga_ls7e_ard_3-2-0_106072_2021-10-26_final
2021-10-29 08:42:20	ga_ls7e_ard_3-2-0_095078_2021-10-28_final
2021-11-03 08:57:37	ga_ls7e_ard_3-2-0_098071_2021-11-02_final
2021-11-03 10:38:29	ga_ls7e_ard_3-2-0_114076_2021-11-03_final
2021-11-05 08:49:03	ga_ls7e_ard_3-2-0_096081_2021-11-04_final
2021-11-05 08:51:03	ga_ls7e_ard_3-2-0_096086_2021-11-04_final
2021-11-07 08:34:07	ga_ls7e_ard_3-2-0_094075_2021-11-06_final
2021-11-12 10:30:39	ga_ls7e_ard_3-2-1_113074_2021-11-12_final
2021-11-14 08:39:37	ga_ls7e_ard_3-2-1_095075_2021-11-13_final
2021-11-15 09:20:47	ga_ls7e_ard_3-2-1_102070_2021-11-14_final
2021-11-15 09:24:46	ga_ls7e_ard_3-2-1_102080_2021-11-14_final
2021-11-16 10:09:08	ga_ls7e_ard_3-2-1_109083_2021-11-16_final
2021-11-20 09:39:14	ga_ls7e_ard_3-2-1_105071_2021-11-20_final
2021-11-20 09:40:01	ga_ls7e_ard_3-2-1_105073_2021-11-20_final
2021-11-20 09:40:25	ga_ls7e_ard_3-2-1_105074_2021-11-20_final
2021-11-22 09:28:16	ga_ls7e_ard_3-2-1_103075_2021-11-21_final
2021-11-28 08:48:14	ga_ls7e_ard_3-2-1_097069_2021-11-27_final
2021-11-29 09:32:36	ga_ls7e_ard_3-2-1_104072_2021-11-29_final
2021-11-30 08:39:16	ga_ls7e_ard_3-2-1_095078_2021-11-29_final
2021-12-03 09:09:54	ga_ls7e_ard_3-2-1_100078_2021-12-02_final
2021-12-04 08:15:47	ga_ls7e_ard_3-2-1_091082_2021-12-03_final
2021-12-04 09:51:04	ga_ls7e_ard_3-2-1_107073_2021-12-04_final
2021-12-07 08:42:24	ga_ls7e_ard_3-2-1_096072_2021-12-06_final
2021-12-10 09:13:49	ga_ls7e_ard_3-2-1_101074_2021-12-09_final
2021-12-13 08:08:45	ga_ls7e_ard_3-2-1_090082_2021-12-12_final
2021-12-14 08:50:43	ga_ls7e_ard_3-2-1_097079_2021-12-13_final
2021-12-14 10:27:36	ga_ls7e_ard_3-2-1_113074_2021-12-14_final
2021-12-17 09:18:08	ga_ls7e_ard_3-2-1_102071_2021-12-16_final
2021-12-17 09:19:43	ga_ls7e_ard_3-2-1_102075_2021-12-16_final
2021-12-18 08:23:37	ga_ls7e_ard_3-2-1_093074_2021-12-17_final
2021-12-18 10:03:41	ga_ls7e_ard_3-2-1_109077_2021-12-18_final
2021-12-19 09:10:22	ga_ls7e_ard_3-2-1_100083_2021-12-18_final
2021-12-20 09:51:32	ga_ls7e_ard_3-2-1_107078_2021-12-20_final
2021-12-21 08:57:49	ga_ls7e_ard_3-2-1_098083_2021-12-20_final
2021-12-27 08:20:32	ga_ls7e_ard_3-2-1_092084_2021-12-26_final
2021-12-28 09:02:54	ga_ls7e_ard_3-2-1_099082_2021-12-27_final
2021-12-29 08:07:58	ga_ls7e_ard_3-2-1_090084_2021-12-28_final
2022-01-01 08:34:10	ga_ls7e_ard_3-2-1_095073_2021-12-31_final
2022-01-01 10:15:27	ga_ls7e_ard_3-2-1_111079_2022-01-01_final
2022-01-03 08:22:01	ga_ls7e_ard_3-2-1_093074_2022-01-02_final
2022-01-04 09:07:33	ga_ls7e_ard_3-2-1_100080_2022-01-03_final
2022-01-06 08:51:25	ga_ls7e_ard_3-2-1_098071_2022-01-05_final
2022-01-08 08:39:16	ga_ls7e_ard_3-2-1_096072_2022-01-07_final
2022-01-10 08:27:31	ga_ls7e_ard_3-2-1_094074_2022-01-09_final
2022-01-14 08:03:38	ga_ls7e_ard_3-2-1_090077_2022-01-13_final
2022-01-17 10:11:07	ga_ls7e_ard_3-2-1_111072_2022-01-17_final
2022-01-17 10:11:55	ga_ls7e_ard_3-2-1_111074_2022-01-17_final
2022-01-18 09:16:12	ga_ls7e_ard_3-2-1_102074_2022-01-17_final
2022-01-18 09:17:00	ga_ls7e_ard_3-2-1_102076_2022-01-17_final
2022-01-19 08:24:29	ga_ls7e_ard_3-2-1_093084_2022-01-18_final
2022-01-19 09:59:22	ga_ls7e_ard_3-2-1_109074_2022-01-19_final
2022-01-19 09:59:46	ga_ls7e_ard_3-2-1_109075_2022-01-19_final
2022-01-19 10:01:46	ga_ls7e_ard_3-2-1_109080_2022-01-19_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-24 10:18:13	ga_ls7e_ard_3-2-1_112076_2022-01-24_final
2022-01-26 10:06:52	ga_ls7e_ard_3-2-1_110079_2022-01-26_final
2022-01-28 09:54:18	ga_ls7e_ard_3-2-1_108079_2022-01-28_final
2022-01-28 09:55:06	ga_ls7e_ard_3-2-1_108081_2022-01-28_final
2022-02-04 08:20:55	ga_ls7e_ard_3-2-1_093079_2022-02-03_final
2022-02-04 09:58:59	ga_ls7e_ard_3-2-1_109077_2022-02-04_final
2022-02-04 09:59:47	ga_ls7e_ard_3-2-1_109079_2022-02-04_final
2022-02-04 10:00:35	ga_ls7e_ard_3-2-1_109081_2022-02-04_final
2022-02-05 09:01:16	ga_ls7e_ard_3-2-1_100072_2022-02-04_final
2022-02-06 09:46:02	ga_ls7e_ard_3-2-1_107076_2022-02-06_final
2022-02-09 08:38:56	ga_ls7e_ard_3-2-1_096079_2022-02-08_final
2022-02-11 08:23:58	ga_ls7e_ard_3-2-1_094073_2022-02-10_final
2022-02-14 08:56:57	ga_ls7e_ard_3-2-1_099079_2022-02-13_final
2022-02-15 08:02:25	ga_ls7e_ard_3-2-1_090082_2022-02-14_final
2022-02-15 08:04:49	ga_ls7e_ard_3-2-1_090088_2022-02-14_final
2022-02-19 09:15:24	ga_ls7e_ard_3-2-1_102080_2022-02-18_final
2022-02-22 09:42:50	ga_ls7e_ard_3-2-1_107072_2022-02-22_final
2022-02-22 09:44:25	ga_ls7e_ard_3-2-1_107076_2022-02-22_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-24 09:33:28	ga_ls7e_ard_3-2-1_105080_2022-02-24_final
2022-02-25 10:17:02	ga_ls7e_ard_3-2-1_112081_2022-02-25_final
2022-03-01 09:50:44	ga_ls7e_ard_3-2-1_108078_2022-03-01_final
2022-03-02 08:56:37	ga_ls7e_ard_3-2-1_099082_2022-03-01_final
2022-03-02 08:57:24	ga_ls7e_ard_3-2-1_099084_2022-03-01_final
2022-03-03 09:37:47	ga_ls7e_ard_3-2-1_106077_2022-03-03_final
2022-03-06 08:31:06	ga_ls7e_ard_3-2-1_095081_2022-03-05_final
2022-03-06 08:32:18	ga_ls7e_ard_3-2-1_095084_2022-03-05_final
2022-03-09 09:01:18	ga_ls7e_ard_3-2-1_100080_2022-03-08_final
2022-03-10 09:44:52	ga_ls7e_ard_3-2-1_107081_2022-03-10_final
2022-03-12 09:27:07	ga_ls7e_ard_3-2-1_105068_2022-03-11_final
2022-03-13 08:38:10	ga_ls7e_ard_3-2-1_096085_2022-03-12_final
2022-03-15 08:24:01	ga_ls7e_ard_3-2-1_094081_2022-03-14_final
2022-03-17 09:47:08	ga_ls7e_ard_3-2-1_108073_2022-03-17_final
2022-03-18 08:54:36	ga_ls7e_ard_3-2-1_099081_2022-03-17_final
2022-03-19 07:58:30	ga_ls7e_ard_3-2-1_090080_2022-03-18_final
2022-03-20 08:43:39	ga_ls7e_ard_3-2-1_097085_2022-03-19_final
2022-03-20 10:21:20	ga_ls7e_ard_3-2-1_113082_2022-03-20_final
2022-03-21 09:20:50	ga_ls7e_ard_3-2-1_104070_2022-03-20_final
2022-03-21 09:22:02	ga_ls7e_ard_3-2-1_104073_2022-03-20_final
2022-03-22 08:29:07	ga_ls7e_ard_3-2-1_095080_2022-03-21_final
2022-03-29 08:33:50	ga_ls7e_ard_3-2-1_096078_2022-03-28_final
2022-03-29 08:36:38	ga_ls7e_ard_3-2-1_096085_2022-03-28_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