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
2021-10-31 08:29:00	ga_ls7e_ard_3-2-0_093076_2021-10-30_final
2021-10-31 08:31:47	ga_ls7e_ard_3-2-0_093083_2021-10-30_final
2021-10-31 10:08:16	ga_ls7e_ard_3-2-0_109077_2021-10-31_final
2021-10-31 10:08:40	ga_ls7e_ard_3-2-0_109078_2021-10-31_final
2021-11-01 09:11:22	ga_ls7e_ard_3-2-0_100074_2021-10-31_final
2021-11-04 09:44:46	ga_ls7e_ard_3-2-0_105081_2021-11-04_final
2021-11-04 09:45:10	ga_ls7e_ard_3-2-0_105082_2021-11-04_final
2021-11-15 09:23:10	ga_ls7e_ard_3-2-1_102076_2021-11-14_final
2021-11-18 09:52:11	ga_ls7e_ard_3-2-1_107072_2021-11-18_final
2021-11-18 09:52:35	ga_ls7e_ard_3-2-1_107073_2021-11-18_final
2021-11-23 10:13:25	ga_ls7e_ard_3-2-1_110080_2021-11-23_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-11-28 10:32:18	ga_ls7e_ard_3-2-1_113082_2021-11-28_final
2021-11-29 09:34:35	ga_ls7e_ard_3-2-1_104077_2021-11-29_final
2021-11-30 08:42:04	ga_ls7e_ard_3-2-1_095085_2021-11-29_final
2021-12-02 10:03:13	ga_ls7e_ard_3-2-1_109072_2021-12-02_final
2021-12-04 09:51:52	ga_ls7e_ard_3-2-1_107075_2021-12-04_final
2021-12-05 10:36:14	ga_ls7e_ard_3-2-1_114078_2021-12-05_final
2021-12-06 09:37:43	ga_ls7e_ard_3-2-1_105071_2021-12-06_final
2021-12-08 09:28:22	ga_ls7e_ard_3-2-1_103079_2021-12-07_final
2021-12-09 08:31:51	ga_ls7e_ard_3-2-1_094077_2021-12-08_final
2021-12-13 08:11:56	ga_ls7e_ard_3-2-1_090090_2021-12-12_final
2021-12-14 10:30:23	ga_ls7e_ard_3-2-1_113081_2021-12-14_final
2021-12-16 08:38:10	ga_ls7e_ard_3-2-1_095079_2021-12-15_final
2021-12-17 09:20:07	ga_ls7e_ard_3-2-1_102076_2021-12-16_final
2021-12-19 09:09:58	ga_ls7e_ard_3-2-1_100082_2021-12-18_final
2021-12-20 09:50:20	ga_ls7e_ard_3-2-1_107075_2021-12-20_final
2021-12-20 09:51:56	ga_ls7e_ard_3-2-1_107079_2021-12-20_final
2021-12-21 08:57:25	ga_ls7e_ard_3-2-1_098082_2021-12-20_final
2021-12-23 08:44:51	ga_ls7e_ard_3-2-1_096082_2021-12-22_final
2021-12-23 10:21:44	ga_ls7e_ard_3-2-1_112077_2021-12-23_final
2021-12-25 08:29:54	ga_ls7e_ard_3-2-1_094076_2021-12-24_final
2021-12-25 10:10:22	ga_ls7e_ard_3-2-1_110080_2021-12-25_final
2021-12-25 10:11:34	ga_ls7e_ard_3-2-1_110083_2021-12-25_final
2021-12-27 09:55:25	ga_ls7e_ard_3-2-1_108074_2021-12-27_final
2021-12-29 08:10:22	ga_ls7e_ard_3-2-1_090090_2021-12-28_final
2021-12-30 08:48:44	ga_ls7e_ard_3-2-1_097078_2021-12-29_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2021-12-30 08:50:44	ga_ls7e_ard_3-2-1_097083_2021-12-29_final
2021-12-30 10:29:12	ga_ls7e_ard_3-2-1_113082_2021-12-30_final
2022-01-02 09:18:56	ga_ls7e_ard_3-2-1_102077_2022-01-01_final
2022-01-05 08:12:14	ga_ls7e_ard_3-2-1_091081_2022-01-04_final
2022-01-10 08:32:43	ga_ls7e_ard_3-2-1_094087_2022-01-09_final
2022-01-10 10:06:24	ga_ls7e_ard_3-2-1_110074_2022-01-10_final
2022-01-12 09:53:51	ga_ls7e_ard_3-2-1_108074_2022-01-12_final
2022-01-13 09:01:44	ga_ls7e_ard_3-2-1_099083_2022-01-12_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-15 08:47:59	ga_ls7e_ard_3-2-1_097080_2022-01-14_final
2022-01-15 10:27:40	ga_ls7e_ard_3-2-1_113082_2022-01-15_final
2022-01-17 10:14:19	ga_ls7e_ard_3-2-1_111080_2022-01-17_final
2022-01-18 09:16:36	ga_ls7e_ard_3-2-1_102075_2022-01-17_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-26 08:27:35	ga_ls7e_ard_3-2-1_094078_2022-01-25_final
2022-01-26 08:31:11	ga_ls7e_ard_3-2-1_094087_2022-01-25_final
2022-01-29 08:57:00	ga_ls7e_ard_3-2-1_099075_2022-01-28_final
2022-01-30 09:40:57	ga_ls7e_ard_3-2-1_106077_2022-01-30_final
2022-01-31 08:44:02	ga_ls7e_ard_3-2-1_097074_2022-01-30_final
2022-01-31 10:25:42	ga_ls7e_ard_3-2-1_113081_2022-01-31_final
2022-02-02 10:13:57	ga_ls7e_ard_3-2-1_111083_2022-02-02_final
2022-02-04 08:20:31	ga_ls7e_ard_3-2-1_093078_2022-02-03_final
2022-02-06 08:09:33	ga_ls7e_ard_3-2-1_091082_2022-02-05_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-09 08:40:32	ga_ls7e_ard_3-2-1_096083_2022-02-08_final
2022-02-11 08:28:22	ga_ls7e_ard_3-2-1_094084_2022-02-10_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-15 08:01:38	ga_ls7e_ard_3-2-1_090080_2022-02-14_final
2022-02-16 10:22:04	ga_ls7e_ard_3-2-1_113076_2022-02-16_final
2022-02-16 10:24:04	ga_ls7e_ard_3-2-1_113081_2022-02-16_final
2022-02-20 08:17:18	ga_ls7e_ard_3-2-1_093074_2022-02-19_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-22 08:06:44	ga_ls7e_ard_3-2-1_091079_2022-02-21_final
2022-02-22 08:10:44	ga_ls7e_ard_3-2-1_091089_2022-02-21_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-25 08:35:22	ga_ls7e_ard_3-2-1_096074_2022-02-24_final
2022-02-25 10:14:38	ga_ls7e_ard_3-2-1_112075_2022-02-25_final
2022-02-26 09:19:43	ga_ls7e_ard_3-2-1_103077_2022-02-25_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
2022-03-01 08:11:51	ga_ls7e_ard_3-2-1_092078_2022-02-28_final
2022-03-01 08:13:03	ga_ls7e_ard_3-2-1_092081_2022-02-28_final
2022-03-01 09:51:32	ga_ls7e_ard_3-2-1_108080_2022-03-01_final
2022-03-01 09:52:43	ga_ls7e_ard_3-2-1_108083_2022-03-01_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-08 08:20:32	ga_ls7e_ard_3-2-1_093086_2022-03-07_final
2022-03-10 08:04:47	ga_ls7e_ard_3-2-1_091078_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
2022-03-13 08:32:59	ga_ls7e_ard_3-2-1_096072_2022-03-12_final
2022-03-17 09:46:20	ga_ls7e_ard_3-2-1_108071_2022-03-17_final
2022-03-18 08:55:24	ga_ls7e_ard_3-2-1_099083_2022-03-17_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-22 08:29:31	ga_ls7e_ard_3-2-1_095081_2022-03-21_final
2022-03-23 09:09:05	ga_ls7e_ard_3-2-1_102072_2022-03-22_final
2022-03-24 08:18:58	ga_ls7e_ard_3-2-1_093086_2022-03-23_final
2022-03-28 09:29:09	ga_ls7e_ard_3-2-1_105077_2022-03-27_final
2022-03-31 08:24:05	ga_ls7e_ard_3-2-1_094085_2022-03-30_final
2022-03-31 10:01:46	ga_ls7e_ard_3-2-1_110082_2022-03-31_final
2022-04-02 09:49:12	ga_ls7e_ard_3-2-1_108082_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