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
2021-09-20 10:18:08	ga_ls7e_ard_3-2-0_110077_2021-09-20_final
2021-11-17 09:10:13	ga_ls7e_ard_3-2-1_100075_2021-11-16_final
2021-11-19 10:36:08	ga_ls7e_ard_3-2-1_114074_2021-11-19_final
2021-11-20 09:38:26	ga_ls7e_ard_3-2-1_105069_2021-11-20_final
2021-11-22 09:29:28	ga_ls7e_ard_3-2-1_103078_2021-11-21_final
2021-11-27 09:47:32	ga_ls7e_ard_3-2-1_106078_2021-11-27_final
2021-11-30 08:40:52	ga_ls7e_ard_3-2-1_095082_2021-11-29_final
2021-12-08 09:27:10	ga_ls7e_ard_3-2-1_103076_2021-12-07_final
2021-12-08 09:27:34	ga_ls7e_ard_3-2-1_103077_2021-12-07_final
2021-12-08 09:28:46	ga_ls7e_ard_3-2-1_103080_2021-12-07_final
2021-12-09 10:11:55	ga_ls7e_ard_3-2-1_110080_2021-12-09_final
2021-12-10 09:15:49	ga_ls7e_ard_3-2-1_101079_2021-12-09_final
2021-12-11 08:20:06	ga_ls7e_ard_3-2-1_092079_2021-12-10_final
2021-12-11 08:21:18	ga_ls7e_ard_3-2-1_092082_2021-12-10_final
2021-12-11 08:21:42	ga_ls7e_ard_3-2-1_092083_2021-12-10_final
2021-12-11 08:22:06	ga_ls7e_ard_3-2-1_092084_2021-12-10_final
2021-12-11 10:00:10	ga_ls7e_ard_3-2-1_108082_2021-12-11_final
2021-12-11 10:00:34	ga_ls7e_ard_3-2-1_108083_2021-12-11_final
2021-12-12 10:40:57	ga_ls7e_ard_3-2-1_115076_2021-12-12_final
2021-12-14 08:48:19	ga_ls7e_ard_3-2-1_097073_2021-12-13_final
2021-12-14 08:52:18	ga_ls7e_ard_3-2-1_097083_2021-12-13_final
2021-12-14 10:30:23	ga_ls7e_ard_3-2-1_113081_2021-12-14_final
2021-12-16 10:16:14	ga_ls7e_ard_3-2-1_111077_2021-12-16_final
2021-12-19 09:09:58	ga_ls7e_ard_3-2-1_100082_2021-12-18_final
2021-12-20 09:51:56	ga_ls7e_ard_3-2-1_107079_2021-12-20_final
2021-12-21 08:56:13	ga_ls7e_ard_3-2-1_098079_2021-12-20_final
2021-12-24 09:28:01	ga_ls7e_ard_3-2-1_103082_2021-12-23_final
2021-12-26 09:12:40	ga_ls7e_ard_3-2-1_101075_2021-12-25_final
2021-12-26 09:13:04	ga_ls7e_ard_3-2-1_101076_2021-12-25_final
2021-12-27 08:19:44	ga_ls7e_ard_3-2-1_092082_2021-12-26_final
2021-12-27 09:56:13	ga_ls7e_ard_3-2-1_108076_2021-12-27_final
2021-12-27 09:59:25	ga_ls7e_ard_3-2-1_108084_2021-12-27_final
2021-12-28 09:00:06	ga_ls7e_ard_3-2-1_099075_2021-12-27_final
2021-12-29 08:07:34	ga_ls7e_ard_3-2-1_090083_2021-12-28_final
2021-12-29 09:45:15	ga_ls7e_ard_3-2-1_106080_2021-12-29_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2022-01-03 08:26:24	ga_ls7e_ard_3-2-1_093085_2022-01-02_final
2022-01-03 10:00:05	ga_ls7e_ard_3-2-1_109072_2022-01-03_final
2022-01-03 10:01:41	ga_ls7e_ard_3-2-1_109076_2022-01-03_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-09 09:22:50	ga_ls7e_ard_3-2-1_103073_2022-01-08_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-10 10:09:12	ga_ls7e_ard_3-2-1_110081_2022-01-10_final
2022-01-11 09:11:05	ga_ls7e_ard_3-2-1_101075_2022-01-10_final
2022-01-12 08:18:58	ga_ls7e_ard_3-2-1_092084_2022-01-11_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-14 09:44:30	ga_ls7e_ard_3-2-1_106082_2022-01-14_final
2022-01-15 08:48:47	ga_ls7e_ard_3-2-1_097082_2022-01-14_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-19 08:24:29	ga_ls7e_ard_3-2-1_093084_2022-01-18_final
2022-01-22 08:51:30	ga_ls7e_ard_3-2-1_098075_2022-01-21_final
2022-01-26 10:05:16	ga_ls7e_ard_3-2-1_110075_2022-01-26_final
2022-01-26 10:07:40	ga_ls7e_ard_3-2-1_110081_2022-01-26_final
2022-01-27 09:11:57	ga_ls7e_ard_3-2-1_101081_2022-01-26_final
2022-01-30 08:03:16	ga_ls7e_ard_3-2-1_090080_2022-01-29_final
2022-02-02 08:35:04	ga_ls7e_ard_3-2-1_095083_2022-02-01_final
2022-02-04 08:22:54	ga_ls7e_ard_3-2-1_093084_2022-02-03_final
2022-02-05 09:05:16	ga_ls7e_ard_3-2-1_100082_2022-02-04_final
2022-02-07 08:50:18	ga_ls7e_ard_3-2-1_098076_2022-02-06_final
2022-02-07 10:29:59	ga_ls7e_ard_3-2-1_114078_2022-02-07_final
2022-02-08 07:57:23	ga_ls7e_ard_3-2-1_089083_2022-02-07_final
2022-02-11 08:29:10	ga_ls7e_ard_3-2-1_094086_2022-02-10_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-14 08:55:21	ga_ls7e_ard_3-2-1_099075_2022-02-13_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-17 09:25:33	ga_ls7e_ard_3-2-1_104074_2022-02-16_final
2022-02-17 09:26:45	ga_ls7e_ard_3-2-1_104077_2022-02-16_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-24 09:29:29	ga_ls7e_ard_3-2-1_105070_2022-02-23_final
2022-02-26 09:19:43	ga_ls7e_ard_3-2-1_103077_2022-02-25_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-04 08:42:04	ga_ls7e_ard_3-2-1_097077_2022-03-03_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-05 09:22:50	ga_ls7e_ard_3-2-1_104071_2022-03-04_final
2022-03-06 10:11:10	ga_ls7e_ard_3-2-1_111084_2022-03-06_final
2022-03-08 08:16:09	ga_ls7e_ard_3-2-1_093075_2022-03-07_final
2022-03-08 08:20:56	ga_ls7e_ard_3-2-1_093087_2022-03-07_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-10 09:42:04	ga_ls7e_ard_3-2-1_107074_2022-03-10_final
2022-03-11 08:49:56	ga_ls7e_ard_3-2-1_098083_2022-03-10_final
2022-03-11 08:50:44	ga_ls7e_ard_3-2-1_098085_2022-03-10_final
2022-03-11 10:25:13	ga_ls7e_ard_3-2-1_114074_2022-03-11_final
2022-03-13 08:36:59	ga_ls7e_ard_3-2-1_096082_2022-03-12_final
2022-03-15 08:24:01	ga_ls7e_ard_3-2-1_094081_2022-03-14_final
2022-03-15 09:59:42	ga_ls7e_ard_3-2-1_110073_2022-03-15_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-19 07:58:06	ga_ls7e_ard_3-2-1_090079_2022-03-18_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-27 10:24:52	ga_ls7e_ard_3-2-1_114077_2022-03-27_final
2022-03-29 08:31:51	ga_ls7e_ard_3-2-1_096073_2022-03-28_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-04-04 09:33:03	ga_ls7e_ard_3-2-1_106073_2022-04-04_final
2022-04-04 09:33:27	ga_ls7e_ard_3-2-1_106074_2022-04-04_final
2022-04-06 09:22:05	ga_ls7e_ard_3-2-1_104077_2022-04-05_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