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 10:03:40	ga_ls7e_ard_3-2-0_105080_2021-03-25_final
2021-09-18 10:29:28	ga_ls7e_ard_3-2-0_112074_2021-09-18_final
2021-09-20 10:16:32	ga_ls7e_ard_3-2-0_110073_2021-09-20_final
2021-10-25 09:07:26	ga_ls7e_ard_3-2-0_099078_2021-10-24_final
2021-11-02 09:56:07	ga_ls7e_ard_3-2-0_107078_2021-11-02_final
2021-11-03 09:03:12	ga_ls7e_ard_3-2-0_098085_2021-11-02_final
2021-11-03 10:38:05	ga_ls7e_ard_3-2-0_114075_2021-11-03_final
2021-11-05 10:28:20	ga_ls7e_ard_3-2-0_112082_2021-11-05_final
2021-11-07 08:38:06	ga_ls7e_ard_3-2-0_094085_2021-11-06_final
2021-11-08 09:15:41	ga_ls7e_ard_3-2-0_101071_2021-11-07_final
2021-11-12 10:33:26	ga_ls7e_ard_3-2-1_113081_2021-11-12_final
2021-11-14 08:38:49	ga_ls7e_ard_3-2-1_095073_2021-11-13_final
2021-11-14 10:16:54	ga_ls7e_ard_3-2-1_111071_2021-11-14_final
2021-11-16 10:06:20	ga_ls7e_ard_3-2-1_109076_2021-11-16_final
2021-11-18 08:19:18	ga_ls7e_ard_3-2-1_091087_2021-11-17_final
2021-11-19 08:58:28	ga_ls7e_ard_3-2-1_098077_2021-11-18_final
2021-11-19 08:58:52	ga_ls7e_ard_3-2-1_098078_2021-11-18_final
2021-11-20 09:40:25	ga_ls7e_ard_3-2-1_105074_2021-11-20_final
2021-11-23 10:10:14	ga_ls7e_ard_3-2-1_110072_2021-11-23_final
2021-11-26 08:59:58	ga_ls7e_ard_3-2-1_099067_2021-11-25_final
2021-11-27 08:13:03	ga_ls7e_ard_3-2-1_090089_2021-11-26_final
2021-11-30 08:42:04	ga_ls7e_ard_3-2-1_095085_2021-11-29_final
2021-12-03 09:10:42	ga_ls7e_ard_3-2-1_100080_2021-12-02_final
2021-12-04 08:13:47	ga_ls7e_ard_3-2-1_091077_2021-12-03_final
2021-12-08 09:24:22	ga_ls7e_ard_3-2-1_103069_2021-12-07_final
2021-12-09 08:33:27	ga_ls7e_ard_3-2-1_094081_2021-12-08_final
2021-12-10 09:12:37	ga_ls7e_ard_3-2-1_101071_2021-12-09_final
2021-12-10 09:17:01	ga_ls7e_ard_3-2-1_101082_2021-12-09_final
2021-12-11 08:24:05	ga_ls7e_ard_3-2-1_092089_2021-12-10_final
2021-12-12 09:02:52	ga_ls7e_ard_3-2-1_099078_2021-12-11_final
2021-12-13 08:09:09	ga_ls7e_ard_3-2-1_090083_2021-12-12_final
2021-12-13 09:42:26	ga_ls7e_ard_3-2-1_106069_2021-12-13_final
2021-12-13 09:47:13	ga_ls7e_ard_3-2-1_106081_2021-12-13_final
2021-12-14 08:51:31	ga_ls7e_ard_3-2-1_097081_2021-12-13_final
2021-12-18 10:01:17	ga_ls7e_ard_3-2-1_109071_2021-12-18_final
2021-12-22 09:35:23	ga_ls7e_ard_3-2-1_105069_2021-12-22_final
2021-12-27 09:54:13	ga_ls7e_ard_3-2-1_108071_2021-12-27_final
2021-12-27 09:59:01	ga_ls7e_ard_3-2-1_108083_2021-12-27_final
2021-12-30 08:51:08	ga_ls7e_ard_3-2-1_097084_2021-12-29_final
2021-12-30 10:28:48	ga_ls7e_ard_3-2-1_113081_2021-12-30_final
2022-01-01 10:13:27	ga_ls7e_ard_3-2-1_111074_2022-01-01_final
2022-01-03 08:27:12	ga_ls7e_ard_3-2-1_093087_2022-01-02_final
2022-01-05 09:48:19	ga_ls7e_ard_3-2-1_107074_2022-01-05_final
2022-01-10 10:08:48	ga_ls7e_ard_3-2-1_110080_2022-01-10_final
2022-01-11 09:11:53	ga_ls7e_ard_3-2-1_101077_2022-01-10_final
2022-01-13 09:00:08	ga_ls7e_ard_3-2-1_099079_2022-01-12_final
2022-01-14 09:41:18	ga_ls7e_ard_3-2-1_106074_2022-01-14_final
2022-01-15 10:27:16	ga_ls7e_ard_3-2-1_113081_2022-01-15_final
2022-01-17 10:12:19	ga_ls7e_ard_3-2-1_111075_2022-01-17_final
2022-01-17 10:15:55	ga_ls7e_ard_3-2-1_111084_2022-01-17_final
2022-01-18 09:15:01	ga_ls7e_ard_3-2-1_102071_2022-01-17_final
2022-01-19 08:24:29	ga_ls7e_ard_3-2-1_093084_2022-01-18_final
2022-01-21 08:11:56	ga_ls7e_ard_3-2-1_091084_2022-01-20_final
2022-01-21 09:45:37	ga_ls7e_ard_3-2-1_107071_2022-01-21_final
2022-01-21 09:46:49	ga_ls7e_ard_3-2-1_107074_2022-01-21_final
2022-01-22 08:48:43	ga_ls7e_ard_3-2-1_098068_2022-01-21_final
2022-01-22 08:49:06	ga_ls7e_ard_3-2-1_098069_2022-01-21_final
2022-01-23 07:58:35	ga_ls7e_ard_3-2-1_089082_2022-01-22_final
2022-01-23 07:58:59	ga_ls7e_ard_3-2-1_089083_2022-01-22_final
2022-01-29 08:58:35	ga_ls7e_ard_3-2-1_099079_2022-01-28_final
2022-01-30 08:02:28	ga_ls7e_ard_3-2-1_090078_2022-01-29_final
2022-01-30 08:04:04	ga_ls7e_ard_3-2-1_090082_2022-01-29_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-02-03 09:15:26	ga_ls7e_ard_3-2-1_102076_2022-02-02_final
2022-02-05 09:06:04	ga_ls7e_ard_3-2-1_100084_2022-02-04_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-07 08:53:54	ga_ls7e_ard_3-2-1_098085_2022-02-06_final
2022-02-08 07:58:11	ga_ls7e_ard_3-2-1_089085_2022-02-07_final
2022-02-09 08:40:56	ga_ls7e_ard_3-2-1_096084_2022-02-08_final
2022-02-11 08:27:34	ga_ls7e_ard_3-2-1_094082_2022-02-10_final
2022-02-11 08:29:34	ga_ls7e_ard_3-2-1_094087_2022-02-10_final
2022-02-12 09:10:43	ga_ls7e_ard_3-2-1_101082_2022-02-11_final
2022-02-13 09:50:17	ga_ls7e_ard_3-2-1_108073_2022-02-13_final
2022-02-14 08:58:33	ga_ls7e_ard_3-2-1_099083_2022-02-13_final
2022-02-17 09:25:09	ga_ls7e_ard_3-2-1_104073_2022-02-16_final
2022-02-18 10:12:43	ga_ls7e_ard_3-2-1_111084_2022-02-18_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-21 09:03:15	ga_ls7e_ard_3-2-1_100081_2022-02-20_final
2022-02-22 09:44:01	ga_ls7e_ard_3-2-1_107075_2022-02-22_final
2022-02-23 08:47:07	ga_ls7e_ard_3-2-1_098072_2022-02-22_final
2022-02-27 10:02:29	ga_ls7e_ard_3-2-1_110076_2022-02-27_final
2022-03-03 09:34:35	ga_ls7e_ard_3-2-1_106069_2022-03-03_final
2022-03-04 10:22:56	ga_ls7e_ard_3-2-1_113082_2022-03-04_final
2022-03-06 08:27:31	ga_ls7e_ard_3-2-1_095072_2022-03-05_final
2022-03-06 08:32:18	ga_ls7e_ard_3-2-1_095084_2022-03-05_final
2022-03-06 10:05:59	ga_ls7e_ard_3-2-1_111071_2022-03-06_final
2022-03-08 08:20:56	ga_ls7e_ard_3-2-1_093087_2022-03-07_final
2022-03-08 09:58:13	ga_ls7e_ard_3-2-1_109083_2022-03-08_final
2022-03-09 09:02:54	ga_ls7e_ard_3-2-1_100084_2022-03-08_final
2022-03-10 09:42:28	ga_ls7e_ard_3-2-1_107075_2022-03-10_final
2022-03-11 08:43:33	ga_ls7e_ard_3-2-1_098067_2022-03-10_final
2022-03-11 08:43:57	ga_ls7e_ard_3-2-1_098068_2022-03-10_final
2022-03-13 08:38:34	ga_ls7e_ard_3-2-1_096086_2022-03-12_final
2022-03-13 10:12:40	ga_ls7e_ard_3-2-1_112074_2022-03-13_final
2022-03-14 09:15:45	ga_ls7e_ard_3-2-1_103071_2022-03-13_final
2022-03-22 08:26:19	ga_ls7e_ard_3-2-1_095073_2022-03-21_final
2022-03-25 08:57:20	ga_ls7e_ard_3-2-1_100074_2022-03-24_final
2022-03-29 10:13:55	ga_ls7e_ard_3-2-1_112081_2022-03-29_final
2022-03-31 08:24:05	ga_ls7e_ard_3-2-1_094085_2022-03-30_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