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
2021-09-18 08:53:23	ga_ls7e_ard_3-2-0_096081_2021-09-17_final
2021-09-20 10:16:32	ga_ls7e_ard_3-2-0_110073_2021-09-20_final
2021-09-20 10:18:08	ga_ls7e_ard_3-2-0_110077_2021-09-20_final
2021-10-25 09:06:14	ga_ls7e_ard_3-2-0_099075_2021-10-24_final
2021-10-26 08:12:07	ga_ls7e_ard_3-2-0_090079_2021-10-25_final
2021-11-14 08:40:01	ga_ls7e_ard_3-2-1_095076_2021-11-13_final
2021-11-14 08:44:00	ga_ls7e_ard_3-2-1_095086_2021-11-13_final
2021-11-19 08:58:04	ga_ls7e_ard_3-2-1_098076_2021-11-18_final
2021-11-28 08:49:26	ga_ls7e_ard_3-2-1_097072_2021-11-27_final
2021-12-01 09:22:26	ga_ls7e_ard_3-2-1_102078_2021-11-30_final
2021-12-10 09:17:24	ga_ls7e_ard_3-2-1_101083_2021-12-09_final
2021-12-12 09:00:28	ga_ls7e_ard_3-2-1_099072_2021-12-11_final
2021-12-12 09:00:52	ga_ls7e_ard_3-2-1_099073_2021-12-11_final
2021-12-13 08:06:45	ga_ls7e_ard_3-2-1_090077_2021-12-12_final
2021-12-13 08:08:45	ga_ls7e_ard_3-2-1_090082_2021-12-12_final
2021-12-16 10:16:38	ga_ls7e_ard_3-2-1_111078_2021-12-16_final
2021-12-19 09:07:10	ga_ls7e_ard_3-2-1_100075_2021-12-18_final
2021-12-21 08:54:13	ga_ls7e_ard_3-2-1_098074_2021-12-20_final
2021-12-21 08:54:37	ga_ls7e_ard_3-2-1_098075_2021-12-20_final
2021-12-22 09:34:59	ga_ls7e_ard_3-2-1_105068_2021-12-22_final
2021-12-23 10:24:32	ga_ls7e_ard_3-2-1_112084_2021-12-23_final
2021-12-24 09:23:37	ga_ls7e_ard_3-2-1_103071_2021-12-23_final
2021-12-25 10:07:35	ga_ls7e_ard_3-2-1_110073_2021-12-25_final
2021-12-26 09:14:39	ga_ls7e_ard_3-2-1_101080_2021-12-25_final
2021-12-28 08:59:18	ga_ls7e_ard_3-2-1_099073_2021-12-27_final
2021-12-28 09:00:30	ga_ls7e_ard_3-2-1_099076_2021-12-27_final
2021-12-30 10:26:01	ga_ls7e_ard_3-2-1_113074_2021-12-30_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-02 09:16:32	ga_ls7e_ard_3-2-1_102071_2022-01-01_final
2022-01-05 08:15:26	ga_ls7e_ard_3-2-1_091089_2022-01-04_final
2022-01-06 08:54:12	ga_ls7e_ard_3-2-1_098078_2022-01-05_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-07 09:34:35	ga_ls7e_ard_3-2-1_105071_2022-01-07_final
2022-01-07 09:37:46	ga_ls7e_ard_3-2-1_105079_2022-01-07_final
2022-01-07 09:38:34	ga_ls7e_ard_3-2-1_105081_2022-01-07_final
2022-01-08 08:39:40	ga_ls7e_ard_3-2-1_096073_2022-01-07_final
2022-01-08 10:22:08	ga_ls7e_ard_3-2-1_112082_2022-01-08_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-10 08:32:43	ga_ls7e_ard_3-2-1_094087_2022-01-09_final
2022-01-11 09:12:17	ga_ls7e_ard_3-2-1_101078_2022-01-10_final
2022-01-11 09:12:41	ga_ls7e_ard_3-2-1_101079_2022-01-10_final
2022-01-12 09:51:52	ga_ls7e_ard_3-2-1_108069_2022-01-12_final
2022-01-12 09:52:15	ga_ls7e_ard_3-2-1_108070_2022-01-12_final
2022-01-12 09:53:27	ga_ls7e_ard_3-2-1_108073_2022-01-12_final
2022-01-14 08:05:37	ga_ls7e_ard_3-2-1_090082_2022-01-13_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-22 08:52:18	ga_ls7e_ard_3-2-1_098077_2022-01-21_final
2022-01-24 10:20:37	ga_ls7e_ard_3-2-1_112082_2022-01-24_final
2022-01-31 08:44:50	ga_ls7e_ard_3-2-1_097076_2022-01-30_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-02-03 09:13:26	ga_ls7e_ard_3-2-1_102071_2022-02-02_final
2022-02-03 09:16:14	ga_ls7e_ard_3-2-1_102078_2022-02-02_final
2022-02-04 08:19:43	ga_ls7e_ard_3-2-1_093076_2022-02-03_final
2022-02-06 08:09:33	ga_ls7e_ard_3-2-1_091082_2022-02-05_final
2022-02-06 09:47:13	ga_ls7e_ard_3-2-1_107079_2022-02-06_final
2022-02-08 09:30:16	ga_ls7e_ard_3-2-1_105068_2022-02-08_final
2022-02-08 09:33:52	ga_ls7e_ard_3-2-1_105077_2022-02-08_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-11 10:06:27	ga_ls7e_ard_3-2-1_110082_2022-02-11_final
2022-02-12 09:06:44	ga_ls7e_ard_3-2-1_101072_2022-02-11_final
2022-02-12 09:09:07	ga_ls7e_ard_3-2-1_101078_2022-02-11_final
2022-02-16 08:43:35	ga_ls7e_ard_3-2-1_097077_2022-02-15_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-17 09:25:57	ga_ls7e_ard_3-2-1_104075_2022-02-16_final
2022-02-18 10:08:43	ga_ls7e_ard_3-2-1_111074_2022-02-18_final
2022-02-23 10:27:11	ga_ls7e_ard_3-2-1_114075_2022-02-23_final
2022-02-24 09:33:04	ga_ls7e_ard_3-2-1_105079_2022-02-24_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-03-02 08:52:13	ga_ls7e_ard_3-2-1_099071_2022-03-01_final
2022-03-04 08:39:40	ga_ls7e_ard_3-2-1_097071_2022-03-03_final
2022-03-04 10:20:56	ga_ls7e_ard_3-2-1_113077_2022-03-04_final
2022-03-05 09:24:49	ga_ls7e_ard_3-2-1_104076_2022-03-04_final
2022-03-05 09:25:13	ga_ls7e_ard_3-2-1_104077_2022-03-04_final
2022-03-06 08:28:42	ga_ls7e_ard_3-2-1_095075_2022-03-05_final
2022-03-08 08:17:21	ga_ls7e_ard_3-2-1_093078_2022-03-07_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-13 10:12:40	ga_ls7e_ard_3-2-1_112074_2022-03-13_final
2022-03-15 09:59:18	ga_ls7e_ard_3-2-1_110072_2022-03-15_final
2022-03-17 08:12:39	ga_ls7e_ard_3-2-1_092084_2022-03-16_final
2022-03-17 09:46:20	ga_ls7e_ard_3-2-1_108071_2022-03-17_final
2022-03-20 08:38:04	ga_ls7e_ard_3-2-1_097071_2022-03-19_final
2022-03-20 10:19:20	ga_ls7e_ard_3-2-1_113077_2022-03-20_final
2022-03-21 09:22:50	ga_ls7e_ard_3-2-1_104075_2022-03-20_final
2022-03-22 10:04:48	ga_ls7e_ard_3-2-1_111072_2022-03-22_final
2022-03-25 08:56:56	ga_ls7e_ard_3-2-1_100073_2022-03-24_final
2022-03-26 09:43:18	ga_ls7e_ard_3-2-1_107081_2022-03-26_final
2022-03-27 08:46:47	ga_ls7e_ard_3-2-1_098079_2022-03-26_final
2022-03-27 10:26:04	ga_ls7e_ard_3-2-1_114080_2022-03-27_final
2022-03-30 09:15:00	ga_ls7e_ard_3-2-1_103073_2022-03-29_final
2022-03-30 09:16:36	ga_ls7e_ard_3-2-1_103077_2022-03-29_final
2022-03-31 08:24:05	ga_ls7e_ard_3-2-1_094085_2022-03-30_final
2022-03-31 09:57:46	ga_ls7e_ard_3-2-1_110072_2022-03-31_final
2022-04-03 10:30:22	ga_ls7e_ard_3-2-1_115077_2022-04-03_final
2022-04-04 09:33:27	ga_ls7e_ard_3-2-1_106074_2022-04-04_final
2022-04-05 08:39:44	ga_ls7e_ard_3-2-1_097079_2022-04-04_final
2022-04-06 09:21:17	ga_ls7e_ard_3-2-1_104075_2022-04-05_final
2022-04-06 09:21:41	ga_ls7e_ard_3-2-1_104076_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