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 10:17:20	ga_ls7e_ard_3-2-0_110075_2021-09-20_final
2021-10-09 10:48:08	ga_ls7e_ard_3-2-0_115079_2021-10-09_final
2021-10-10 09:49:38	ga_ls7e_ard_3-2-0_106072_2021-10-10_final
2021-10-11 08:58:43	ga_ls7e_ard_3-2-0_097084_2021-10-10_final
2021-10-14 09:24:34	ga_ls7e_ard_3-2-0_102072_2021-10-13_final
2021-10-17 08:18:19	ga_ls7e_ard_3-2-0_091077_2021-10-16_final
2021-10-25 09:06:38	ga_ls7e_ard_3-2-0_099076_2021-10-24_final
2021-10-26 09:48:36	ga_ls7e_ard_3-2-0_106073_2021-10-26_final
2021-10-26 09:50:36	ga_ls7e_ard_3-2-0_106078_2021-10-26_final
2021-10-27 08:57:17	ga_ls7e_ard_3-2-0_097084_2021-10-26_final
2021-11-04 09:44:46	ga_ls7e_ard_3-2-0_105081_2021-11-04_final
2021-11-10 09:08:19	ga_ls7e_ard_3-2-0_099084_2021-11-09_final
2021-11-17 09:13:49	ga_ls7e_ard_3-2-1_100084_2021-11-16_final
2021-11-18 08:18:06	ga_ls7e_ard_3-2-1_091084_2021-11-17_final
2021-11-19 10:36:32	ga_ls7e_ard_3-2-1_114075_2021-11-19_final
2021-11-19 10:37:20	ga_ls7e_ard_3-2-1_114077_2021-11-19_final
2021-11-21 08:49:06	ga_ls7e_ard_3-2-1_096085_2021-11-20_final
2021-11-23 10:11:49	ga_ls7e_ard_3-2-1_110076_2021-11-23_final
2021-11-23 10:14:13	ga_ls7e_ard_3-2-1_110082_2021-11-23_final
2021-11-26 09:01:10	ga_ls7e_ard_3-2-1_099070_2021-11-25_final
2021-11-26 10:42:27	ga_ls7e_ard_3-2-1_115076_2021-11-26_final
2021-11-27 08:13:03	ga_ls7e_ard_3-2-1_090089_2021-11-26_final
2021-11-28 08:48:14	ga_ls7e_ard_3-2-1_097069_2021-11-27_final
2021-11-29 09:31:00	ga_ls7e_ard_3-2-1_104068_2021-11-29_final
2021-11-29 09:34:35	ga_ls7e_ard_3-2-1_104077_2021-11-29_final
2021-12-02 10:02:25	ga_ls7e_ard_3-2-1_109070_2021-12-02_final
2021-12-02 10:05:36	ga_ls7e_ard_3-2-1_109078_2021-12-02_final
2021-12-04 09:51:28	ga_ls7e_ard_3-2-1_107074_2021-12-04_final
2021-12-05 10:36:14	ga_ls7e_ard_3-2-1_114078_2021-12-05_final
2021-12-11 09:59:46	ga_ls7e_ard_3-2-1_108081_2021-12-11_final
2021-12-14 08:51:07	ga_ls7e_ard_3-2-1_097080_2021-12-13_final
2021-12-16 10:19:02	ga_ls7e_ard_3-2-1_111084_2021-12-16_final
2021-12-20 08:15:27	ga_ls7e_ard_3-2-1_091085_2021-12-19_final
2021-12-22 08:02:06	ga_ls7e_ard_3-2-1_089083_2021-12-21_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-23 10:21:44	ga_ls7e_ard_3-2-1_112077_2021-12-23_final
2021-12-27 08:20:56	ga_ls7e_ard_3-2-1_092085_2021-12-26_final
2021-12-27 09:57:25	ga_ls7e_ard_3-2-1_108079_2021-12-27_final
2021-12-28 08:59:18	ga_ls7e_ard_3-2-1_099073_2021-12-27_final
2021-12-29 08:07:34	ga_ls7e_ard_3-2-1_090083_2021-12-28_final
2022-01-01 08:39:22	ga_ls7e_ard_3-2-1_095086_2021-12-31_final
2022-01-02 09:16:08	ga_ls7e_ard_3-2-1_102070_2022-01-01_final
2022-01-02 09:16:56	ga_ls7e_ard_3-2-1_102072_2022-01-01_final
2022-01-02 09:19:20	ga_ls7e_ard_3-2-1_102078_2022-01-01_final
2022-01-03 08:23:36	ga_ls7e_ard_3-2-1_093078_2022-01-02_final
2022-01-04 09:04:46	ga_ls7e_ard_3-2-1_100073_2022-01-03_final
2022-01-06 08:55:00	ga_ls7e_ard_3-2-1_098080_2022-01-05_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-10 10:10:23	ga_ls7e_ard_3-2-1_110084_2022-01-10_final
2022-01-11 09:12:17	ga_ls7e_ard_3-2-1_101078_2022-01-10_final
2022-01-15 10:26:52	ga_ls7e_ard_3-2-1_113080_2022-01-15_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-21 08:11:56	ga_ls7e_ard_3-2-1_091084_2022-01-20_final
2022-01-21 08:13:32	ga_ls7e_ard_3-2-1_091088_2022-01-20_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-28 09:55:54	ga_ls7e_ard_3-2-1_108083_2022-01-28_final
2022-01-31 10:23:43	ga_ls7e_ard_3-2-1_113076_2022-01-31_final
2022-01-31 10:25:42	ga_ls7e_ard_3-2-1_113081_2022-01-31_final
2022-02-04 10:01:23	ga_ls7e_ard_3-2-1_109083_2022-02-04_final
2022-02-13 09:49:05	ga_ls7e_ard_3-2-1_108070_2022-02-13_final
2022-02-13 09:50:17	ga_ls7e_ard_3-2-1_108073_2022-02-13_final
2022-02-15 08:01:14	ga_ls7e_ard_3-2-1_090079_2022-02-14_final
2022-02-15 09:36:55	ga_ls7e_ard_3-2-1_106071_2022-02-15_final
2022-02-15 09:39:42	ga_ls7e_ard_3-2-1_106078_2022-02-15_final
2022-02-16 08:42:23	ga_ls7e_ard_3-2-1_097074_2022-02-15_final
2022-02-16 08:44:23	ga_ls7e_ard_3-2-1_097079_2022-02-15_final
2022-02-17 09:24:45	ga_ls7e_ard_3-2-1_104072_2022-02-16_final
2022-02-18 08:33:50	ga_ls7e_ard_3-2-1_095084_2022-02-17_final
2022-02-18 10:07:55	ga_ls7e_ard_3-2-1_111072_2022-02-18_final
2022-02-19 09:11:49	ga_ls7e_ard_3-2-1_102071_2022-02-18_final
2022-02-21 08:59:16	ga_ls7e_ard_3-2-1_100071_2022-02-20_final
2022-02-22 08:07:56	ga_ls7e_ard_3-2-1_091082_2022-02-21_final
2022-02-22 09:42:26	ga_ls7e_ard_3-2-1_107071_2022-02-22_final
2022-02-22 09:44:25	ga_ls7e_ard_3-2-1_107076_2022-02-22_final
2022-02-23 10:29:35	ga_ls7e_ard_3-2-1_114081_2022-02-23_final
2022-02-27 10:04:29	ga_ls7e_ard_3-2-1_110081_2022-02-27_final
2022-03-04 10:19:44	ga_ls7e_ard_3-2-1_113074_2022-03-04_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-09 09:02:06	ga_ls7e_ard_3-2-1_100082_2022-03-08_final
2022-03-10 08:07:11	ga_ls7e_ard_3-2-1_091084_2022-03-09_final
2022-03-10 09:41:16	ga_ls7e_ard_3-2-1_107072_2022-03-10_final
2022-03-11 08:48:44	ga_ls7e_ard_3-2-1_098080_2022-03-10_final
2022-03-11 08:50:20	ga_ls7e_ard_3-2-1_098084_2022-03-10_final
2022-03-13 08:32:35	ga_ls7e_ard_3-2-1_096071_2022-03-12_final
2022-03-15 08:24:01	ga_ls7e_ard_3-2-1_094081_2022-03-14_final
2022-03-15 10:04:05	ga_ls7e_ard_3-2-1_110084_2022-03-15_final
2022-03-17 09:47:56	ga_ls7e_ard_3-2-1_108075_2022-03-17_final
2022-03-18 08:51:25	ga_ls7e_ard_3-2-1_099073_2022-03-17_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-22 08:31:07	ga_ls7e_ard_3-2-1_095085_2022-03-21_final
2022-03-24 08:14:34	ga_ls7e_ard_3-2-1_093075_2022-03-23_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-26 09:44:06	ga_ls7e_ard_3-2-1_107083_2022-03-26_final
2022-03-27 08:47:11	ga_ls7e_ard_3-2-1_098080_2022-03-26_final
2022-03-27 10:24:04	ga_ls7e_ard_3-2-1_114075_2022-03-27_final
2022-03-28 09:28:21	ga_ls7e_ard_3-2-1_105075_2022-03-27_final
2022-03-30 09:13:01	ga_ls7e_ard_3-2-1_103068_2022-03-29_final
2022-04-03 08:49:54	ga_ls7e_ard_3-2-1_099073_2022-04-02_final
2022-04-04 07:56:10	ga_ls7e_ard_3-2-1_090078_2022-04-03_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