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
2021-08-25 09:42:56	ga_ls7e_ard_3-2-0_104076_2021-08-25_final
2021-09-06 08:29:44	ga_ls7e_ard_3-2-0_092081_2021-09-05_final
2021-09-06 08:30:32	ga_ls7e_ard_3-2-0_092083_2021-09-05_final
2021-09-11 10:27:54	ga_ls7e_ard_3-2-0_111084_2021-09-11_final
2021-09-13 08:38:05	ga_ls7e_ard_3-2-0_093088_2021-09-12_final
2021-09-18 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-18 08:50:59	ga_ls7e_ard_3-2-0_096075_2021-09-17_final
2021-09-25 08:59:20	ga_ls7e_ard_3-2-0_097082_2021-09-24_final
2021-09-27 08:46:47	ga_ls7e_ard_3-2-0_095082_2021-09-26_final
2021-09-27 10:19:41	ga_ls7e_ard_3-2-0_111067_2021-09-27_final
2021-09-29 10:13:08	ga_ls7e_ard_3-2-0_109082_2021-09-29_final
2021-10-02 10:41:46	ga_ls7e_ard_3-2-0_114077_2021-10-02_final
2021-10-05 09:30:45	ga_ls7e_ard_3-2-0_103070_2021-10-05_final
2021-10-08 08:26:53	ga_ls7e_ard_3-2-0_092081_2021-10-07_final
2021-10-10 08:14:45	ga_ls7e_ard_3-2-0_090082_2021-10-09_final
2021-10-12 09:35:54	ga_ls7e_ard_3-2-0_104069_2021-10-12_final
2021-10-13 10:18:41	ga_ls7e_ard_3-2-0_111068_2021-10-13_final
2021-10-13 10:23:52	ga_ls7e_ard_3-2-0_111081_2021-10-13_final
2021-10-15 08:30:51	ga_ls7e_ard_3-2-0_093077_2021-10-14_final
2021-10-16 09:12:26	ga_ls7e_ard_3-2-0_100073_2021-10-15_final
2021-10-17 09:57:11	ga_ls7e_ard_3-2-0_107077_2021-10-17_final
2021-10-27 08:55:41	ga_ls7e_ard_3-2-0_097080_2021-10-26_final
2021-10-31 10:08:40	ga_ls7e_ard_3-2-0_109078_2021-10-31_final
2021-11-02 08:18:27	ga_ls7e_ard_3-2-0_091081_2021-11-01_final
2021-11-02 08:20:26	ga_ls7e_ard_3-2-0_091086_2021-11-01_final
2021-11-02 09:58:31	ga_ls7e_ard_3-2-0_107084_2021-11-02_final
2021-11-04 09:40:47	ga_ls7e_ard_3-2-0_105071_2021-11-04_final
2021-11-05 10:25:56	ga_ls7e_ard_3-2-0_112076_2021-11-05_final
2021-11-07 10:15:23	ga_ls7e_ard_3-2-0_110081_2021-11-07_final
2021-11-10 09:03:55	ga_ls7e_ard_3-2-0_099073_2021-11-09_final
2021-11-11 08:12:36	ga_ls7e_ard_3-2-0_090084_2021-11-10_final
2021-11-19 08:57:40	ga_ls7e_ard_3-2-1_098075_2021-11-18_final
2021-11-21 08:47:54	ga_ls7e_ard_3-2-1_096082_2021-11-20_final
2021-11-25 10:00:28	ga_ls7e_ard_3-2-1_108079_2021-11-25_final
2021-11-30 08:41:40	ga_ls7e_ard_3-2-1_095084_2021-11-29_final
2021-12-02 08:27:56	ga_ls7e_ard_3-2-1_093081_2021-12-01_final
2021-12-05 08:55:21	ga_ls7e_ard_3-2-1_098073_2021-12-04_final
2021-12-07 08:42:24	ga_ls7e_ard_3-2-1_096072_2021-12-06_final
2021-12-09 08:34:15	ga_ls7e_ard_3-2-1_094083_2021-12-08_final
2021-12-11 08:20:30	ga_ls7e_ard_3-2-1_092080_2021-12-10_final
2021-12-11 08:21:42	ga_ls7e_ard_3-2-1_092083_2021-12-10_final
2021-12-16 08:37:22	ga_ls7e_ard_3-2-1_095077_2021-12-15_final
2021-12-18 08:26:48	ga_ls7e_ard_3-2-1_093082_2021-12-17_final
2021-12-18 10:06:05	ga_ls7e_ard_3-2-1_109083_2021-12-18_final
2021-12-20 08:13:51	ga_ls7e_ard_3-2-1_091081_2021-12-19_final
2021-12-20 09:52:20	ga_ls7e_ard_3-2-1_107080_2021-12-20_final
2021-12-24 09:24:25	ga_ls7e_ard_3-2-1_103073_2021-12-23_final
2021-12-25 08:29:30	ga_ls7e_ard_3-2-1_094075_2021-12-24_final
2021-12-25 10:11:58	ga_ls7e_ard_3-2-1_110084_2021-12-25_final
2021-12-28 09:00:06	ga_ls7e_ard_3-2-1_099075_2021-12-27_final
2021-12-28 09:02:54	ga_ls7e_ard_3-2-1_099082_2021-12-27_final
2021-12-29 09:44:51	ga_ls7e_ard_3-2-1_106079_2021-12-29_final
2022-01-02 09:18:32	ga_ls7e_ard_3-2-1_102076_2022-01-01_final
2022-01-02 09:19:20	ga_ls7e_ard_3-2-1_102078_2022-01-01_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-05 08:12:14	ga_ls7e_ard_3-2-1_091081_2022-01-04_final
2022-01-08 08:43:16	ga_ls7e_ard_3-2-1_096082_2022-01-07_final
2022-01-09 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-10 08:30:43	ga_ls7e_ard_3-2-1_094082_2022-01-09_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-12 08:17:22	ga_ls7e_ard_3-2-1_092080_2022-01-11_final
2022-01-13 08:58:32	ga_ls7e_ard_3-2-1_099075_2022-01-12_final
2022-01-18 09:16:12	ga_ls7e_ard_3-2-1_102074_2022-01-17_final
2022-01-18 09:16:36	ga_ls7e_ard_3-2-1_102075_2022-01-17_final
2022-01-18 09:17:00	ga_ls7e_ard_3-2-1_102076_2022-01-17_final
2022-01-21 08:11:08	ga_ls7e_ard_3-2-1_091082_2022-01-20_final
2022-01-23 09:36:15	ga_ls7e_ard_3-2-1_105079_2022-01-23_final
2022-01-26 08:31:11	ga_ls7e_ard_3-2-1_094087_2022-01-25_final
2022-01-28 09:53:31	ga_ls7e_ard_3-2-1_108077_2022-01-28_final
2022-01-30 08:03:40	ga_ls7e_ard_3-2-1_090081_2022-01-29_final
2022-01-31 10:24:55	ga_ls7e_ard_3-2-1_113079_2022-01-31_final
2022-02-02 10:13:09	ga_ls7e_ard_3-2-1_111081_2022-02-02_final
2022-02-05 09:05:16	ga_ls7e_ard_3-2-1_100082_2022-02-04_final
2022-02-09 08:40:32	ga_ls7e_ard_3-2-1_096083_2022-02-08_final
2022-02-14 08:54:57	ga_ls7e_ard_3-2-1_099074_2022-02-13_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-16 10:21:40	ga_ls7e_ard_3-2-1_113075_2022-02-16_final
2022-02-19 09:16:12	ga_ls7e_ard_3-2-1_102082_2022-02-18_final
2022-02-21 09:00:04	ga_ls7e_ard_3-2-1_100073_2022-02-20_final
2022-02-22 09:45:37	ga_ls7e_ard_3-2-1_107079_2022-02-22_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-03-02 08:56:37	ga_ls7e_ard_3-2-1_099082_2022-03-01_final
2022-03-04 08:44:03	ga_ls7e_ard_3-2-1_097082_2022-03-03_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-06 10:08:47	ga_ls7e_ard_3-2-1_111078_2022-03-06_final
2022-03-06 10:11:10	ga_ls7e_ard_3-2-1_111084_2022-03-06_final
2022-03-09 08:59:18	ga_ls7e_ard_3-2-1_100075_2022-03-08_final
2022-03-11 08:46:21	ga_ls7e_ard_3-2-1_098074_2022-03-10_final
2022-03-15 10:01:18	ga_ls7e_ard_3-2-1_110077_2022-03-15_final
2022-03-15 10:02:53	ga_ls7e_ard_3-2-1_110081_2022-03-15_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_final
2022-03-18 08:54:36	ga_ls7e_ard_3-2-1_099081_2022-03-17_final
2022-03-20 10:19:44	ga_ls7e_ard_3-2-1_113078_2022-03-20_final
2022-03-23 09:11:29	ga_ls7e_ard_3-2-1_102078_2022-03-22_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_final
2022-03-31 09:59:46	ga_ls7e_ard_3-2-1_110077_2022-03-31_final
2022-04-05 10:17:00	ga_ls7e_ard_3-2-1_113075_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years