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 08:50:12	ga_ls7e_ard_3-2-0_096073_2021-09-17_final
2021-09-18 08:50:59	ga_ls7e_ard_3-2-0_096075_2021-09-17_final
2021-09-20 08:39:15	ga_ls7e_ard_3-2-0_094077_2021-09-19_final
2021-09-20 10:19:19	ga_ls7e_ard_3-2-0_110080_2021-09-20_final
2021-10-08 08:26:53	ga_ls7e_ard_3-2-0_092081_2021-10-07_final
2021-10-09 09:06:52	ga_ls7e_ard_3-2-0_099073_2021-10-08_final
2021-10-10 08:15:09	ga_ls7e_ard_3-2-0_090083_2021-10-09_final
2021-10-12 09:35:54	ga_ls7e_ard_3-2-0_104069_2021-10-12_final
2021-10-13 08:42:12	ga_ls7e_ard_3-2-0_095074_2021-10-12_final
2021-10-15 10:10:08	ga_ls7e_ard_3-2-0_109078_2021-10-15_final
2021-10-17 08:20:19	ga_ls7e_ard_3-2-0_091082_2021-10-16_final
2021-10-17 08:21:54	ga_ls7e_ard_3-2-0_091086_2021-10-16_final
2021-10-26 09:48:12	ga_ls7e_ard_3-2-0_106072_2021-10-26_final
2021-10-27 08:52:53	ga_ls7e_ard_3-2-0_097073_2021-10-26_final
2021-10-27 08:55:41	ga_ls7e_ard_3-2-0_097080_2021-10-26_final
2021-10-28 09:35:15	ga_ls7e_ard_3-2-0_104071_2021-10-28_final
2021-10-28 09:36:27	ga_ls7e_ard_3-2-0_104074_2021-10-28_final
2021-10-31 08:29:24	ga_ls7e_ard_3-2-0_093077_2021-10-30_final
2021-10-31 08:29:48	ga_ls7e_ard_3-2-0_093078_2021-10-30_final
2021-11-05 10:26:20	ga_ls7e_ard_3-2-0_112077_2021-11-05_final
2021-11-16 08:29:27	ga_ls7e_ard_3-2-1_093081_2021-11-15_final
2021-11-25 09:57:41	ga_ls7e_ard_3-2-1_108072_2021-11-25_final
2021-12-02 08:27:32	ga_ls7e_ard_3-2-1_093080_2021-12-01_final
2021-12-02 10:06:24	ga_ls7e_ard_3-2-1_109080_2021-12-02_final
2021-12-05 08:55:21	ga_ls7e_ard_3-2-1_098073_2021-12-04_final
2021-12-12 09:00:52	ga_ls7e_ard_3-2-1_099073_2021-12-11_final
2021-12-13 09:47:37	ga_ls7e_ard_3-2-1_106082_2021-12-13_final
2021-12-14 10:29:11	ga_ls7e_ard_3-2-1_113078_2021-12-14_final
2021-12-16 08:37:22	ga_ls7e_ard_3-2-1_095077_2021-12-15_final
2021-12-17 09:19:20	ga_ls7e_ard_3-2-1_102074_2021-12-16_final
2021-12-17 09:20:55	ga_ls7e_ard_3-2-1_102078_2021-12-16_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-21 08:54:37	ga_ls7e_ard_3-2-1_098075_2021-12-20_final
2021-12-23 10:23:20	ga_ls7e_ard_3-2-1_112081_2021-12-23_final
2021-12-25 08:31:30	ga_ls7e_ard_3-2-1_094080_2021-12-24_final
2021-12-26 09:13:04	ga_ls7e_ard_3-2-1_101076_2021-12-25_final
2021-12-30 08:47:56	ga_ls7e_ard_3-2-1_097076_2021-12-29_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-08 10:20:32	ga_ls7e_ard_3-2-1_112078_2022-01-08_final
2022-01-09 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-10 08:31:07	ga_ls7e_ard_3-2-1_094083_2022-01-09_final
2022-01-11 09:13:29	ga_ls7e_ard_3-2-1_101081_2022-01-10_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-13 08:57:45	ga_ls7e_ard_3-2-1_099073_2022-01-12_final
2022-01-15 10:26:04	ga_ls7e_ard_3-2-1_113078_2022-01-15_final
2022-01-18 09:17:00	ga_ls7e_ard_3-2-1_102076_2022-01-17_final
2022-01-21 09:49:37	ga_ls7e_ard_3-2-1_107081_2022-01-21_final
2022-01-23 09:36:39	ga_ls7e_ard_3-2-1_105080_2022-01-23_final
2022-01-25 09:23:18	ga_ls7e_ard_3-2-1_103078_2022-01-24_final
2022-01-28 09:53:31	ga_ls7e_ard_3-2-1_108077_2022-01-28_final
2022-01-30 09:42:33	ga_ls7e_ard_3-2-1_106081_2022-01-30_final
2022-02-02 10:11:33	ga_ls7e_ard_3-2-1_111077_2022-02-02_final
2022-02-02 10:12:45	ga_ls7e_ard_3-2-1_111080_2022-02-02_final
2022-02-04 08:20:07	ga_ls7e_ard_3-2-1_093077_2022-02-03_final
2022-02-04 08:23:42	ga_ls7e_ard_3-2-1_093086_2022-02-03_final
2022-02-05 09:04:52	ga_ls7e_ard_3-2-1_100081_2022-02-04_final
2022-02-07 10:29:59	ga_ls7e_ard_3-2-1_114078_2022-02-07_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-09 08:39:20	ga_ls7e_ard_3-2-1_096080_2022-02-08_final
2022-02-09 10:16:37	ga_ls7e_ard_3-2-1_112076_2022-02-09_final
2022-02-11 08:28:46	ga_ls7e_ard_3-2-1_094085_2022-02-10_final
2022-02-11 10:04:03	ga_ls7e_ard_3-2-1_110076_2022-02-11_final
2022-02-13 09:51:29	ga_ls7e_ard_3-2-1_108076_2022-02-13_final
2022-02-14 08:55:21	ga_ls7e_ard_3-2-1_099075_2022-02-13_final
2022-02-18 10:10:43	ga_ls7e_ard_3-2-1_111079_2022-02-18_final
2022-02-19 09:13:24	ga_ls7e_ard_3-2-1_102075_2022-02-18_final
2022-02-24 09:29:53	ga_ls7e_ard_3-2-1_105071_2022-02-23_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-25 08:38:09	ga_ls7e_ard_3-2-1_096081_2022-02-24_final
2022-02-25 08:38:33	ga_ls7e_ard_3-2-1_096082_2022-02-24_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-02 08:56:13	ga_ls7e_ard_3-2-1_099081_2022-03-01_final
2022-03-04 08:42:04	ga_ls7e_ard_3-2-1_097077_2022-03-03_final
2022-03-05 09:22:50	ga_ls7e_ard_3-2-1_104071_2022-03-04_final
2022-03-06 10:09:59	ga_ls7e_ard_3-2-1_111081_2022-03-06_final
2022-03-08 09:56:37	ga_ls7e_ard_3-2-1_109079_2022-03-08_final
2022-03-11 08:47:09	ga_ls7e_ard_3-2-1_098076_2022-03-10_final
2022-03-11 08:48:44	ga_ls7e_ard_3-2-1_098080_2022-03-10_final
2022-03-15 08:22:01	ga_ls7e_ard_3-2-1_094076_2022-03-14_final
2022-03-15 08:23:37	ga_ls7e_ard_3-2-1_094080_2022-03-14_final
2022-03-17 08:10:15	ga_ls7e_ard_3-2-1_092078_2022-03-16_final
2022-03-17 09:49:55	ga_ls7e_ard_3-2-1_108080_2022-03-17_final
2022-03-18 08:51:25	ga_ls7e_ard_3-2-1_099073_2022-03-17_final
2022-03-19 09:36:10	ga_ls7e_ard_3-2-1_106077_2022-03-19_final
2022-03-19 09:38:10	ga_ls7e_ard_3-2-1_106082_2022-03-19_final
2022-03-20 08:42:27	ga_ls7e_ard_3-2-1_097082_2022-03-19_final
2022-03-21 09:21:14	ga_ls7e_ard_3-2-1_104071_2022-03-20_final
2022-03-22 08:27:07	ga_ls7e_ard_3-2-1_095075_2022-03-21_final
2022-03-22 10:06:24	ga_ls7e_ard_3-2-1_111076_2022-03-22_final
2022-03-25 09:00:08	ga_ls7e_ard_3-2-1_100081_2022-03-24_final
2022-03-27 08:45:35	ga_ls7e_ard_3-2-1_098076_2022-03-26_final
2022-03-29 08:34:14	ga_ls7e_ard_3-2-1_096079_2022-03-28_final
2022-03-29 08:35:50	ga_ls7e_ard_3-2-1_096083_2022-03-28_final
2022-03-29 10:13:07	ga_ls7e_ard_3-2-1_112079_2022-03-29_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 08:22:05	ga_ls7e_ard_3-2-1_094080_2022-03-30_final
2022-03-31 09:57:22	ga_ls7e_ard_3-2-1_110071_2022-03-31_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