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 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-18 08:50:12	ga_ls7e_ard_3-2-0_096073_2021-09-17_final
2021-09-18 08:50:35	ga_ls7e_ard_3-2-0_096074_2021-09-17_final
2021-09-18 08:50:59	ga_ls7e_ard_3-2-0_096075_2021-09-17_final
2021-09-18 10:32:16	ga_ls7e_ard_3-2-0_112081_2021-09-18_final
2021-09-20 08:41:15	ga_ls7e_ard_3-2-0_094082_2021-09-19_final
2021-10-26 08:14:07	ga_ls7e_ard_3-2-0_090084_2021-10-25_final
2021-10-26 09:49:48	ga_ls7e_ard_3-2-0_106076_2021-10-26_final
2021-12-18 10:04:53	ga_ls7e_ard_3-2-1_109080_2021-12-18_final
2021-12-18 10:06:05	ga_ls7e_ard_3-2-1_109083_2021-12-18_final
2021-12-19 09:06:46	ga_ls7e_ard_3-2-1_100074_2021-12-18_final
2021-12-23 10:23:20	ga_ls7e_ard_3-2-1_112081_2021-12-23_final
2021-12-25 10:11:34	ga_ls7e_ard_3-2-1_110083_2021-12-25_final
2021-12-25 10:11:58	ga_ls7e_ard_3-2-1_110084_2021-12-25_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-30 08:48:20	ga_ls7e_ard_3-2-1_097077_2021-12-29_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2022-01-01 08:36:58	ga_ls7e_ard_3-2-1_095080_2021-12-31_final
2022-01-03 08:26:24	ga_ls7e_ard_3-2-1_093085_2022-01-02_final
2022-01-03 08:26:48	ga_ls7e_ard_3-2-1_093086_2022-01-02_final
2022-01-03 10:04:05	ga_ls7e_ard_3-2-1_109082_2022-01-03_final
2022-01-08 08:42:52	ga_ls7e_ard_3-2-1_096081_2022-01-07_final
2022-01-08 10:21:44	ga_ls7e_ard_3-2-1_112081_2022-01-08_final
2022-01-09 09:22:02	ga_ls7e_ard_3-2-1_103071_2022-01-08_final
2022-01-09 09:23:14	ga_ls7e_ard_3-2-1_103074_2022-01-08_final
2022-01-10 08:30:43	ga_ls7e_ard_3-2-1_094082_2022-01-09_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-11 09:11:29	ga_ls7e_ard_3-2-1_101076_2022-01-10_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-12 09:57:03	ga_ls7e_ard_3-2-1_108082_2022-01-12_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-19 09:59:22	ga_ls7e_ard_3-2-1_109074_2022-01-19_final
2022-01-21 08:09:56	ga_ls7e_ard_3-2-1_091079_2022-01-20_final
2022-01-21 08:11:08	ga_ls7e_ard_3-2-1_091082_2022-01-20_final
2022-01-21 09:49:13	ga_ls7e_ard_3-2-1_107080_2022-01-21_final
2022-01-21 09:49:37	ga_ls7e_ard_3-2-1_107081_2022-01-21_final
2022-01-24 10:18:37	ga_ls7e_ard_3-2-1_112077_2022-01-24_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-28 08:15:50	ga_ls7e_ard_3-2-1_092080_2022-01-27_final
2022-01-28 08:18:13	ga_ls7e_ard_3-2-1_092086_2022-01-27_final
2022-01-28 09:54:42	ga_ls7e_ard_3-2-1_108080_2022-01-28_final
2022-01-29 08:59:47	ga_ls7e_ard_3-2-1_099082_2022-01-28_final
2022-01-30 08:03:40	ga_ls7e_ard_3-2-1_090081_2022-01-29_final
2022-01-30 09:42:57	ga_ls7e_ard_3-2-1_106082_2022-01-30_final
2022-01-31 08:44:50	ga_ls7e_ard_3-2-1_097076_2022-01-30_final
2022-02-02 08:31:53	ga_ls7e_ard_3-2-1_095075_2022-02-01_final
2022-02-02 10:11:09	ga_ls7e_ard_3-2-1_111076_2022-02-02_final
2022-02-04 08:20:31	ga_ls7e_ard_3-2-1_093078_2022-02-03_final
2022-02-04 08:22:54	ga_ls7e_ard_3-2-1_093084_2022-02-03_final
2022-02-04 08:23:18	ga_ls7e_ard_3-2-1_093085_2022-02-03_final
2022-02-04 10:00:59	ga_ls7e_ard_3-2-1_109082_2022-02-04_final
2022-02-05 09:06:04	ga_ls7e_ard_3-2-1_100084_2022-02-04_final
2022-02-06 08:07:57	ga_ls7e_ard_3-2-1_091078_2022-02-05_final
2022-02-09 08:39:44	ga_ls7e_ard_3-2-1_096081_2022-02-08_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-11 08:26:46	ga_ls7e_ard_3-2-1_094080_2022-02-10_final
2022-02-11 08:27:58	ga_ls7e_ard_3-2-1_094083_2022-02-10_final
2022-02-13 09:54:40	ga_ls7e_ard_3-2-1_108084_2022-02-13_final
2022-02-14 08:57:45	ga_ls7e_ard_3-2-1_099081_2022-02-13_final
2022-02-15 08:01:38	ga_ls7e_ard_3-2-1_090080_2022-02-14_final
2022-02-16 08:45:35	ga_ls7e_ard_3-2-1_097082_2022-02-15_final
2022-02-16 10:22:04	ga_ls7e_ard_3-2-1_113076_2022-02-16_final
2022-02-20 08:21:17	ga_ls7e_ard_3-2-1_093084_2022-02-19_final
2022-02-20 08:22:05	ga_ls7e_ard_3-2-1_093086_2022-02-19_final
2022-02-22 08:05:57	ga_ls7e_ard_3-2-1_091077_2022-02-21_final
2022-02-22 09:46:25	ga_ls7e_ard_3-2-1_107081_2022-02-22_final
2022-02-24 09:29:53	ga_ls7e_ard_3-2-1_105071_2022-02-23_final
2022-02-25 08:38:33	ga_ls7e_ard_3-2-1_096082_2022-02-24_final
2022-02-26 09:20:31	ga_ls7e_ard_3-2-1_103079_2022-02-25_final
2022-02-27 08:25:36	ga_ls7e_ard_3-2-1_094081_2022-02-26_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-02-28 09:08:46	ga_ls7e_ard_3-2-1_101081_2022-02-27_final
2022-03-01 09:52:20	ga_ls7e_ard_3-2-1_108082_2022-03-01_final
2022-03-04 08:41:40	ga_ls7e_ard_3-2-1_097076_2022-03-03_final
2022-03-08 08:16:57	ga_ls7e_ard_3-2-1_093077_2022-03-07_final
2022-03-08 08:20:32	ga_ls7e_ard_3-2-1_093086_2022-03-07_final
2022-03-09 09:00:54	ga_ls7e_ard_3-2-1_100079_2022-03-08_final
2022-03-10 09:44:04	ga_ls7e_ard_3-2-1_107079_2022-03-10_final
2022-03-11 08:49:56	ga_ls7e_ard_3-2-1_098083_2022-03-10_final
2022-03-12 09:28:42	ga_ls7e_ard_3-2-1_105072_2022-03-11_final
2022-03-13 10:14:15	ga_ls7e_ard_3-2-1_112078_2022-03-13_final
2022-03-13 10:15:27	ga_ls7e_ard_3-2-1_112081_2022-03-13_final
2022-03-14 09:18:08	ga_ls7e_ard_3-2-1_103077_2022-03-13_final
2022-03-14 09:18:32	ga_ls7e_ard_3-2-1_103078_2022-03-13_final
2022-03-15 10:00:54	ga_ls7e_ard_3-2-1_110076_2022-03-15_final
2022-03-15 10:02:29	ga_ls7e_ard_3-2-1_110080_2022-03-15_final
2022-03-17 09:46:44	ga_ls7e_ard_3-2-1_108072_2022-03-17_final
2022-03-20 08:40:04	ga_ls7e_ard_3-2-1_097076_2022-03-19_final
2022-03-20 08:40:28	ga_ls7e_ard_3-2-1_097077_2022-03-19_final
2022-03-20 10:18:33	ga_ls7e_ard_3-2-1_113075_2022-03-20_final
2022-03-22 08:29:31	ga_ls7e_ard_3-2-1_095081_2022-03-21_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-26 09:42:54	ga_ls7e_ard_3-2-1_107080_2022-03-26_final
2022-03-27 08:47:35	ga_ls7e_ard_3-2-1_098081_2022-03-26_final
2022-03-28 09:26:46	ga_ls7e_ard_3-2-1_105071_2022-03-27_final
2022-03-28 09:29:33	ga_ls7e_ard_3-2-1_105078_2022-03-27_final
2022-03-29 08:36:14	ga_ls7e_ard_3-2-1_096084_2022-03-28_final
2022-04-02 09:45:13	ga_ls7e_ard_3-2-1_108072_2022-04-02_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