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 08:49:00	ga_ls7e_ard_3-2-0_096070_2021-09-17_final
2021-09-20 08:38:03	ga_ls7e_ard_3-2-0_094074_2021-09-19_final
2021-10-25 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-11-01 09:11:22	ga_ls7e_ard_3-2-0_100074_2021-10-31_final
2021-11-01 09:13:45	ga_ls7e_ard_3-2-0_100080_2021-10-31_final
2021-11-02 08:21:14	ga_ls7e_ard_3-2-0_091088_2021-11-01_final
2021-11-03 08:57:13	ga_ls7e_ard_3-2-0_098070_2021-11-02_final
2021-11-03 10:40:29	ga_ls7e_ard_3-2-0_114081_2021-11-03_final
2021-11-05 08:48:16	ga_ls7e_ard_3-2-0_096079_2021-11-04_final
2021-11-06 09:29:02	ga_ls7e_ard_3-2-0_103073_2021-11-05_final
2021-11-06 09:29:26	ga_ls7e_ard_3-2-0_103074_2021-11-05_final
2021-11-09 08:25:09	ga_ls7e_ard_3-2-0_092084_2021-11-08_final
2021-11-14 10:15:42	ga_ls7e_ard_3-2-1_111068_2021-11-14_final
2021-11-14 10:21:17	ga_ls7e_ard_3-2-1_111082_2021-11-14_final
2021-11-16 08:27:27	ga_ls7e_ard_3-2-1_093076_2021-11-15_final
2021-11-16 10:03:56	ga_ls7e_ard_3-2-1_109070_2021-11-16_final
2021-11-17 09:09:25	ga_ls7e_ard_3-2-1_100073_2021-11-16_final
2021-11-25 10:00:28	ga_ls7e_ard_3-2-1_108079_2021-11-25_final
2021-11-28 08:53:25	ga_ls7e_ard_3-2-1_097082_2021-11-27_final
2021-12-03 09:08:42	ga_ls7e_ard_3-2-1_100075_2021-12-02_final
2021-12-04 09:50:40	ga_ls7e_ard_3-2-1_107072_2021-12-04_final
2021-12-08 09:28:46	ga_ls7e_ard_3-2-1_103080_2021-12-07_final
2021-12-11 09:56:11	ga_ls7e_ard_3-2-1_108072_2021-12-11_final
2021-12-12 08:59:40	ga_ls7e_ard_3-2-1_099070_2021-12-11_final
2021-12-12 09:04:28	ga_ls7e_ard_3-2-1_099082_2021-12-11_final
2021-12-12 10:40:57	ga_ls7e_ard_3-2-1_115076_2021-12-12_final
2021-12-13 09:44:26	ga_ls7e_ard_3-2-1_106074_2021-12-13_final
2021-12-14 08:47:55	ga_ls7e_ard_3-2-1_097072_2021-12-13_final
2021-12-14 10:30:47	ga_ls7e_ard_3-2-1_113082_2021-12-14_final
2021-12-16 08:39:45	ga_ls7e_ard_3-2-1_095083_2021-12-15_final
2021-12-16 10:15:50	ga_ls7e_ard_3-2-1_111076_2021-12-16_final
2021-12-23 10:23:44	ga_ls7e_ard_3-2-1_112082_2021-12-23_final
2021-12-25 10:11:58	ga_ls7e_ard_3-2-1_110084_2021-12-25_final
2021-12-27 08:19:20	ga_ls7e_ard_3-2-1_092081_2021-12-26_final
2021-12-27 08:19:44	ga_ls7e_ard_3-2-1_092082_2021-12-26_final
2021-12-27 09:58:37	ga_ls7e_ard_3-2-1_108082_2021-12-27_final
2021-12-30 08:49:08	ga_ls7e_ard_3-2-1_097079_2021-12-29_final
2021-12-31 09:29:06	ga_ls7e_ard_3-2-1_104071_2021-12-30_final
2021-12-31 09:29:30	ga_ls7e_ard_3-2-1_104072_2021-12-30_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-01 08:38:10	ga_ls7e_ard_3-2-1_095083_2021-12-31_final
2022-01-01 08:38:34	ga_ls7e_ard_3-2-1_095084_2021-12-31_final
2022-01-02 09:18:08	ga_ls7e_ard_3-2-1_102075_2022-01-01_final
2022-01-03 08:26:00	ga_ls7e_ard_3-2-1_093084_2022-01-02_final
2022-01-03 10:00:05	ga_ls7e_ard_3-2-1_109072_2022-01-03_final
2022-01-03 10:02:05	ga_ls7e_ard_3-2-1_109077_2022-01-03_final
2022-01-04 09:07:33	ga_ls7e_ard_3-2-1_100080_2022-01-03_final
2022-01-05 09:50:43	ga_ls7e_ard_3-2-1_107080_2022-01-05_final
2022-01-05 09:51:31	ga_ls7e_ard_3-2-1_107082_2022-01-05_final
2022-01-08 10:21:44	ga_ls7e_ard_3-2-1_112081_2022-01-08_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-10 10:09:59	ga_ls7e_ard_3-2-1_110083_2022-01-10_final
2022-01-12 08:19:22	ga_ls7e_ard_3-2-1_092085_2022-01-11_final
2022-01-14 08:05:13	ga_ls7e_ard_3-2-1_090081_2022-01-13_final
2022-01-15 08:45:12	ga_ls7e_ard_3-2-1_097073_2022-01-14_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-25 09:23:42	ga_ls7e_ard_3-2-1_103079_2022-01-24_final
2022-01-30 08:03:40	ga_ls7e_ard_3-2-1_090081_2022-01-29_final
2022-01-30 09:43:21	ga_ls7e_ard_3-2-1_106083_2022-01-30_final
2022-02-03 09:15:50	ga_ls7e_ard_3-2-1_102077_2022-02-02_final
2022-02-04 08:21:19	ga_ls7e_ard_3-2-1_093080_2022-02-03_final
2022-02-06 08:07:57	ga_ls7e_ard_3-2-1_091078_2022-02-05_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-10 09:21:18	ga_ls7e_ard_3-2-1_103077_2022-02-09_final
2022-02-11 08:28:22	ga_ls7e_ard_3-2-1_094084_2022-02-10_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-15 08:02:25	ga_ls7e_ard_3-2-1_090082_2022-02-14_final
2022-02-16 10:22:04	ga_ls7e_ard_3-2-1_113076_2022-02-16_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-19 09:13:48	ga_ls7e_ard_3-2-1_102076_2022-02-18_final
2022-02-20 08:19:17	ga_ls7e_ard_3-2-1_093079_2022-02-19_final
2022-02-22 08:07:08	ga_ls7e_ard_3-2-1_091080_2022-02-21_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-24 09:30:17	ga_ls7e_ard_3-2-1_105072_2022-02-24_final
2022-02-26 09:20:55	ga_ls7e_ard_3-2-1_103080_2022-02-25_final
2022-02-26 09:21:43	ga_ls7e_ard_3-2-1_103082_2022-02-25_final
2022-02-27 10:04:53	ga_ls7e_ard_3-2-1_110082_2022-02-27_final
2022-03-01 09:51:56	ga_ls7e_ard_3-2-1_108081_2022-03-01_final
2022-03-03 08:00:30	ga_ls7e_ard_3-2-1_090081_2022-03-02_final
2022-03-04 10:22:32	ga_ls7e_ard_3-2-1_113081_2022-03-04_final
2022-03-04 10:22:56	ga_ls7e_ard_3-2-1_113082_2022-03-04_final
2022-03-08 08:18:33	ga_ls7e_ard_3-2-1_093081_2022-03-07_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-13 08:33:23	ga_ls7e_ard_3-2-1_096073_2022-03-12_final
2022-03-13 08:36:59	ga_ls7e_ard_3-2-1_096082_2022-03-12_final
2022-03-13 08:38:10	ga_ls7e_ard_3-2-1_096085_2022-03-12_final
2022-03-18 10:30:41	ga_ls7e_ard_3-2-1_115074_2022-03-18_final
2022-03-19 09:34:11	ga_ls7e_ard_3-2-1_106072_2022-03-19_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-23 09:09:05	ga_ls7e_ard_3-2-1_102072_2022-03-22_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-26 09:40:30	ga_ls7e_ard_3-2-1_107074_2022-03-26_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_2022-04-03_final
2022-04-04 09:32:39	ga_ls7e_ard_3-2-1_106072_2022-04-04_final
2022-04-05 08:39:44	ga_ls7e_ard_3-2-1_097079_2022-04-04_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