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 08:54:11	ga_ls7e_ard_3-2-0_096083_2021-09-17_final
2021-09-20 08:41:15	ga_ls7e_ard_3-2-0_094082_2021-09-19_final
2021-09-22 08:29:30	ga_ls7e_ard_3-2-0_092084_2021-09-21_final
2021-09-22 10:07:35	ga_ls7e_ard_3-2-0_108082_2021-09-22_final
2021-09-24 09:54:15	ga_ls7e_ard_3-2-0_106080_2021-09-24_final
2021-09-25 08:55:45	ga_ls7e_ard_3-2-0_097073_2021-09-24_final
2021-09-25 08:58:56	ga_ls7e_ard_3-2-0_097081_2021-09-24_final
2021-09-26 09:38:31	ga_ls7e_ard_3-2-0_104072_2021-09-26_final
2021-09-28 09:27:34	ga_ls7e_ard_3-2-0_102076_2021-09-27_final
2021-09-29 10:08:20	ga_ls7e_ard_3-2-0_109070_2021-09-29_final
2021-10-01 09:57:00	ga_ls7e_ard_3-2-0_107073_2021-10-01_final
2021-10-13 10:18:17	ga_ls7e_ard_3-2-0_111067_2021-10-13_final
2021-10-13 10:21:52	ga_ls7e_ard_3-2-0_111076_2021-10-13_final
2021-10-14 09:25:22	ga_ls7e_ard_3-2-0_102074_2021-10-13_final
2021-10-18 10:39:58	ga_ls7e_ard_3-2-0_114076_2021-10-18_final
2021-10-20 10:27:25	ga_ls7e_ard_3-2-0_112076_2021-10-20_final
2021-10-23 09:18:46	ga_ls7e_ard_3-2-0_101075_2021-10-22_final
2021-10-27 08:54:53	ga_ls7e_ard_3-2-0_097078_2021-10-26_final
2021-10-29 08:43:32	ga_ls7e_ard_3-2-0_095081_2021-10-28_final
2021-10-29 10:20:25	ga_ls7e_ard_3-2-0_111076_2021-10-29_final
2021-10-29 10:22:25	ga_ls7e_ard_3-2-0_111081_2021-10-29_final
2021-11-02 09:53:44	ga_ls7e_ard_3-2-0_107072_2021-11-02_final
2021-11-03 10:38:29	ga_ls7e_ard_3-2-0_114076_2021-11-03_final
2021-11-04 09:40:47	ga_ls7e_ard_3-2-0_105071_2021-11-04_final
2021-11-05 10:25:32	ga_ls7e_ard_3-2-0_112075_2021-11-05_final
2021-11-05 10:25:56	ga_ls7e_ard_3-2-0_112076_2021-11-05_final
2021-11-06 09:30:14	ga_ls7e_ard_3-2-0_103076_2021-11-06_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-10 09:07:07	ga_ls7e_ard_3-2-0_099081_2021-11-09_final
2021-11-12 08:52:58	ga_ls7e_ard_3-2-0_097077_2021-11-11_final
2021-11-13 09:34:08	ga_ls7e_ard_3-2-1_104072_2021-11-13_final
2021-11-23 08:34:09	ga_ls7e_ard_3-2-1_094079_2021-11-22_final
2021-11-23 08:35:20	ga_ls7e_ard_3-2-1_094082_2021-11-22_final
2021-11-26 09:03:10	ga_ls7e_ard_3-2-1_099075_2021-11-25_final
2021-11-26 10:42:51	ga_ls7e_ard_3-2-1_115077_2021-11-26_final
2021-11-29 09:32:12	ga_ls7e_ard_3-2-1_104071_2021-11-29_final
2021-11-29 09:33:23	ga_ls7e_ard_3-2-1_104074_2021-11-29_final
2021-11-29 09:34:35	ga_ls7e_ard_3-2-1_104077_2021-11-29_final
2021-11-30 08:39:16	ga_ls7e_ard_3-2-1_095078_2021-11-29_final
2021-12-05 08:58:57	ga_ls7e_ard_3-2-1_098082_2021-12-04_final
2021-12-06 09:40:55	ga_ls7e_ard_3-2-1_105079_2021-12-06_final
2021-12-07 08:43:12	ga_ls7e_ard_3-2-1_096074_2021-12-06_final
2021-12-09 10:11:55	ga_ls7e_ard_3-2-1_110080_2021-12-09_final
2021-12-13 09:47:13	ga_ls7e_ard_3-2-1_106081_2021-12-13_final
2021-12-13 09:47:37	ga_ls7e_ard_3-2-1_106082_2021-12-13_final
2021-12-14 08:51:54	ga_ls7e_ard_3-2-1_097082_2021-12-13_final
2021-12-16 08:37:46	ga_ls7e_ard_3-2-1_095078_2021-12-15_final
2021-12-16 08:39:45	ga_ls7e_ard_3-2-1_095083_2021-12-15_final
2021-12-17 09:19:20	ga_ls7e_ard_3-2-1_102074_2021-12-16_final
2021-12-18 08:24:25	ga_ls7e_ard_3-2-1_093076_2021-12-17_final
2021-12-18 10:03:41	ga_ls7e_ard_3-2-1_109077_2021-12-18_final
2021-12-19 09:09:10	ga_ls7e_ard_3-2-1_100080_2021-12-18_final
2021-12-21 08:53:49	ga_ls7e_ard_3-2-1_098073_2021-12-20_final
2021-12-27 08:22:32	ga_ls7e_ard_3-2-1_092089_2021-12-26_final
2022-01-03 08:24:24	ga_ls7e_ard_3-2-1_093080_2022-01-02_final
2022-01-03 10:00:05	ga_ls7e_ard_3-2-1_109072_2022-01-03_final
2022-01-06 08:53:25	ga_ls7e_ard_3-2-1_098076_2022-01-05_final
2022-01-06 10:32:17	ga_ls7e_ard_3-2-1_114076_2022-01-06_final
2022-01-06 10:32:41	ga_ls7e_ard_3-2-1_114077_2022-01-06_final
2022-01-07 09:38:10	ga_ls7e_ard_3-2-1_105080_2022-01-07_final
2022-01-10 08:30:19	ga_ls7e_ard_3-2-1_094081_2022-01-09_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-10 08:31:55	ga_ls7e_ard_3-2-1_094085_2022-01-09_final
2022-01-10 10:09:12	ga_ls7e_ard_3-2-1_110081_2022-01-10_final
2022-01-12 09:56:39	ga_ls7e_ard_3-2-1_108081_2022-01-12_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-19 09:58:34	ga_ls7e_ard_3-2-1_109072_2022-01-19_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-21 09:47:13	ga_ls7e_ard_3-2-1_107075_2022-01-21_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-28 09:54:42	ga_ls7e_ard_3-2-1_108080_2022-01-28_final
2022-01-29 10:35:28	ga_ls7e_ard_3-2-1_115074_2022-01-29_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-30 09:42:09	ga_ls7e_ard_3-2-1_106080_2022-01-30_final
2022-02-04 08:20:31	ga_ls7e_ard_3-2-1_093078_2022-02-03_final
2022-02-05 09:04:04	ga_ls7e_ard_3-2-1_100079_2022-02-04_final
2022-02-09 10:18:37	ga_ls7e_ard_3-2-1_112081_2022-02-09_final
2022-02-10 09:18:54	ga_ls7e_ard_3-2-1_103071_2022-02-09_final
2022-02-10 09:22:29	ga_ls7e_ard_3-2-1_103080_2022-02-09_final
2022-02-17 09:27:33	ga_ls7e_ard_3-2-1_104079_2022-02-16_final
2022-02-19 09:13:24	ga_ls7e_ard_3-2-1_102075_2022-02-18_final
2022-02-20 08:21:17	ga_ls7e_ard_3-2-1_093084_2022-02-19_final
2022-02-22 09:44:49	ga_ls7e_ard_3-2-1_107077_2022-02-22_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-23 10:27:11	ga_ls7e_ard_3-2-1_114075_2022-02-23_final
2022-02-26 09:16:56	ga_ls7e_ard_3-2-1_103070_2022-02-25_final
2022-02-28 09:05:34	ga_ls7e_ard_3-2-1_101073_2022-02-27_final
2022-03-14 09:17:44	ga_ls7e_ard_3-2-1_103076_2022-03-13_final
2022-03-14 09:18:32	ga_ls7e_ard_3-2-1_103078_2022-03-13_final
2022-03-21 09:24:26	ga_ls7e_ard_3-2-1_104079_2022-03-20_final
2022-03-23 09:12:17	ga_ls7e_ard_3-2-1_102080_2022-03-22_final
2022-03-24 08:16:34	ga_ls7e_ard_3-2-1_093080_2022-03-23_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-30 09:13:25	ga_ls7e_ard_3-2-1_103069_2022-03-29_final
2022-03-30 09:16:36	ga_ls7e_ard_3-2-1_103077_2022-03-29_final
2022-03-31 08:19:41	ga_ls7e_ard_3-2-1_094074_2022-03-30_final
2022-03-31 10:00:34	ga_ls7e_ard_3-2-1_110079_2022-03-31_final
2022-04-01 09:01:15	ga_ls7e_ard_3-2-1_101070_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