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
2021-03-17 09:16:04	ga_ls7e_ard_3-2-0_097083_2021-03-16_final
2021-07-31 08:14:26	ga_ls7e_ard_3-2-0_089081_2021-07-30_final
2021-08-06 10:53:23	ga_ls7e_ard_3-2-0_115078_2021-08-06_final
2021-08-19 10:22:55	ga_ls7e_ard_3-2-0_110082_2021-08-19_final
2021-08-21 08:28:43	ga_ls7e_ard_3-2-0_092075_2021-08-20_final
2021-08-21 08:29:31	ga_ls7e_ard_3-2-0_092077_2021-08-20_final
2021-08-21 10:09:11	ga_ls7e_ard_3-2-0_108079_2021-08-21_final
2021-08-25 09:40:56	ga_ls7e_ard_3-2-0_104071_2021-08-25_final
2021-08-29 09:16:40	ga_ls7e_ard_3-2-0_100073_2021-08-28_final
2021-08-30 09:59:03	ga_ls7e_ard_3-2-0_107071_2021-08-30_final
2021-08-30 10:01:50	ga_ls7e_ard_3-2-0_107078_2021-08-30_final
2021-08-31 09:02:56	ga_ls7e_ard_3-2-0_098070_2021-08-30_final
2021-08-31 10:44:13	ga_ls7e_ard_3-2-0_114076_2021-08-31_final
2021-09-01 08:12:49	ga_ls7e_ard_3-2-0_089084_2021-08-31_final
2021-09-01 09:50:54	ga_ls7e_ard_3-2-0_105082_2021-09-01_final
2021-09-02 08:56:24	ga_ls7e_ard_3-2-0_096085_2021-09-01_final
2021-09-02 10:31:17	ga_ls7e_ard_3-2-0_112075_2021-09-02_final
2021-09-06 10:08:36	ga_ls7e_ard_3-2-0_108081_2021-09-06_final
2021-09-07 09:13:18	ga_ls7e_ard_3-2-0_099082_2021-09-06_final
2021-09-08 08:19:11	ga_ls7e_ard_3-2-0_090086_2021-09-07_final
2021-09-13 08:33:18	ga_ls7e_ard_3-2-0_093076_2021-09-12_final
2021-09-16 10:42:48	ga_ls7e_ard_3-2-0_114076_2021-09-16_final
2021-09-21 09:21:13	ga_ls7e_ard_3-2-0_101074_2021-09-20_final
2021-09-22 10:03:36	ga_ls7e_ard_3-2-0_108072_2021-09-22_final
2021-09-27 08:46:47	ga_ls7e_ard_3-2-0_095082_2021-09-26_final
2021-09-30 09:16:14	ga_ls7e_ard_3-2-0_100079_2021-09-29_final
2021-10-06 08:37:26	ga_ls7e_ard_3-2-0_094076_2021-10-05_final
2021-10-13 08:44:59	ga_ls7e_ard_3-2-0_095081_2021-10-12_final
2021-10-17 08:21:30	ga_ls7e_ard_3-2-0_091085_2021-10-16_final
2021-10-19 08:08:10	ga_ls7e_ard_3-2-0_089083_2021-10-18_final
2021-10-20 08:47:21	ga_ls7e_ard_3-2-0_096073_2021-10-19_final
2021-10-28 09:38:51	ga_ls7e_ard_3-2-0_104080_2021-10-28_final
2021-10-29 10:21:13	ga_ls7e_ard_3-2-0_111078_2021-10-29_final
2021-10-30 09:21:55	ga_ls7e_ard_3-2-0_102069_2021-10-29_final
2021-10-30 09:23:07	ga_ls7e_ard_3-2-0_102072_2021-10-29_final
2021-11-01 09:15:21	ga_ls7e_ard_3-2-0_100084_2021-10-31_final
2021-11-03 08:56:01	ga_ls7e_ard_3-2-0_098067_2021-11-02_final
2021-11-05 10:26:44	ga_ls7e_ard_3-2-0_112078_2021-11-05_final
2021-11-09 08:25:57	ga_ls7e_ard_3-2-0_092086_2021-11-08_final
2021-11-12 08:50:34	ga_ls7e_ard_3-2-0_097071_2021-11-11_final
2021-11-13 09:34:56	ga_ls7e_ard_3-2-1_104074_2021-11-13_final
2021-11-18 08:14:54	ga_ls7e_ard_3-2-1_091076_2021-11-17_final
2021-11-19 10:36:56	ga_ls7e_ard_3-2-1_114076_2021-11-19_final
2021-11-23 10:13:25	ga_ls7e_ard_3-2-1_110080_2021-11-23_final
2021-11-28 08:53:25	ga_ls7e_ard_3-2-1_097082_2021-11-27_final
2021-12-01 09:21:39	ga_ls7e_ard_3-2-1_102076_2021-11-30_final
2021-12-09 08:32:15	ga_ls7e_ard_3-2-1_094078_2021-12-08_final
2021-12-17 09:20:07	ga_ls7e_ard_3-2-1_102076_2021-12-16_final
2021-12-21 10:33:30	ga_ls7e_ard_3-2-1_114075_2021-12-21_final
2021-12-23 08:44:27	ga_ls7e_ard_3-2-1_096081_2021-12-22_final
2021-12-23 10:22:56	ga_ls7e_ard_3-2-1_112080_2021-12-23_final
2021-12-24 09:26:01	ga_ls7e_ard_3-2-1_103077_2021-12-23_final
2022-01-01 10:12:15	ga_ls7e_ard_3-2-1_111071_2022-01-01_final
2022-01-01 10:16:39	ga_ls7e_ard_3-2-1_111082_2022-01-01_final
2022-01-03 10:02:53	ga_ls7e_ard_3-2-1_109079_2022-01-03_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-05 08:11:02	ga_ls7e_ard_3-2-1_091078_2022-01-04_final
2022-01-05 09:49:55	ga_ls7e_ard_3-2-1_107078_2022-01-05_final
2022-01-08 10:20:09	ga_ls7e_ard_3-2-1_112077_2022-01-08_final
2022-01-09 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-10 08:31:31	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 10:04:48	ga_ls7e_ard_3-2-1_110070_2022-01-10_final
2022-01-10 10:10:23	ga_ls7e_ard_3-2-1_110084_2022-01-10_final
2022-01-12 09:57:27	ga_ls7e_ard_3-2-1_108083_2022-01-12_final
2022-01-14 08:08:49	ga_ls7e_ard_3-2-1_090090_2022-01-13_final
2022-01-14 09:42:30	ga_ls7e_ard_3-2-1_106077_2022-01-14_final
2022-01-18 09:14:13	ga_ls7e_ard_3-2-1_102069_2022-01-17_final
2022-01-21 09:48:01	ga_ls7e_ard_3-2-1_107077_2022-01-21_final
2022-01-26 08:27:11	ga_ls7e_ard_3-2-1_094077_2022-01-25_final
2022-01-28 08:17:02	ga_ls7e_ard_3-2-1_092083_2022-01-27_final
2022-01-30 08:06:52	ga_ls7e_ard_3-2-1_090089_2022-01-29_final
2022-01-30 09:41:21	ga_ls7e_ard_3-2-1_106078_2022-01-30_final
2022-02-04 08:21:19	ga_ls7e_ard_3-2-1_093080_2022-02-03_final
2022-02-04 08:21:43	ga_ls7e_ard_3-2-1_093081_2022-02-03_final
2022-02-04 08:22:54	ga_ls7e_ard_3-2-1_093084_2022-02-03_final
2022-02-04 08:23:42	ga_ls7e_ard_3-2-1_093086_2022-02-03_final
2022-02-09 10:17:01	ga_ls7e_ard_3-2-1_112077_2022-02-09_final
2022-02-11 08:25:34	ga_ls7e_ard_3-2-1_094077_2022-02-10_final
2022-02-15 09:36:31	ga_ls7e_ard_3-2-1_106070_2022-02-15_final
2022-02-21 09:02:51	ga_ls7e_ard_3-2-1_100080_2022-02-20_final
2022-02-26 09:19:19	ga_ls7e_ard_3-2-1_103076_2022-02-25_final
2022-02-27 08:26:00	ga_ls7e_ard_3-2-1_094082_2022-02-26_final
2022-03-01 09:52:20	ga_ls7e_ard_3-2-1_108082_2022-03-01_final
2022-03-06 08:30:18	ga_ls7e_ard_3-2-1_095079_2022-03-05_final
2022-03-06 08:32:18	ga_ls7e_ard_3-2-1_095084_2022-03-05_final
2022-03-07 09:12:40	ga_ls7e_ard_3-2-1_102077_2022-03-06_final
2022-03-09 09:01:42	ga_ls7e_ard_3-2-1_100081_2022-03-08_final
2022-03-17 09:49:07	ga_ls7e_ard_3-2-1_108078_2022-03-17_final
2022-03-22 10:05:36	ga_ls7e_ard_3-2-1_111074_2022-03-22_final
2022-03-24 08:18:58	ga_ls7e_ard_3-2-1_093086_2022-03-23_final
2022-03-24 09:55:03	ga_ls7e_ard_3-2-1_109079_2022-03-24_final
2022-03-25 08:59:44	ga_ls7e_ard_3-2-1_100080_2022-03-24_final
2022-03-27 08:49:11	ga_ls7e_ard_3-2-1_098085_2022-03-26_final
2022-03-29 08:33:26	ga_ls7e_ard_3-2-1_096077_2022-03-28_final
2022-03-29 08:33:50	ga_ls7e_ard_3-2-1_096078_2022-03-28_final
2022-03-30 09:17:24	ga_ls7e_ard_3-2-1_103079_2022-03-29_final
2022-03-31 09:58:10	ga_ls7e_ard_3-2-1_110073_2022-03-31_final
2022-03-31 09:59:22	ga_ls7e_ard_3-2-1_110076_2022-03-31_final
2022-04-03 08:53:05	ga_ls7e_ard_3-2-1_099081_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years