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
2021-09-20 10:16:08	ga_ls7e_ard_3-2-0_110072_2021-09-20_final
2021-09-25 08:54:57	ga_ls7e_ard_3-2-0_097071_2021-09-24_final
2021-09-25 10:37:49	ga_ls7e_ard_3-2-0_113081_2021-09-25_final
2021-09-27 08:44:48	ga_ls7e_ard_3-2-0_095077_2021-09-26_final
2021-10-06 08:41:25	ga_ls7e_ard_3-2-0_094086_2021-10-05_final
2021-10-07 09:18:36	ga_ls7e_ard_3-2-0_101071_2021-10-06_final
2021-10-08 10:02:35	ga_ls7e_ard_3-2-0_108073_2021-10-08_final
2021-10-10 08:13:57	ga_ls7e_ard_3-2-0_090080_2021-10-09_final
2021-10-11 08:57:31	ga_ls7e_ard_3-2-0_097081_2021-10-10_final
2021-10-17 08:18:43	ga_ls7e_ard_3-2-0_091078_2021-10-16_final
2021-10-17 09:58:23	ga_ls7e_ard_3-2-0_107080_2021-10-17_final
2021-10-19 08:06:10	ga_ls7e_ard_3-2-0_089078_2021-10-18_final
2021-10-20 08:48:09	ga_ls7e_ard_3-2-0_096075_2021-10-19_final
2021-10-22 10:16:52	ga_ls7e_ard_3-2-0_110081_2021-10-22_final
2021-10-24 10:02:20	ga_ls7e_ard_3-2-0_108076_2021-10-24_final
2021-10-25 09:03:02	ga_ls7e_ard_3-2-0_099067_2021-10-24_final
2021-10-25 09:03:50	ga_ls7e_ard_3-2-0_099069_2021-10-24_final
2021-10-26 08:12:07	ga_ls7e_ard_3-2-0_090079_2021-10-25_final
2021-10-26 08:14:31	ga_ls7e_ard_3-2-0_090085_2021-10-25_final
2021-10-27 08:53:41	ga_ls7e_ard_3-2-0_097075_2021-10-26_final
2021-10-31 08:29:00	ga_ls7e_ard_3-2-0_093076_2021-10-30_final
2021-10-31 08:29:48	ga_ls7e_ard_3-2-0_093078_2021-10-30_final
2021-11-01 09:12:10	ga_ls7e_ard_3-2-0_100076_2021-10-31_final
2021-11-01 09:13:21	ga_ls7e_ard_3-2-0_100079_2021-10-31_final
2021-11-02 08:21:38	ga_ls7e_ard_3-2-0_091089_2021-11-01_final
2021-11-08 09:19:40	ga_ls7e_ard_3-2-0_101081_2021-11-07_final
2021-11-09 10:00:50	ga_ls7e_ard_3-2-0_108076_2021-11-09_final
2021-11-17 09:12:37	ga_ls7e_ard_3-2-1_100081_2021-11-16_final
2021-11-18 08:17:18	ga_ls7e_ard_3-2-1_091082_2021-11-17_final
2021-11-18 09:52:11	ga_ls7e_ard_3-2-1_107072_2021-11-18_final
2021-11-19 08:56:52	ga_ls7e_ard_3-2-1_098073_2021-11-18_final
2021-11-19 10:38:32	ga_ls7e_ard_3-2-1_114080_2021-11-19_final
2021-11-23 10:13:01	ga_ls7e_ard_3-2-1_110079_2021-11-23_final
2021-11-25 09:59:40	ga_ls7e_ard_3-2-1_108077_2021-11-25_final
2021-11-26 09:01:34	ga_ls7e_ard_3-2-1_099071_2021-11-25_final
2021-11-30 10:20:09	ga_ls7e_ard_3-2-1_111083_2021-11-30_final
2021-12-04 09:49:52	ga_ls7e_ard_3-2-1_107070_2021-12-04_final
2021-12-09 08:31:03	ga_ls7e_ard_3-2-1_094075_2021-12-08_final
2021-12-10 09:14:13	ga_ls7e_ard_3-2-1_101075_2021-12-09_final
2021-12-14 10:29:59	ga_ls7e_ard_3-2-1_113080_2021-12-14_final
2021-12-25 08:32:18	ga_ls7e_ard_3-2-1_094082_2021-12-24_final
2021-12-28 09:02:30	ga_ls7e_ard_3-2-1_099081_2021-12-27_final
2021-12-29 08:08:46	ga_ls7e_ard_3-2-1_090086_2021-12-28_final
2022-01-01 08:36:58	ga_ls7e_ard_3-2-1_095080_2021-12-31_final
2022-01-02 09:20:07	ga_ls7e_ard_3-2-1_102080_2022-01-01_final
2022-01-03 10:04:05	ga_ls7e_ard_3-2-1_109082_2022-01-03_final
2022-01-05 08:15:26	ga_ls7e_ard_3-2-1_091089_2022-01-04_final
2022-01-06 10:31:53	ga_ls7e_ard_3-2-1_114075_2022-01-06_final
2022-01-08 10:21:20	ga_ls7e_ard_3-2-1_112080_2022-01-08_final
2022-01-13 10:37:01	ga_ls7e_ard_3-2-1_115074_2022-01-13_final
2022-01-14 09:38:55	ga_ls7e_ard_3-2-1_106068_2022-01-14_final
2022-01-17 08:34:38	ga_ls7e_ard_3-2-1_095078_2022-01-16_final
2022-01-17 08:35:02	ga_ls7e_ard_3-2-1_095079_2022-01-16_final
2022-01-17 08:35:50	ga_ls7e_ard_3-2-1_095081_2022-01-16_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-17 10:14:43	ga_ls7e_ard_3-2-1_111081_2022-01-17_final
2022-01-21 09:48:25	ga_ls7e_ard_3-2-1_107078_2022-01-21_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-24 08:38:57	ga_ls7e_ard_3-2-1_096075_2022-01-23_final
2022-01-24 10:19:01	ga_ls7e_ard_3-2-1_112078_2022-01-24_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-31 10:22:55	ga_ls7e_ard_3-2-1_113074_2022-01-31_final
2022-02-02 10:12:21	ga_ls7e_ard_3-2-1_111079_2022-02-02_final
2022-02-05 09:04:04	ga_ls7e_ard_3-2-1_100079_2022-02-04_final
2022-02-06 09:44:02	ga_ls7e_ard_3-2-1_107071_2022-02-06_final
2022-02-09 10:16:13	ga_ls7e_ard_3-2-1_112075_2022-02-09_final
2022-02-09 10:16:37	ga_ls7e_ard_3-2-1_112076_2022-02-09_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-10 09:20:54	ga_ls7e_ard_3-2-1_103076_2022-02-09_final
2022-02-11 10:03:15	ga_ls7e_ard_3-2-1_110074_2022-02-11_final
2022-02-13 09:51:53	ga_ls7e_ard_3-2-1_108077_2022-02-13_final
2022-02-13 09:52:17	ga_ls7e_ard_3-2-1_108078_2022-02-13_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-18 08:31:26	ga_ls7e_ard_3-2-1_095078_2022-02-17_final
2022-02-19 09:13:24	ga_ls7e_ard_3-2-1_102075_2022-02-18_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-03-01 08:12:15	ga_ls7e_ard_3-2-1_092079_2022-02-28_final
2022-03-02 08:56:37	ga_ls7e_ard_3-2-1_099082_2022-03-01_final
2022-03-04 08:39:16	ga_ls7e_ard_3-2-1_097070_2022-03-03_final
2022-03-06 08:27:31	ga_ls7e_ard_3-2-1_095072_2022-03-05_final
2022-03-06 10:09:11	ga_ls7e_ard_3-2-1_111079_2022-03-06_final
2022-03-10 09:42:52	ga_ls7e_ard_3-2-1_107076_2022-03-10_final
2022-03-17 08:09:03	ga_ls7e_ard_3-2-1_092075_2022-03-16_final
2022-03-17 08:09:51	ga_ls7e_ard_3-2-1_092077_2022-03-16_final
2022-03-17 09:47:32	ga_ls7e_ard_3-2-1_108074_2022-03-17_final
2022-03-17 09:48:44	ga_ls7e_ard_3-2-1_108077_2022-03-17_final
2022-03-20 08:43:15	ga_ls7e_ard_3-2-1_097084_2022-03-19_final
2022-03-22 08:27:55	ga_ls7e_ard_3-2-1_095077_2022-03-21_final
2022-03-22 08:28:43	ga_ls7e_ard_3-2-1_095079_2022-03-21_final
2022-03-22 08:29:07	ga_ls7e_ard_3-2-1_095080_2022-03-21_final
2022-03-23 09:10:17	ga_ls7e_ard_3-2-1_102075_2022-03-22_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-26 08:08:01	ga_ls7e_ard_3-2-1_091090_2022-03-25_final
2022-03-26 09:41:18	ga_ls7e_ard_3-2-1_107076_2022-03-26_final
2022-03-27 08:48:47	ga_ls7e_ard_3-2-1_098084_2022-03-26_final
2022-03-30 09:16:12	ga_ls7e_ard_3-2-1_103076_2022-03-29_final
2022-03-31 08:21:17	ga_ls7e_ard_3-2-1_094078_2022-03-30_final
2022-04-01 09:05:39	ga_ls7e_ard_3-2-1_101081_2022-03-31_final
2022-04-03 08:52:41	ga_ls7e_ard_3-2-1_099080_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