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 08:51:23	ga_ls7e_ard_3-2-0_096076_2021-09-17_final
2021-09-18 08:52:11	ga_ls7e_ard_3-2-0_096078_2021-09-17_final
2021-09-18 10:29:52	ga_ls7e_ard_3-2-0_112075_2021-09-18_final
2021-09-20 08:38:27	ga_ls7e_ard_3-2-0_094075_2021-09-19_final
2021-10-25 09:05:26	ga_ls7e_ard_3-2-0_099073_2021-10-24_final
2021-10-26 09:48:12	ga_ls7e_ard_3-2-0_106072_2021-10-26_final
2021-11-04 09:45:10	ga_ls7e_ard_3-2-0_105082_2021-11-04_final
2021-11-05 08:49:03	ga_ls7e_ard_3-2-0_096081_2021-11-04_final
2021-11-05 08:49:51	ga_ls7e_ard_3-2-0_096083_2021-11-04_final
2021-11-09 08:23:33	ga_ls7e_ard_3-2-0_092080_2021-11-08_final
2021-11-09 09:59:14	ga_ls7e_ard_3-2-0_108072_2021-11-09_final
2021-11-09 10:00:50	ga_ls7e_ard_3-2-0_108076_2021-11-09_final
2021-11-12 10:31:51	ga_ls7e_ard_3-2-1_113077_2021-11-12_final
2021-11-14 08:40:25	ga_ls7e_ard_3-2-1_095077_2021-11-13_final
2021-11-14 08:41:13	ga_ls7e_ard_3-2-1_095079_2021-11-13_final
2021-11-16 08:29:27	ga_ls7e_ard_3-2-1_093081_2021-11-15_final
2021-11-17 09:12:37	ga_ls7e_ard_3-2-1_100081_2021-11-16_final
2021-12-02 08:28:43	ga_ls7e_ard_3-2-1_093083_2021-12-01_final
2021-12-02 10:06:48	ga_ls7e_ard_3-2-1_109081_2021-12-02_final
2021-12-04 09:51:04	ga_ls7e_ard_3-2-1_107073_2021-12-04_final
2021-12-06 09:41:19	ga_ls7e_ard_3-2-1_105080_2021-12-06_final
2021-12-10 09:14:37	ga_ls7e_ard_3-2-1_101076_2021-12-09_final
2021-12-10 09:16:37	ga_ls7e_ard_3-2-1_101081_2021-12-09_final
2021-12-13 09:46:02	ga_ls7e_ard_3-2-1_106078_2021-12-13_final
2021-12-22 09:38:58	ga_ls7e_ard_3-2-1_105078_2021-12-22_final
2021-12-23 10:22:56	ga_ls7e_ard_3-2-1_112080_2021-12-23_final
2021-12-25 08:29:54	ga_ls7e_ard_3-2-1_094076_2021-12-24_final
2021-12-26 09:14:39	ga_ls7e_ard_3-2-1_101080_2021-12-25_final
2021-12-27 08:19:20	ga_ls7e_ard_3-2-1_092081_2021-12-26_final
2021-12-27 09:57:01	ga_ls7e_ard_3-2-1_108078_2021-12-27_final
2022-01-01 08:36:34	ga_ls7e_ard_3-2-1_095079_2021-12-31_final
2022-01-01 10:15:03	ga_ls7e_ard_3-2-1_111078_2022-01-01_final
2022-01-01 10:15:51	ga_ls7e_ard_3-2-1_111080_2022-01-01_final
2022-01-02 09:17:44	ga_ls7e_ard_3-2-1_102074_2022-01-01_final
2022-01-03 08:24:24	ga_ls7e_ard_3-2-1_093080_2022-01-02_final
2022-01-03 10:02:53	ga_ls7e_ard_3-2-1_109079_2022-01-03_final
2022-01-04 09:07:10	ga_ls7e_ard_3-2-1_100079_2022-01-03_final
2022-01-05 09:50:43	ga_ls7e_ard_3-2-1_107080_2022-01-05_final
2022-01-06 08:55:24	ga_ls7e_ard_3-2-1_098081_2022-01-05_final
2022-01-08 08:42:04	ga_ls7e_ard_3-2-1_096079_2022-01-07_final
2022-01-12 08:19:46	ga_ls7e_ard_3-2-1_092086_2022-01-11_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-13 09:01:20	ga_ls7e_ard_3-2-1_099082_2022-01-12_final
2022-01-14 08:06:01	ga_ls7e_ard_3-2-1_090083_2022-01-13_final
2022-01-17 10:13:55	ga_ls7e_ard_3-2-1_111079_2022-01-17_final
2022-01-18 09:16:12	ga_ls7e_ard_3-2-1_102074_2022-01-17_final
2022-01-19 08:24:29	ga_ls7e_ard_3-2-1_093084_2022-01-18_final
2022-01-19 08:25:17	ga_ls7e_ard_3-2-1_093086_2022-01-18_final
2022-01-19 10:02:10	ga_ls7e_ard_3-2-1_109081_2022-01-19_final
2022-01-23 09:36:39	ga_ls7e_ard_3-2-1_105080_2022-01-23_final
2022-01-24 10:19:49	ga_ls7e_ard_3-2-1_112080_2022-01-24_final
2022-01-26 08:31:11	ga_ls7e_ard_3-2-1_094087_2022-01-25_final
2022-01-30 09:42:33	ga_ls7e_ard_3-2-1_106081_2022-01-30_final
2022-01-31 08:46:26	ga_ls7e_ard_3-2-1_097080_2022-01-30_final
2022-02-02 10:12:45	ga_ls7e_ard_3-2-1_111080_2022-02-02_final
2022-02-06 09:47:37	ga_ls7e_ard_3-2-1_107080_2022-02-06_final
2022-02-09 08:39:20	ga_ls7e_ard_3-2-1_096080_2022-02-08_final
2022-02-09 10:18:13	ga_ls7e_ard_3-2-1_112080_2022-02-09_final
2022-02-10 09:22:05	ga_ls7e_ard_3-2-1_103079_2022-02-09_final
2022-02-11 08:28:46	ga_ls7e_ard_3-2-1_094085_2022-02-10_final
2022-02-11 10:03:39	ga_ls7e_ard_3-2-1_110075_2022-02-11_final
2022-02-14 08:58:09	ga_ls7e_ard_3-2-1_099082_2022-02-13_final
2022-02-15 08:02:01	ga_ls7e_ard_3-2-1_090081_2022-02-14_final
2022-02-18 08:32:38	ga_ls7e_ard_3-2-1_095081_2022-02-17_final
2022-02-21 09:02:51	ga_ls7e_ard_3-2-1_100080_2022-02-20_final
2022-02-22 09:44:49	ga_ls7e_ard_3-2-1_107077_2022-02-22_final
2022-02-24 09:33:04	ga_ls7e_ard_3-2-1_105079_2022-02-24_final
2022-02-25 08:36:09	ga_ls7e_ard_3-2-1_096076_2022-02-24_final
2022-02-25 10:15:02	ga_ls7e_ard_3-2-1_112076_2022-02-25_final
2022-02-26 09:17:20	ga_ls7e_ard_3-2-1_103071_2022-02-25_final
2022-02-27 10:03:41	ga_ls7e_ard_3-2-1_110079_2022-02-27_final
2022-03-01 09:49:56	ga_ls7e_ard_3-2-1_108076_2022-03-01_final
2022-03-01 09:51:32	ga_ls7e_ard_3-2-1_108080_2022-03-01_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-06 08:30:18	ga_ls7e_ard_3-2-1_095079_2022-03-05_final
2022-03-06 08:32:42	ga_ls7e_ard_3-2-1_095085_2022-03-05_final
2022-03-08 08:18:33	ga_ls7e_ard_3-2-1_093081_2022-03-07_final
2022-03-09 09:01:42	ga_ls7e_ard_3-2-1_100081_2022-03-08_final
2022-03-10 09:41:40	ga_ls7e_ard_3-2-1_107073_2022-03-10_final
2022-03-13 08:35:47	ga_ls7e_ard_3-2-1_096079_2022-03-12_final
2022-03-13 08:37:23	ga_ls7e_ard_3-2-1_096083_2022-03-12_final
2022-03-13 10:14:39	ga_ls7e_ard_3-2-1_112079_2022-03-13_final
2022-03-14 09:16:56	ga_ls7e_ard_3-2-1_103074_2022-03-13_final
2022-03-18 08:51:48	ga_ls7e_ard_3-2-1_099074_2022-03-17_final
2022-03-22 08:27:31	ga_ls7e_ard_3-2-1_095076_2022-03-21_final
2022-03-22 08:30:19	ga_ls7e_ard_3-2-1_095083_2022-03-21_final
2022-03-23 09:10:17	ga_ls7e_ard_3-2-1_102075_2022-03-22_final
2022-03-24 08:16:34	ga_ls7e_ard_3-2-1_093080_2022-03-23_final
2022-03-26 09:42:30	ga_ls7e_ard_3-2-1_107079_2022-03-26_final
2022-03-29 08:36:38	ga_ls7e_ard_3-2-1_096085_2022-03-28_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_final
2022-03-30 09:13:49	ga_ls7e_ard_3-2-1_103070_2022-03-29_final
2022-03-30 09:15:48	ga_ls7e_ard_3-2-1_103075_2022-03-29_final
2022-03-31 08:20:29	ga_ls7e_ard_3-2-1_094076_2022-03-30_final
2022-03-31 08:21:41	ga_ls7e_ard_3-2-1_094079_2022-03-30_final
2022-03-31 08:22:29	ga_ls7e_ard_3-2-1_094081_2022-03-30_final
2022-04-01 09:05:39	ga_ls7e_ard_3-2-1_101081_2022-03-31_final
2022-04-02 08:09:56	ga_ls7e_ard_3-2-1_092081_2022-04-01_final
2022-04-04 09:34:39	ga_ls7e_ard_3-2-1_106077_2022-04-04_final
2022-04-06 09:19:18	ga_ls7e_ard_3-2-1_104070_2022-04-05_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