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
2021-03-25 10:04:27	ga_ls7e_ard_3-2-0_105082_2021-03-25_final
2021-09-18 08:50:59	ga_ls7e_ard_3-2-0_096075_2021-09-17_final
2021-09-18 10:31:04	ga_ls7e_ard_3-2-0_112078_2021-09-18_final
2021-09-20 08:41:15	ga_ls7e_ard_3-2-0_094082_2021-09-19_final
2021-10-25 09:07:49	ga_ls7e_ard_3-2-0_099079_2021-10-24_final
2021-10-26 09:49:00	ga_ls7e_ard_3-2-0_106074_2021-10-26_final
2021-11-13 09:35:20	ga_ls7e_ard_3-2-1_104075_2021-11-13_final
2021-11-15 09:25:34	ga_ls7e_ard_3-2-1_102082_2021-11-14_final
2021-11-19 08:56:52	ga_ls7e_ard_3-2-1_098073_2021-11-18_final
2021-11-21 08:43:55	ga_ls7e_ard_3-2-1_096072_2021-11-20_final
2021-11-23 08:34:33	ga_ls7e_ard_3-2-1_094080_2021-11-22_final
2021-11-27 09:45:56	ga_ls7e_ard_3-2-1_106074_2021-11-27_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-11-30 10:18:57	ga_ls7e_ard_3-2-1_111080_2021-11-30_final
2021-11-30 10:20:09	ga_ls7e_ard_3-2-1_111083_2021-11-30_final
2021-12-02 10:06:00	ga_ls7e_ard_3-2-1_109079_2021-12-02_final
2021-12-07 08:43:36	ga_ls7e_ard_3-2-1_096075_2021-12-06_final
2021-12-09 08:33:03	ga_ls7e_ard_3-2-1_094080_2021-12-08_final
2021-12-09 08:33:51	ga_ls7e_ard_3-2-1_094082_2021-12-08_final
2021-12-10 09:13:25	ga_ls7e_ard_3-2-1_101073_2021-12-09_final
2021-12-13 08:09:09	ga_ls7e_ard_3-2-1_090083_2021-12-12_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-14 10:27:36	ga_ls7e_ard_3-2-1_113074_2021-12-14_final
2021-12-14 10:30:23	ga_ls7e_ard_3-2-1_113081_2021-12-14_final
2021-12-17 09:17:20	ga_ls7e_ard_3-2-1_102069_2021-12-16_final
2021-12-20 09:49:32	ga_ls7e_ard_3-2-1_107073_2021-12-20_final
2021-12-23 08:43:15	ga_ls7e_ard_3-2-1_096078_2021-12-22_final
2021-12-23 08:45:39	ga_ls7e_ard_3-2-1_096084_2021-12-22_final
2021-12-25 08:33:53	ga_ls7e_ard_3-2-1_094086_2021-12-24_final
2021-12-27 08:22:32	ga_ls7e_ard_3-2-1_092089_2021-12-26_final
2021-12-28 10:40:34	ga_ls7e_ard_3-2-1_115079_2021-12-28_final
2021-12-29 09:45:39	ga_ls7e_ard_3-2-1_106081_2021-12-29_final
2021-12-30 08:48:20	ga_ls7e_ard_3-2-1_097077_2021-12-29_final
2022-01-03 10:00:29	ga_ls7e_ard_3-2-1_109073_2022-01-03_final
2022-01-03 10:04:05	ga_ls7e_ard_3-2-1_109082_2022-01-03_final
2022-01-14 08:05:13	ga_ls7e_ard_3-2-1_090081_2022-01-13_final
2022-01-15 08:46:00	ga_ls7e_ard_3-2-1_097075_2022-01-14_final
2022-01-16 09:27:10	ga_ls7e_ard_3-2-1_104070_2022-01-15_final
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-19 08:26:05	ga_ls7e_ard_3-2-1_093088_2022-01-18_final
2022-01-21 08:10:44	ga_ls7e_ard_3-2-1_091081_2022-01-20_final
2022-01-21 09:48:01	ga_ls7e_ard_3-2-1_107077_2022-01-21_final
2022-01-24 08:38:33	ga_ls7e_ard_3-2-1_096074_2022-01-23_final
2022-01-28 08:17:02	ga_ls7e_ard_3-2-1_092083_2022-01-27_final
2022-01-28 09:53:55	ga_ls7e_ard_3-2-1_108078_2022-01-28_final
2022-01-30 09:42:33	ga_ls7e_ard_3-2-1_106081_2022-01-30_final
2022-01-31 10:22:55	ga_ls7e_ard_3-2-1_113074_2022-01-31_final
2022-02-05 09:02:52	ga_ls7e_ard_3-2-1_100076_2022-02-04_final
2022-02-05 09:04:04	ga_ls7e_ard_3-2-1_100079_2022-02-04_final
2022-02-06 08:11:08	ga_ls7e_ard_3-2-1_091086_2022-02-05_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-07 08:51:06	ga_ls7e_ard_3-2-1_098078_2022-02-06_final
2022-02-09 08:36:56	ga_ls7e_ard_3-2-1_096074_2022-02-08_final
2022-02-09 10:18:37	ga_ls7e_ard_3-2-1_112081_2022-02-09_final
2022-02-14 08:54:33	ga_ls7e_ard_3-2-1_099073_2022-02-13_final
2022-02-14 08:54:57	ga_ls7e_ard_3-2-1_099074_2022-02-13_final
2022-02-14 08:57:45	ga_ls7e_ard_3-2-1_099081_2022-02-13_final
2022-02-14 08:58:09	ga_ls7e_ard_3-2-1_099082_2022-02-13_final
2022-02-15 08:02:49	ga_ls7e_ard_3-2-1_090083_2022-02-14_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-18 08:29:51	ga_ls7e_ard_3-2-1_095074_2022-02-17_final
2022-02-22 09:42:26	ga_ls7e_ard_3-2-1_107071_2022-02-22_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-23 10:27:35	ga_ls7e_ard_3-2-1_114076_2022-02-23_final
2022-02-25 08:35:22	ga_ls7e_ard_3-2-1_096074_2022-02-24_final
2022-02-25 08:35:46	ga_ls7e_ard_3-2-1_096075_2022-02-24_final
2022-02-26 09:17:20	ga_ls7e_ard_3-2-1_103071_2022-02-25_final
2022-02-27 08:23:12	ga_ls7e_ard_3-2-1_094075_2022-02-26_final
2022-02-27 08:26:00	ga_ls7e_ard_3-2-1_094082_2022-02-26_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-02 08:56:13	ga_ls7e_ard_3-2-1_099081_2022-03-01_final
2022-03-05 09:23:14	ga_ls7e_ard_3-2-1_104072_2022-03-04_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-05 09:24:49	ga_ls7e_ard_3-2-1_104076_2022-03-04_final
2022-03-06 10:07:11	ga_ls7e_ard_3-2-1_111074_2022-03-06_final
2022-03-08 08:19:20	ga_ls7e_ard_3-2-1_093083_2022-03-07_final
2022-03-10 09:42:52	ga_ls7e_ard_3-2-1_107076_2022-03-10_final
2022-03-11 08:46:45	ga_ls7e_ard_3-2-1_098075_2022-03-10_final
2022-03-11 10:27:37	ga_ls7e_ard_3-2-1_114080_2022-03-11_final
2022-03-13 08:35:47	ga_ls7e_ard_3-2-1_096079_2022-03-12_final
2022-03-13 08:38:10	ga_ls7e_ard_3-2-1_096085_2022-03-12_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_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
2022-03-15 08:26:01	ga_ls7e_ard_3-2-1_094086_2022-03-14_final
2022-03-17 08:11:51	ga_ls7e_ard_3-2-1_092082_2022-03-16_final
2022-03-18 08:51:48	ga_ls7e_ard_3-2-1_099074_2022-03-17_final
2022-03-18 08:52:12	ga_ls7e_ard_3-2-1_099075_2022-03-17_final
2022-03-18 08:54:12	ga_ls7e_ard_3-2-1_099080_2022-03-17_final
2022-03-20 08:42:51	ga_ls7e_ard_3-2-1_097083_2022-03-19_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-27 08:44:24	ga_ls7e_ard_3-2-1_098073_2022-03-26_final
2022-03-27 08:47:11	ga_ls7e_ard_3-2-1_098080_2022-03-26_final
2022-03-27 08:47:59	ga_ls7e_ard_3-2-1_098082_2022-03-26_final
2022-03-27 08:48:47	ga_ls7e_ard_3-2-1_098084_2022-03-26_final
2022-03-29 08:35:50	ga_ls7e_ard_3-2-1_096083_2022-03-28_final
2022-03-31 08:24:05	ga_ls7e_ard_3-2-1_094085_2022-03-30_final
2022-04-03 10:30:46	ga_ls7e_ard_3-2-1_115078_2022-04-03_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