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 08:50:12	ga_ls7e_ard_3-2-0_096073_2021-09-17_final
2021-09-18 08:50:35	ga_ls7e_ard_3-2-0_096074_2021-09-17_final
2021-09-18 08:53:47	ga_ls7e_ard_3-2-0_096082_2021-09-17_final
2021-09-20 10:15:44	ga_ls7e_ard_3-2-0_110071_2021-09-20_final
2021-10-25 09:06:14	ga_ls7e_ard_3-2-0_099075_2021-10-24_final
2021-10-26 09:49:00	ga_ls7e_ard_3-2-0_106074_2021-10-26_final
2021-11-15 09:22:46	ga_ls7e_ard_3-2-1_102075_2021-11-14_final
2021-11-16 10:06:44	ga_ls7e_ard_3-2-1_109077_2021-11-16_final
2021-11-19 10:38:08	ga_ls7e_ard_3-2-1_114079_2021-11-19_final
2021-11-20 09:38:02	ga_ls7e_ard_3-2-1_105068_2021-11-20_final
2021-11-22 09:29:28	ga_ls7e_ard_3-2-1_103078_2021-11-21_final
2021-11-26 10:42:27	ga_ls7e_ard_3-2-1_115076_2021-11-26_final
2021-11-27 08:13:03	ga_ls7e_ard_3-2-1_090089_2021-11-26_final
2021-11-28 08:49:26	ga_ls7e_ard_3-2-1_097072_2021-11-27_final
2021-11-28 08:51:25	ga_ls7e_ard_3-2-1_097077_2021-11-27_final
2021-12-03 09:10:42	ga_ls7e_ard_3-2-1_100080_2021-12-02_final
2021-12-09 10:12:43	ga_ls7e_ard_3-2-1_110082_2021-12-09_final
2021-12-10 09:15:01	ga_ls7e_ard_3-2-1_101077_2021-12-09_final
2021-12-10 09:15:25	ga_ls7e_ard_3-2-1_101078_2021-12-09_final
2021-12-14 08:48:19	ga_ls7e_ard_3-2-1_097073_2021-12-13_final
2021-12-18 08:25:36	ga_ls7e_ard_3-2-1_093079_2021-12-17_final
2021-12-18 10:04:53	ga_ls7e_ard_3-2-1_109080_2021-12-18_final
2021-12-21 08:54:13	ga_ls7e_ard_3-2-1_098074_2021-12-20_final
2021-12-21 10:33:54	ga_ls7e_ard_3-2-1_114076_2021-12-21_final
2021-12-22 09:38:11	ga_ls7e_ard_3-2-1_105076_2021-12-22_final
2021-12-23 08:42:04	ga_ls7e_ard_3-2-1_096075_2021-12-22_final
2021-12-23 08:42:28	ga_ls7e_ard_3-2-1_096076_2021-12-22_final
2021-12-23 10:23:20	ga_ls7e_ard_3-2-1_112081_2021-12-23_final
2021-12-25 08:31:30	ga_ls7e_ard_3-2-1_094080_2021-12-24_final
2021-12-25 10:07:35	ga_ls7e_ard_3-2-1_110073_2021-12-25_final
2021-12-26 09:15:27	ga_ls7e_ard_3-2-1_101082_2021-12-25_final
2021-12-27 09:58:13	ga_ls7e_ard_3-2-1_108081_2021-12-27_final
2021-12-29 09:42:51	ga_ls7e_ard_3-2-1_106074_2021-12-29_final
2021-12-30 08:48:20	ga_ls7e_ard_3-2-1_097077_2021-12-29_final
2021-12-30 10:29:36	ga_ls7e_ard_3-2-1_113083_2021-12-30_final
2022-01-01 10:17:03	ga_ls7e_ard_3-2-1_111083_2022-01-01_final
2022-01-02 09:19:43	ga_ls7e_ard_3-2-1_102079_2022-01-01_final
2022-01-04 09:04:22	ga_ls7e_ard_3-2-1_100072_2022-01-03_final
2022-01-04 09:05:34	ga_ls7e_ard_3-2-1_100075_2022-01-03_final
2022-01-07 09:35:23	ga_ls7e_ard_3-2-1_105073_2022-01-07_final
2022-01-08 10:22:08	ga_ls7e_ard_3-2-1_112082_2022-01-08_final
2022-01-09 09:23:38	ga_ls7e_ard_3-2-1_103075_2022-01-08_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-12 09:55:27	ga_ls7e_ard_3-2-1_108078_2022-01-12_final
2022-01-15 08:44:24	ga_ls7e_ard_3-2-1_097071_2022-01-14_final
2022-01-17 10:13:31	ga_ls7e_ard_3-2-1_111078_2022-01-17_final
2022-01-19 09:58:58	ga_ls7e_ard_3-2-1_109073_2022-01-19_final
2022-01-21 08:11:56	ga_ls7e_ard_3-2-1_091084_2022-01-20_final
2022-01-22 10:32:22	ga_ls7e_ard_3-2-1_114080_2022-01-22_final
2022-01-23 07:57:47	ga_ls7e_ard_3-2-1_089080_2022-01-22_final
2022-01-24 08:40:09	ga_ls7e_ard_3-2-1_096078_2022-01-23_final
2022-01-24 10:20:37	ga_ls7e_ard_3-2-1_112082_2022-01-24_final
2022-02-02 10:11:57	ga_ls7e_ard_3-2-1_111078_2022-02-02_final
2022-02-03 09:16:38	ga_ls7e_ard_3-2-1_102079_2022-02-02_final
2022-02-05 09:03:16	ga_ls7e_ard_3-2-1_100077_2022-02-04_final
2022-02-07 08:49:07	ga_ls7e_ard_3-2-1_098073_2022-02-06_final
2022-02-08 07:57:47	ga_ls7e_ard_3-2-1_089084_2022-02-07_final
2022-02-08 09:31:28	ga_ls7e_ard_3-2-1_105071_2022-02-08_final
2022-02-09 08:35:45	ga_ls7e_ard_3-2-1_096071_2022-02-08_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-09 10:18:37	ga_ls7e_ard_3-2-1_112081_2022-02-09_final
2022-02-10 09:20:54	ga_ls7e_ard_3-2-1_103076_2022-02-09_final
2022-02-11 08:24:46	ga_ls7e_ard_3-2-1_094075_2022-02-10_final
2022-02-11 08:26:46	ga_ls7e_ard_3-2-1_094080_2022-02-10_final
2022-02-16 08:43:59	ga_ls7e_ard_3-2-1_097078_2022-02-15_final
2022-02-18 08:29:27	ga_ls7e_ard_3-2-1_095073_2022-02-17_final
2022-02-18 10:09:55	ga_ls7e_ard_3-2-1_111077_2022-02-18_final
2022-02-22 09:42:26	ga_ls7e_ard_3-2-1_107071_2022-02-22_final
2022-02-26 09:20:07	ga_ls7e_ard_3-2-1_103078_2022-02-25_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-02-28 09:07:34	ga_ls7e_ard_3-2-1_101078_2022-02-27_final
2022-02-28 09:08:22	ga_ls7e_ard_3-2-1_101080_2022-02-27_final
2022-02-28 09:08:46	ga_ls7e_ard_3-2-1_101081_2022-02-27_final
2022-03-01 09:52:43	ga_ls7e_ard_3-2-1_108083_2022-03-01_final
2022-03-04 08:44:27	ga_ls7e_ard_3-2-1_097083_2022-03-03_final
2022-03-04 10:22:32	ga_ls7e_ard_3-2-1_113081_2022-03-04_final
2022-03-08 08:19:20	ga_ls7e_ard_3-2-1_093083_2022-03-07_final
2022-03-13 08:38:34	ga_ls7e_ard_3-2-1_096086_2022-03-12_final
2022-03-14 09:16:32	ga_ls7e_ard_3-2-1_103073_2022-03-13_final
2022-03-15 10:02:29	ga_ls7e_ard_3-2-1_110080_2022-03-15_final
2022-03-18 08:54:12	ga_ls7e_ard_3-2-1_099080_2022-03-17_final
2022-03-20 10:18:33	ga_ls7e_ard_3-2-1_113075_2022-03-20_final
2022-03-20 10:18:56	ga_ls7e_ard_3-2-1_113076_2022-03-20_final
2022-03-21 09:22:26	ga_ls7e_ard_3-2-1_104074_2022-03-20_final
2022-03-22 08:30:43	ga_ls7e_ard_3-2-1_095084_2022-03-21_final
2022-03-22 10:07:12	ga_ls7e_ard_3-2-1_111078_2022-03-22_final
2022-03-26 08:02:26	ga_ls7e_ard_3-2-1_091076_2022-03-25_final
2022-03-28 09:25:58	ga_ls7e_ard_3-2-1_105069_2022-03-27_final
2022-03-29 10:14:43	ga_ls7e_ard_3-2-1_112083_2022-03-29_final
2022-03-30 09:14:12	ga_ls7e_ard_3-2-1_103071_2022-03-29_final
2022-03-30 09:16:12	ga_ls7e_ard_3-2-1_103076_2022-03-29_final
2022-03-31 09:58:10	ga_ls7e_ard_3-2-1_110073_2022-03-31_final
2022-03-31 10:01:46	ga_ls7e_ard_3-2-1_110082_2022-03-31_final
2022-04-03 10:30:46	ga_ls7e_ard_3-2-1_115078_2022-04-03_final
2022-04-04 09:31:27	ga_ls7e_ard_3-2-1_106069_2022-04-04_final
2022-04-04 09:31:51	ga_ls7e_ard_3-2-1_106070_2022-04-04_final
2022-04-04 09:33:03	ga_ls7e_ard_3-2-1_106073_2022-04-04_final
2022-04-04 09:35:27	ga_ls7e_ard_3-2-1_106079_2022-04-04_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