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 08:49:24	ga_ls7e_ard_3-2-0_096071_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
2021-09-18 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
2021-11-14 08:40:25	ga_ls7e_ard_3-2-1_095077_2021-11-13_final
2021-11-14 10:19:17	ga_ls7e_ard_3-2-1_111077_2021-11-14_final
2021-11-17 09:10:13	ga_ls7e_ard_3-2-1_100075_2021-11-16_final
2021-11-19 10:36:08	ga_ls7e_ard_3-2-1_114074_2021-11-19_final
2021-11-19 10:37:20	ga_ls7e_ard_3-2-1_114077_2021-11-19_final
2021-11-21 08:45:06	ga_ls7e_ard_3-2-1_096075_2021-11-20_final
2021-11-23 10:09:50	ga_ls7e_ard_3-2-1_110071_2021-11-23_final
2021-11-25 10:00:04	ga_ls7e_ard_3-2-1_108078_2021-11-25_final
2021-11-25 10:00:52	ga_ls7e_ard_3-2-1_108080_2021-11-25_final
2021-11-29 09:34:59	ga_ls7e_ard_3-2-1_104078_2021-11-29_final
2021-12-04 08:16:11	ga_ls7e_ard_3-2-1_091083_2021-12-03_final
2021-12-05 08:56:09	ga_ls7e_ard_3-2-1_098075_2021-12-04_final
2021-12-07 08:44:24	ga_ls7e_ard_3-2-1_096077_2021-12-06_final
2021-12-07 10:23:41	ga_ls7e_ard_3-2-1_112078_2021-12-07_final
2021-12-11 09:58:11	ga_ls7e_ard_3-2-1_108077_2021-12-11_final
2021-12-12 10:40:33	ga_ls7e_ard_3-2-1_115075_2021-12-12_final
2021-12-13 08:10:21	ga_ls7e_ard_3-2-1_090086_2021-12-12_final
2021-12-16 10:18:38	ga_ls7e_ard_3-2-1_111083_2021-12-16_final
2021-12-17 09:17:20	ga_ls7e_ard_3-2-1_102069_2021-12-16_final
2021-12-17 09:21:19	ga_ls7e_ard_3-2-1_102079_2021-12-16_final
2021-12-18 08:26:24	ga_ls7e_ard_3-2-1_093081_2021-12-17_final
2021-12-21 08:53:01	ga_ls7e_ard_3-2-1_098071_2021-12-20_final
2021-12-24 09:24:25	ga_ls7e_ard_3-2-1_103073_2021-12-23_final
2021-12-25 08:31:54	ga_ls7e_ard_3-2-1_094081_2021-12-24_final
2021-12-27 09:57:01	ga_ls7e_ard_3-2-1_108078_2021-12-27_final
2021-12-29 09:42:51	ga_ls7e_ard_3-2-1_106074_2021-12-29_final
2021-12-30 08:47:32	ga_ls7e_ard_3-2-1_097075_2021-12-29_final
2021-12-30 08:48:44	ga_ls7e_ard_3-2-1_097078_2021-12-29_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2021-12-30 10:29:12	ga_ls7e_ard_3-2-1_113082_2021-12-30_final
2022-01-01 08:34:58	ga_ls7e_ard_3-2-1_095075_2021-12-31_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
2022-01-02 09:16:56	ga_ls7e_ard_3-2-1_102072_2022-01-01_final
2022-01-06 10:34:17	ga_ls7e_ard_3-2-1_114081_2022-01-06_final
2022-01-07 09:37:46	ga_ls7e_ard_3-2-1_105079_2022-01-07_final
2022-01-14 08:04:01	ga_ls7e_ard_3-2-1_090078_2022-01-13_final
2022-01-14 08:04:25	ga_ls7e_ard_3-2-1_090079_2022-01-13_final
2022-01-16 09:27:10	ga_ls7e_ard_3-2-1_104070_2022-01-15_final
2022-01-21 08:11:56	ga_ls7e_ard_3-2-1_091084_2022-01-20_final
2022-01-21 09:48:49	ga_ls7e_ard_3-2-1_107079_2022-01-21_final
2022-01-24 08:37:45	ga_ls7e_ard_3-2-1_096072_2022-01-23_final
2022-01-26 10:07:16	ga_ls7e_ard_3-2-1_110080_2022-01-26_final
2022-01-31 08:46:26	ga_ls7e_ard_3-2-1_097080_2022-01-30_final
2022-02-02 08:34:16	ga_ls7e_ard_3-2-1_095081_2022-02-01_final
2022-02-02 10:13:57	ga_ls7e_ard_3-2-1_111083_2022-02-02_final
2022-02-04 08:24:06	ga_ls7e_ard_3-2-1_093087_2022-02-03_final
2022-02-07 08:52:42	ga_ls7e_ard_3-2-1_098082_2022-02-06_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-13 09:50:41	ga_ls7e_ard_3-2-1_108074_2022-02-13_final
2022-02-16 08:43:35	ga_ls7e_ard_3-2-1_097077_2022-02-15_final
2022-02-17 09:27:33	ga_ls7e_ard_3-2-1_104079_2022-02-16_final
2022-02-18 08:30:38	ga_ls7e_ard_3-2-1_095076_2022-02-17_final
2022-02-18 08:31:50	ga_ls7e_ard_3-2-1_095079_2022-02-17_final
2022-02-18 10:09:55	ga_ls7e_ard_3-2-1_111077_2022-02-18_final
2022-02-22 09:46:25	ga_ls7e_ard_3-2-1_107081_2022-02-22_final
2022-02-23 08:47:31	ga_ls7e_ard_3-2-1_098073_2022-02-22_final
2022-02-23 10:29:35	ga_ls7e_ard_3-2-1_114081_2022-02-23_final
2022-02-24 09:29:53	ga_ls7e_ard_3-2-1_105071_2022-02-23_final
2022-02-24 09:31:28	ga_ls7e_ard_3-2-1_105075_2022-02-24_final
2022-02-24 09:33:04	ga_ls7e_ard_3-2-1_105079_2022-02-24_final
2022-02-26 09:20:31	ga_ls7e_ard_3-2-1_103079_2022-02-25_final
2022-02-28 09:08:22	ga_ls7e_ard_3-2-1_101080_2022-02-27_final
2022-03-01 08:13:27	ga_ls7e_ard_3-2-1_092082_2022-02-28_final
2022-03-04 08:41:16	ga_ls7e_ard_3-2-1_097075_2022-03-03_final
2022-03-06 10:09:35	ga_ls7e_ard_3-2-1_111080_2022-03-06_final
2022-03-08 08:16:57	ga_ls7e_ard_3-2-1_093077_2022-03-07_final
2022-03-09 08:58:30	ga_ls7e_ard_3-2-1_100073_2022-03-08_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-11 08:46:45	ga_ls7e_ard_3-2-1_098075_2022-03-10_final
2022-03-12 09:32:42	ga_ls7e_ard_3-2-1_105082_2022-03-12_final
2022-03-13 08:37:23	ga_ls7e_ard_3-2-1_096083_2022-03-12_final
2022-03-13 10:13:04	ga_ls7e_ard_3-2-1_112075_2022-03-13_final
2022-03-15 08:21:37	ga_ls7e_ard_3-2-1_094075_2022-03-14_final
2022-03-18 10:32:17	ga_ls7e_ard_3-2-1_115078_2022-03-18_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-20 08:41:40	ga_ls7e_ard_3-2-1_097080_2022-03-19_final
2022-03-21 09:21:14	ga_ls7e_ard_3-2-1_104071_2022-03-20_final
2022-03-22 08:27:31	ga_ls7e_ard_3-2-1_095076_2022-03-21_final
2022-03-24 08:14:10	ga_ls7e_ard_3-2-1_093074_2022-03-23_final
2022-03-24 08:15:22	ga_ls7e_ard_3-2-1_093077_2022-03-23_final
2022-03-24 08:15:46	ga_ls7e_ard_3-2-1_093078_2022-03-23_final
2022-03-26 08:02:49	ga_ls7e_ard_3-2-1_091077_2022-03-25_final
2022-03-28 09:26:46	ga_ls7e_ard_3-2-1_105071_2022-03-27_final
2022-03-29 08:35:02	ga_ls7e_ard_3-2-1_096081_2022-03-28_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_final
2022-03-31 08:19:17	ga_ls7e_ard_3-2-1_094073_2022-03-30_final
2022-03-31 08:19:41	ga_ls7e_ard_3-2-1_094074_2022-03-30_final
2022-03-31 08:23:17	ga_ls7e_ard_3-2-1_094083_2022-03-30_final
2022-03-31 10:00:34	ga_ls7e_ard_3-2-1_110079_2022-03-31_final
2022-04-01 09:06:03	ga_ls7e_ard_3-2-1_101082_2022-03-31_final
2022-04-02 08:07:32	ga_ls7e_ard_3-2-1_092075_2022-04-01_final
2022-04-02 09:45:37	ga_ls7e_ard_3-2-1_108073_2022-04-02_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_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