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
2021-10-06 10:19:06	ga_ls7e_ard_3-2-0_110083_2021-10-06_final
2021-10-08 10:01:23	ga_ls7e_ard_3-2-0_108070_2021-10-08_final
2021-10-08 10:02:35	ga_ls7e_ard_3-2-0_108073_2021-10-08_final
2021-10-09 09:05:40	ga_ls7e_ard_3-2-0_099070_2021-10-08_final
2021-10-10 09:49:15	ga_ls7e_ard_3-2-0_106071_2021-10-10_final
2021-10-11 08:53:08	ga_ls7e_ard_3-2-0_097070_2021-10-10_final
2021-10-11 10:30:49	ga_ls7e_ard_3-2-0_113067_2021-10-11_final
2021-10-20 08:46:09	ga_ls7e_ard_3-2-0_096070_2021-10-19_final
2021-10-21 09:28:55	ga_ls7e_ard_3-2-0_103069_2021-10-20_final
2021-10-23 09:21:34	ga_ls7e_ard_3-2-0_101082_2021-10-22_final
2021-10-24 08:23:28	ga_ls7e_ard_3-2-0_092076_2021-10-23_final
2021-10-24 08:25:51	ga_ls7e_ard_3-2-0_092082_2021-10-23_final
2021-10-25 10:44:42	ga_ls7e_ard_3-2-0_115074_2021-10-25_final
2021-10-29 08:40:44	ga_ls7e_ard_3-2-0_095074_2021-10-28_final
2021-10-29 08:44:44	ga_ls7e_ard_3-2-0_095084_2021-10-28_final
2021-10-29 10:22:49	ga_ls7e_ard_3-2-0_111082_2021-10-29_final
2021-10-30 09:23:54	ga_ls7e_ard_3-2-0_102074_2021-10-29_final
2021-11-01 09:14:57	ga_ls7e_ard_3-2-0_100083_2021-10-31_final
2021-11-03 08:58:49	ga_ls7e_ard_3-2-0_098074_2021-11-02_final
2021-11-07 08:35:19	ga_ls7e_ard_3-2-0_094078_2021-11-06_final
2021-11-07 10:12:59	ga_ls7e_ard_3-2-0_110075_2021-11-07_final
2021-11-08 09:18:52	ga_ls7e_ard_3-2-0_101079_2021-11-07_final
2021-11-08 09:19:40	ga_ls7e_ard_3-2-0_101081_2021-11-07_final
2021-11-14 08:38:49	ga_ls7e_ard_3-2-1_095073_2021-11-13_final
2021-11-16 08:28:15	ga_ls7e_ard_3-2-1_093078_2021-11-15_final
2021-11-18 09:51:23	ga_ls7e_ard_3-2-1_107070_2021-11-18_final
2021-11-19 10:36:32	ga_ls7e_ard_3-2-1_114075_2021-11-19_final
2021-11-19 10:36:56	ga_ls7e_ard_3-2-1_114076_2021-11-19_final
2021-11-19 10:37:44	ga_ls7e_ard_3-2-1_114078_2021-11-19_final
2021-11-21 08:49:06	ga_ls7e_ard_3-2-1_096085_2021-11-20_final
2021-11-26 09:05:34	ga_ls7e_ard_3-2-1_099081_2021-11-25_final
2021-11-28 08:48:14	ga_ls7e_ard_3-2-1_097069_2021-11-27_final
2021-11-28 08:48:38	ga_ls7e_ard_3-2-1_097070_2021-11-27_final
2021-11-28 08:52:13	ga_ls7e_ard_3-2-1_097079_2021-11-27_final
2021-11-30 10:19:45	ga_ls7e_ard_3-2-1_111082_2021-11-30_final
2021-12-01 09:20:03	ga_ls7e_ard_3-2-1_102072_2021-11-30_final
2021-12-02 08:29:55	ga_ls7e_ard_3-2-1_093086_2021-12-01_final
2021-12-02 10:05:36	ga_ls7e_ard_3-2-1_109078_2021-12-02_final
2021-12-03 09:07:54	ga_ls7e_ard_3-2-1_100073_2021-12-02_final
2021-12-04 09:51:52	ga_ls7e_ard_3-2-1_107075_2021-12-04_final
2021-12-07 10:26:04	ga_ls7e_ard_3-2-1_112084_2021-12-07_final
2021-12-10 09:17:24	ga_ls7e_ard_3-2-1_101083_2021-12-09_final
2021-12-14 10:27:36	ga_ls7e_ard_3-2-1_113074_2021-12-14_final
2021-12-14 10:28:00	ga_ls7e_ard_3-2-1_113075_2021-12-14_final
2021-12-18 08:28:24	ga_ls7e_ard_3-2-1_093086_2021-12-17_final
2021-12-20 08:12:39	ga_ls7e_ard_3-2-1_091078_2021-12-19_final
2021-12-20 09:49:56	ga_ls7e_ard_3-2-1_107074_2021-12-20_final
2021-12-20 09:53:32	ga_ls7e_ard_3-2-1_107083_2021-12-20_final
2021-12-21 08:55:49	ga_ls7e_ard_3-2-1_098078_2021-12-20_final
2021-12-23 08:46:27	ga_ls7e_ard_3-2-1_096086_2021-12-22_final
2021-12-25 10:07:35	ga_ls7e_ard_3-2-1_110073_2021-12-25_final
2021-12-25 10:08:23	ga_ls7e_ard_3-2-1_110075_2021-12-25_final
2021-12-27 09:58:13	ga_ls7e_ard_3-2-1_108081_2021-12-27_final
2021-12-29 08:07:58	ga_ls7e_ard_3-2-1_090084_2021-12-28_final
2021-12-30 08:51:08	ga_ls7e_ard_3-2-1_097084_2021-12-29_final
2022-01-01 10:17:26	ga_ls7e_ard_3-2-1_111084_2022-01-01_final
2022-01-02 09:16:08	ga_ls7e_ard_3-2-1_102070_2022-01-01_final
2022-01-03 08:23:36	ga_ls7e_ard_3-2-1_093078_2022-01-02_final
2022-01-03 08:27:12	ga_ls7e_ard_3-2-1_093087_2022-01-02_final
2022-01-06 10:33:53	ga_ls7e_ard_3-2-1_114080_2022-01-06_final
2022-01-12 09:53:51	ga_ls7e_ard_3-2-1_108074_2022-01-12_final
2022-01-15 10:27:40	ga_ls7e_ard_3-2-1_113082_2022-01-15_final
2022-01-16 09:27:58	ga_ls7e_ard_3-2-1_104072_2022-01-15_final
2022-01-17 10:15:55	ga_ls7e_ard_3-2-1_111084_2022-01-17_final
2022-01-18 09:17:48	ga_ls7e_ard_3-2-1_102078_2022-01-17_final
2022-01-19 08:20:30	ga_ls7e_ard_3-2-1_093074_2022-01-18_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-22 10:31:58	ga_ls7e_ard_3-2-1_114079_2022-01-22_final
2022-01-28 08:17:26	ga_ls7e_ard_3-2-1_092084_2022-01-27_final
2022-01-29 09:00:11	ga_ls7e_ard_3-2-1_099083_2022-01-28_final
2022-01-30 08:07:16	ga_ls7e_ard_3-2-1_090090_2022-01-29_final
2022-01-31 08:45:38	ga_ls7e_ard_3-2-1_097078_2022-01-30_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-01-31 10:25:42	ga_ls7e_ard_3-2-1_113081_2022-01-31_final
2022-02-06 08:11:08	ga_ls7e_ard_3-2-1_091086_2022-02-05_final
2022-02-11 10:02:03	ga_ls7e_ard_3-2-1_110071_2022-02-11_final
2022-02-11 10:06:50	ga_ls7e_ard_3-2-1_110083_2022-02-11_final
2022-02-13 09:50:41	ga_ls7e_ard_3-2-1_108074_2022-02-13_final
2022-02-16 08:42:23	ga_ls7e_ard_3-2-1_097074_2022-02-15_final
2022-02-17 09:27:09	ga_ls7e_ard_3-2-1_104078_2022-02-16_final
2022-02-21 09:00:28	ga_ls7e_ard_3-2-1_100074_2022-02-20_final
2022-02-22 09:42:26	ga_ls7e_ard_3-2-1_107071_2022-02-22_final
2022-03-01 09:52:43	ga_ls7e_ard_3-2-1_108083_2022-03-01_final
2022-03-04 08:39:16	ga_ls7e_ard_3-2-1_097070_2022-03-03_final
2022-03-04 10:22:08	ga_ls7e_ard_3-2-1_113080_2022-03-04_final
2022-03-06 08:32:18	ga_ls7e_ard_3-2-1_095084_2022-03-05_final
2022-03-08 08:17:21	ga_ls7e_ard_3-2-1_093078_2022-03-07_final
2022-03-08 09:58:13	ga_ls7e_ard_3-2-1_109083_2022-03-08_final
2022-03-09 09:02:30	ga_ls7e_ard_3-2-1_100083_2022-03-08_final
2022-03-10 09:42:28	ga_ls7e_ard_3-2-1_107075_2022-03-10_final
2022-03-11 08:47:33	ga_ls7e_ard_3-2-1_098077_2022-03-10_final
2022-03-12 07:52:37	ga_ls7e_ard_3-2-1_089079_2022-03-11_final
2022-03-19 09:34:35	ga_ls7e_ard_3-2-1_106073_2022-03-19_final
2022-03-20 08:38:04	ga_ls7e_ard_3-2-1_097071_2022-03-19_final
2022-03-21 09:22:02	ga_ls7e_ard_3-2-1_104073_2022-03-20_final
2022-03-24 09:56:39	ga_ls7e_ard_3-2-1_109083_2022-03-24_final
2022-03-25 08:58:08	ga_ls7e_ard_3-2-1_100076_2022-03-24_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-31 09:57:46	ga_ls7e_ard_3-2-1_110072_2022-03-31_final
2022-03-31 10:01:22	ga_ls7e_ard_3-2-1_110081_2022-03-31_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