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
2021-07-21 09:11:31	ga_ls7e_ard_3-2-0_099067_2021-07-20_final
2021-07-24 09:42:33	ga_ls7e_ard_3-2-0_104068_2021-07-24_final
2021-07-31 08:13:14	ga_ls7e_ard_3-2-0_089078_2021-07-30_final
2021-07-31 08:14:02	ga_ls7e_ard_3-2-0_089080_2021-07-30_final
2021-07-31 08:14:50	ga_ls7e_ard_3-2-0_089082_2021-07-30_final
2021-08-05 08:30:08	ga_ls7e_ard_3-2-0_092075_2021-08-04_final
2021-08-05 10:08:13	ga_ls7e_ard_3-2-0_108073_2021-08-05_final
2021-08-06 09:12:06	ga_ls7e_ard_3-2-0_099072_2021-08-05_final
2021-08-08 10:41:14	ga_ls7e_ard_3-2-0_113079_2021-08-08_final
2021-08-14 08:27:08	ga_ls7e_ard_3-2-0_091085_2021-08-13_final
2021-08-28 08:37:53	ga_ls7e_ard_3-2-0_093084_2021-08-27_final
2021-08-29 09:16:16	ga_ls7e_ard_3-2-0_100072_2021-08-28_final
2021-08-31 10:43:25	ga_ls7e_ard_3-2-0_114074_2021-08-31_final
2021-09-01 08:13:37	ga_ls7e_ard_3-2-0_089086_2021-08-31_final
2021-09-02 08:56:00	ga_ls7e_ard_3-2-0_096084_2021-09-01_final
2021-09-05 09:23:50	ga_ls7e_ard_3-2-0_101077_2021-09-04_final
2021-09-06 10:04:37	ga_ls7e_ard_3-2-0_108071_2021-09-06_final
2021-09-06 10:05:25	ga_ls7e_ard_3-2-0_108073_2021-09-06_final
2021-09-12 09:26:13	ga_ls7e_ard_3-2-0_102069_2021-09-11_final
2021-09-14 09:19:16	ga_ls7e_ard_3-2-0_100083_2021-09-13_final
2021-09-15 09:58:50	ga_ls7e_ard_3-2-0_107074_2021-09-15_final
2021-09-22 08:25:55	ga_ls7e_ard_3-2-0_092075_2021-09-21_final
2021-09-22 08:29:54	ga_ls7e_ard_3-2-0_092085_2021-09-21_final
2021-10-01 09:57:48	ga_ls7e_ard_3-2-0_107075_2021-10-01_final
2021-10-01 09:59:48	ga_ls7e_ard_3-2-0_107080_2021-10-01_final
2021-10-02 09:03:42	ga_ls7e_ard_3-2-0_098079_2021-10-01_final
2021-10-03 09:44:04	ga_ls7e_ard_3-2-0_105072_2021-10-03_final
2021-10-08 10:01:47	ga_ls7e_ard_3-2-0_108071_2021-10-08_final
2021-10-15 10:12:31	ga_ls7e_ard_3-2-0_109084_2021-10-15_final
2021-10-17 09:56:00	ga_ls7e_ard_3-2-0_107074_2021-10-17_final
2021-10-18 09:03:53	ga_ls7e_ard_3-2-0_098083_2021-10-17_final
2021-10-18 10:41:33	ga_ls7e_ard_3-2-0_114080_2021-10-18_final
2021-10-26 09:48:36	ga_ls7e_ard_3-2-0_106073_2021-10-26_final
2021-10-26 09:49:00	ga_ls7e_ard_3-2-0_106074_2021-10-26_final
2021-10-31 08:32:35	ga_ls7e_ard_3-2-0_093085_2021-10-30_final
2021-10-31 08:32:59	ga_ls7e_ard_3-2-0_093086_2021-10-30_final
2021-10-31 10:11:04	ga_ls7e_ard_3-2-0_109084_2021-10-31_final
2021-11-10 09:05:07	ga_ls7e_ard_3-2-0_099076_2021-11-09_final
2021-11-13 09:35:44	ga_ls7e_ard_3-2-1_104076_2021-11-13_final
2021-11-15 09:19:59	ga_ls7e_ard_3-2-1_102068_2021-11-14_final
2021-11-18 08:17:42	ga_ls7e_ard_3-2-1_091083_2021-11-17_final
2021-11-19 08:58:28	ga_ls7e_ard_3-2-1_098077_2021-11-18_final
2021-11-21 10:23:59	ga_ls7e_ard_3-2-1_112075_2021-11-21_final
2021-11-23 10:09:50	ga_ls7e_ard_3-2-1_110071_2021-11-23_final
2021-11-25 10:01:40	ga_ls7e_ard_3-2-1_108082_2021-11-25_final
2021-11-28 08:51:49	ga_ls7e_ard_3-2-1_097078_2021-11-27_final
2021-11-30 08:41:40	ga_ls7e_ard_3-2-1_095084_2021-11-29_final
2021-11-30 10:16:57	ga_ls7e_ard_3-2-1_111075_2021-11-30_final
2021-12-03 09:10:42	ga_ls7e_ard_3-2-1_100080_2021-12-02_final
2021-12-04 08:18:34	ga_ls7e_ard_3-2-1_091089_2021-12-03_final
2021-12-05 10:37:25	ga_ls7e_ard_3-2-1_114081_2021-12-05_final
2021-12-06 09:41:19	ga_ls7e_ard_3-2-1_105080_2021-12-06_final
2021-12-07 10:22:29	ga_ls7e_ard_3-2-1_112075_2021-12-07_final
2021-12-13 08:09:09	ga_ls7e_ard_3-2-1_090083_2021-12-12_final
2021-12-14 08:52:42	ga_ls7e_ard_3-2-1_097084_2021-12-13_final
2021-12-16 10:15:26	ga_ls7e_ard_3-2-1_111075_2021-12-16_final
2021-12-20 09:50:20	ga_ls7e_ard_3-2-1_107075_2021-12-20_final
2021-12-27 09:58:13	ga_ls7e_ard_3-2-1_108081_2021-12-27_final
2021-12-27 09:58:37	ga_ls7e_ard_3-2-1_108082_2021-12-27_final
2021-12-27 09:59:25	ga_ls7e_ard_3-2-1_108084_2021-12-27_final
2022-01-01 10:12:15	ga_ls7e_ard_3-2-1_111071_2022-01-01_final
2022-01-08 08:38:28	ga_ls7e_ard_3-2-1_096070_2022-01-07_final
2022-01-09 09:25:38	ga_ls7e_ard_3-2-1_103080_2022-01-08_final
2022-01-21 08:13:08	ga_ls7e_ard_3-2-1_091087_2022-01-20_final
2022-01-22 10:30:23	ga_ls7e_ard_3-2-1_114075_2022-01-22_final
2022-01-23 09:32:40	ga_ls7e_ard_3-2-1_105070_2022-01-23_final
2022-01-28 08:17:26	ga_ls7e_ard_3-2-1_092084_2022-01-27_final
2022-01-29 08:59:47	ga_ls7e_ard_3-2-1_099082_2022-01-28_final
2022-01-30 08:06:52	ga_ls7e_ard_3-2-1_090089_2022-01-29_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-02-02 08:34:40	ga_ls7e_ard_3-2-1_095082_2022-02-01_final
2022-02-02 08:36:16	ga_ls7e_ard_3-2-1_095086_2022-02-01_final
2022-02-04 08:24:06	ga_ls7e_ard_3-2-1_093087_2022-02-03_final
2022-02-06 08:07:09	ga_ls7e_ard_3-2-1_091076_2022-02-05_final
2022-02-06 08:09:57	ga_ls7e_ard_3-2-1_091083_2022-02-05_final
2022-02-06 09:44:50	ga_ls7e_ard_3-2-1_107073_2022-02-06_final
2022-02-06 09:45:14	ga_ls7e_ard_3-2-1_107074_2022-02-06_final
2022-02-07 08:48:43	ga_ls7e_ard_3-2-1_098072_2022-02-06_final
2022-02-09 08:36:09	ga_ls7e_ard_3-2-1_096072_2022-02-08_final
2022-02-13 09:50:17	ga_ls7e_ard_3-2-1_108073_2022-02-13_final
2022-02-16 10:22:52	ga_ls7e_ard_3-2-1_113078_2022-02-16_final
2022-02-16 10:24:51	ga_ls7e_ard_3-2-1_113083_2022-02-16_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-21 09:00:28	ga_ls7e_ard_3-2-1_100074_2022-02-20_final
2022-02-22 08:08:44	ga_ls7e_ard_3-2-1_091084_2022-02-21_final
2022-02-22 08:11:08	ga_ls7e_ard_3-2-1_091090_2022-02-21_final
2022-02-23 08:52:18	ga_ls7e_ard_3-2-1_098085_2022-02-22_final
2022-03-02 08:57:24	ga_ls7e_ard_3-2-1_099084_2022-03-01_final
2022-03-10 08:04:23	ga_ls7e_ard_3-2-1_091077_2022-03-09_final
2022-03-11 10:25:37	ga_ls7e_ard_3-2-1_114075_2022-03-11_final
2022-03-12 07:53:49	ga_ls7e_ard_3-2-1_089082_2022-03-11_final
2022-03-13 08:37:46	ga_ls7e_ard_3-2-1_096084_2022-03-12_final
2022-03-13 08:38:34	ga_ls7e_ard_3-2-1_096086_2022-03-12_final
2022-03-15 10:00:54	ga_ls7e_ard_3-2-1_110076_2022-03-15_final
2022-03-15 10:04:05	ga_ls7e_ard_3-2-1_110084_2022-03-15_final
2022-03-24 09:52:39	ga_ls7e_ard_3-2-1_109073_2022-03-24_final
2022-03-25 08:56:32	ga_ls7e_ard_3-2-1_100072_2022-03-24_final
2022-03-25 09:00:56	ga_ls7e_ard_3-2-1_100083_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

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