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 08:23:59	ga_ls7e_ard_3-2-0_089078_2021-03-24_final
2021-09-20 10:16:08	ga_ls7e_ard_3-2-0_110072_2021-09-20_final
2021-10-10 09:50:02	ga_ls7e_ard_3-2-0_106073_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
2021-10-14 09:28:33	ga_ls7e_ard_3-2-0_102082_2021-10-13_final
2021-10-16 09:16:25	ga_ls7e_ard_3-2-0_100083_2021-10-15_final
2021-10-25 09:03:02	ga_ls7e_ard_3-2-0_099067_2021-10-24_final
2021-10-26 09:47:00	ga_ls7e_ard_3-2-0_106069_2021-10-26_final
2021-10-29 10:17:14	ga_ls7e_ard_3-2-0_111068_2021-10-29_final
2021-10-30 09:22:19	ga_ls7e_ard_3-2-0_102070_2021-10-29_final
2021-10-31 08:33:23	ga_ls7e_ard_3-2-0_093087_2021-10-30_final
2021-11-01 09:14:57	ga_ls7e_ard_3-2-0_100083_2021-10-31_final
2021-11-02 08:18:03	ga_ls7e_ard_3-2-0_091080_2021-11-01_final
2021-11-02 09:53:20	ga_ls7e_ard_3-2-0_107071_2021-11-02_final
2021-11-03 08:58:01	ga_ls7e_ard_3-2-0_098072_2021-11-02_final
2021-11-03 08:58:25	ga_ls7e_ard_3-2-0_098073_2021-11-02_final
2021-11-03 10:40:05	ga_ls7e_ard_3-2-0_114080_2021-11-03_final
2021-11-15 09:20:47	ga_ls7e_ard_3-2-1_102070_2021-11-14_final
2021-11-16 08:28:15	ga_ls7e_ard_3-2-1_093078_2021-11-15_final
2021-11-18 09:53:23	ga_ls7e_ard_3-2-1_107075_2021-11-18_final
2021-11-20 09:38:50	ga_ls7e_ard_3-2-1_105070_2021-11-20_final
2021-11-22 09:27:52	ga_ls7e_ard_3-2-1_103074_2021-11-21_final
2021-11-26 10:43:14	ga_ls7e_ard_3-2-1_115078_2021-11-26_final
2021-11-28 08:54:37	ga_ls7e_ard_3-2-1_097085_2021-11-27_final
2021-11-28 10:29:30	ga_ls7e_ard_3-2-1_113075_2021-11-28_final
2021-12-02 08:29:31	ga_ls7e_ard_3-2-1_093085_2021-12-01_final
2021-12-04 09:51:28	ga_ls7e_ard_3-2-1_107074_2021-12-04_final
2021-12-05 08:54:33	ga_ls7e_ard_3-2-1_098071_2021-12-04_final
2021-12-06 08:01:38	ga_ls7e_ard_3-2-1_089078_2021-12-05_final
2021-12-06 09:40:07	ga_ls7e_ard_3-2-1_105077_2021-12-06_final
2021-12-09 08:33:51	ga_ls7e_ard_3-2-1_094082_2021-12-08_final
2021-12-09 10:12:43	ga_ls7e_ard_3-2-1_110082_2021-12-09_final
2021-12-12 09:03:16	ga_ls7e_ard_3-2-1_099079_2021-12-11_final
2021-12-13 09:44:26	ga_ls7e_ard_3-2-1_106074_2021-12-13_final
2021-12-14 10:27:36	ga_ls7e_ard_3-2-1_113074_2021-12-14_final
2021-12-17 09:18:08	ga_ls7e_ard_3-2-1_102071_2021-12-16_final
2021-12-20 09:49:56	ga_ls7e_ard_3-2-1_107074_2021-12-20_final
2021-12-20 09:51:08	ga_ls7e_ard_3-2-1_107077_2021-12-20_final
2021-12-21 10:33:30	ga_ls7e_ard_3-2-1_114075_2021-12-21_final
2021-12-22 08:02:06	ga_ls7e_ard_3-2-1_089083_2021-12-21_final
2021-12-22 09:35:47	ga_ls7e_ard_3-2-1_105070_2021-12-22_final
2021-12-23 10:24:32	ga_ls7e_ard_3-2-1_112084_2021-12-23_final
2021-12-25 10:07:11	ga_ls7e_ard_3-2-1_110072_2021-12-25_final
2021-12-25 10:07:35	ga_ls7e_ard_3-2-1_110073_2021-12-25_final
2021-12-28 10:39:46	ga_ls7e_ard_3-2-1_115077_2021-12-28_final
2021-12-29 08:07:58	ga_ls7e_ard_3-2-1_090084_2021-12-28_final
2021-12-29 09:42:04	ga_ls7e_ard_3-2-1_106072_2021-12-29_final
2021-12-30 10:26:25	ga_ls7e_ard_3-2-1_113075_2021-12-30_final
2022-01-01 08:38:10	ga_ls7e_ard_3-2-1_095083_2021-12-31_final
2022-01-01 08:39:22	ga_ls7e_ard_3-2-1_095086_2021-12-31_final
2022-01-05 08:15:50	ga_ls7e_ard_3-2-1_091090_2022-01-04_final
2022-01-06 08:55:00	ga_ls7e_ard_3-2-1_098080_2022-01-05_final
2022-01-08 08:44:03	ga_ls7e_ard_3-2-1_096084_2022-01-07_final
2022-01-08 10:22:56	ga_ls7e_ard_3-2-1_112084_2022-01-08_final
2022-01-09 09:21:14	ga_ls7e_ard_3-2-1_103069_2022-01-08_final
2022-01-10 10:05:12	ga_ls7e_ard_3-2-1_110071_2022-01-10_final
2022-01-12 09:57:51	ga_ls7e_ard_3-2-1_108084_2022-01-12_final
2022-01-15 08:49:35	ga_ls7e_ard_3-2-1_097084_2022-01-14_final
2022-01-17 10:15:31	ga_ls7e_ard_3-2-1_111083_2022-01-17_final
2022-01-19 09:58:58	ga_ls7e_ard_3-2-1_109073_2022-01-19_final
2022-01-21 08:12:20	ga_ls7e_ard_3-2-1_091085_2022-01-20_final
2022-01-22 08:51:06	ga_ls7e_ard_3-2-1_098074_2022-01-21_final
2022-01-22 10:32:22	ga_ls7e_ard_3-2-1_114080_2022-01-22_final
2022-01-23 07:56:35	ga_ls7e_ard_3-2-1_089077_2022-01-22_final
2022-01-26 10:05:40	ga_ls7e_ard_3-2-1_110076_2022-01-26_final
2022-01-28 08:14:14	ga_ls7e_ard_3-2-1_092076_2022-01-27_final
2022-01-28 08:17:50	ga_ls7e_ard_3-2-1_092085_2022-01-27_final
2022-01-29 08:58:59	ga_ls7e_ard_3-2-1_099080_2022-01-28_final
2022-01-29 08:59:47	ga_ls7e_ard_3-2-1_099082_2022-01-28_final
2022-02-02 08:32:17	ga_ls7e_ard_3-2-1_095076_2022-02-01_final
2022-02-02 08:35:04	ga_ls7e_ard_3-2-1_095083_2022-02-01_final
2022-02-03 09:15:02	ga_ls7e_ard_3-2-1_102075_2022-02-02_final
2022-02-06 09:45:38	ga_ls7e_ard_3-2-1_107075_2022-02-06_final
2022-02-07 10:29:11	ga_ls7e_ard_3-2-1_114076_2022-02-07_final
2022-02-08 07:57:47	ga_ls7e_ard_3-2-1_089084_2022-02-07_final
2022-02-14 08:54:09	ga_ls7e_ard_3-2-1_099072_2022-02-13_final
2022-02-15 09:38:06	ga_ls7e_ard_3-2-1_106074_2022-02-15_final
2022-02-16 10:22:52	ga_ls7e_ard_3-2-1_113078_2022-02-16_final
2022-02-21 09:00:28	ga_ls7e_ard_3-2-1_100074_2022-02-20_final
2022-02-23 08:51:30	ga_ls7e_ard_3-2-1_098083_2022-02-22_final
2022-02-25 10:14:14	ga_ls7e_ard_3-2-1_112074_2022-02-25_final
2022-02-26 09:16:32	ga_ls7e_ard_3-2-1_103069_2022-02-25_final
2022-02-28 09:09:10	ga_ls7e_ard_3-2-1_101082_2022-02-27_final
2022-03-09 09:02:06	ga_ls7e_ard_3-2-1_100082_2022-03-08_final
2022-03-10 09:41:16	ga_ls7e_ard_3-2-1_107072_2022-03-10_final
2022-03-13 08:37:46	ga_ls7e_ard_3-2-1_096084_2022-03-12_final
2022-03-17 08:12:39	ga_ls7e_ard_3-2-1_092084_2022-03-16_final
2022-03-18 08:51:01	ga_ls7e_ard_3-2-1_099072_2022-03-17_final
2022-03-19 09:33:23	ga_ls7e_ard_3-2-1_106070_2022-03-19_final
2022-03-19 09:33:47	ga_ls7e_ard_3-2-1_106071_2022-03-19_final
2022-03-20 08:38:04	ga_ls7e_ard_3-2-1_097071_2022-03-19_final
2022-03-24 09:56:39	ga_ls7e_ard_3-2-1_109083_2022-03-24_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-27 10:26:04	ga_ls7e_ard_3-2-1_114080_2022-03-27_final
2022-03-27 10:26:28	ga_ls7e_ard_3-2-1_114081_2022-03-27_final
2022-03-28 09:27:57	ga_ls7e_ard_3-2-1_105074_2022-03-27_final
2022-04-03 08:54:17	ga_ls7e_ard_3-2-1_099084_2022-04-02_final
2022-04-04 07:56:34	ga_ls7e_ard_3-2-1_090079_2022-04-03_final
2022-04-04 09:31:27	ga_ls7e_ard_3-2-1_106069_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