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 08:50:59	ga_ls7e_ard_3-2-0_096075_2021-09-17_final
2021-09-18 08:53:23	ga_ls7e_ard_3-2-0_096081_2021-09-17_final
2021-09-20 08:40:03	ga_ls7e_ard_3-2-0_094079_2021-09-19_final
2021-09-20 08:40:51	ga_ls7e_ard_3-2-0_094081_2021-09-19_final
2021-09-20 10:18:56	ga_ls7e_ard_3-2-0_110079_2021-09-20_final
2021-10-26 08:12:31	ga_ls7e_ard_3-2-0_090080_2021-10-25_final
2021-10-29 08:42:20	ga_ls7e_ard_3-2-0_095078_2021-10-28_final
2021-11-02 08:17:39	ga_ls7e_ard_3-2-0_091079_2021-11-01_final
2021-11-05 08:46:40	ga_ls7e_ard_3-2-0_096075_2021-11-04_final
2021-11-05 10:27:32	ga_ls7e_ard_3-2-0_112080_2021-11-05_final
2021-11-13 09:34:56	ga_ls7e_ard_3-2-1_104074_2021-11-13_final
2021-11-14 08:40:49	ga_ls7e_ard_3-2-1_095078_2021-11-13_final
2021-11-14 08:41:37	ga_ls7e_ard_3-2-1_095080_2021-11-13_final
2021-11-15 09:25:34	ga_ls7e_ard_3-2-1_102082_2021-11-14_final
2021-11-23 08:32:33	ga_ls7e_ard_3-2-1_094075_2021-11-22_final
2021-11-28 10:31:06	ga_ls7e_ard_3-2-1_113079_2021-11-28_final
2021-11-29 09:36:11	ga_ls7e_ard_3-2-1_104081_2021-11-29_final
2021-11-30 08:40:04	ga_ls7e_ard_3-2-1_095080_2021-11-29_final
2021-11-30 10:18:33	ga_ls7e_ard_3-2-1_111079_2021-11-30_final
2021-12-07 08:42:00	ga_ls7e_ard_3-2-1_096071_2021-12-06_final
2021-12-11 09:58:35	ga_ls7e_ard_3-2-1_108078_2021-12-11_final
2021-12-12 09:01:16	ga_ls7e_ard_3-2-1_099074_2021-12-11_final
2021-12-17 09:20:31	ga_ls7e_ard_3-2-1_102077_2021-12-16_final
2021-12-19 09:09:34	ga_ls7e_ard_3-2-1_100081_2021-12-18_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-02 09:18:32	ga_ls7e_ard_3-2-1_102076_2022-01-01_final
2022-01-03 08:24:00	ga_ls7e_ard_3-2-1_093079_2022-01-02_final
2022-01-03 09:59:17	ga_ls7e_ard_3-2-1_109070_2022-01-03_final
2022-01-03 10:02:53	ga_ls7e_ard_3-2-1_109079_2022-01-03_final
2022-01-05 09:48:43	ga_ls7e_ard_3-2-1_107075_2022-01-05_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-07 09:34:35	ga_ls7e_ard_3-2-1_105071_2022-01-07_final
2022-01-08 08:41:40	ga_ls7e_ard_3-2-1_096078_2022-01-07_final
2022-01-08 10:19:21	ga_ls7e_ard_3-2-1_112075_2022-01-08_final
2022-01-08 10:20:32	ga_ls7e_ard_3-2-1_112078_2022-01-08_final
2022-01-09 09:23:14	ga_ls7e_ard_3-2-1_103074_2022-01-08_final
2022-01-10 08:29:31	ga_ls7e_ard_3-2-1_094079_2022-01-09_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-13 10:38:13	ga_ls7e_ard_3-2-1_115077_2022-01-13_final
2022-01-14 08:06:25	ga_ls7e_ard_3-2-1_090084_2022-01-13_final
2022-01-14 09:43:18	ga_ls7e_ard_3-2-1_106079_2022-01-14_final
2022-01-17 08:33:51	ga_ls7e_ard_3-2-1_095076_2022-01-16_final
2022-01-17 08:35:50	ga_ls7e_ard_3-2-1_095081_2022-01-16_final
2022-01-17 10:14:19	ga_ls7e_ard_3-2-1_111080_2022-01-17_final
2022-01-20 09:04:03	ga_ls7e_ard_3-2-1_100075_2022-01-19_final
2022-01-24 10:19:49	ga_ls7e_ard_3-2-1_112080_2022-01-24_final
2022-01-27 09:09:57	ga_ls7e_ard_3-2-1_101076_2022-01-26_final
2022-01-28 09:53:31	ga_ls7e_ard_3-2-1_108077_2022-01-28_final
2022-01-31 08:47:14	ga_ls7e_ard_3-2-1_097082_2022-01-30_final
2022-02-03 09:16:14	ga_ls7e_ard_3-2-1_102078_2022-02-02_final
2022-02-04 08:20:07	ga_ls7e_ard_3-2-1_093077_2022-02-03_final
2022-02-04 10:00:35	ga_ls7e_ard_3-2-1_109081_2022-02-04_final
2022-02-07 10:29:35	ga_ls7e_ard_3-2-1_114077_2022-02-07_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-11 08:26:46	ga_ls7e_ard_3-2-1_094080_2022-02-10_final
2022-02-14 08:55:45	ga_ls7e_ard_3-2-1_099076_2022-02-13_final
2022-02-15 08:02:01	ga_ls7e_ard_3-2-1_090081_2022-02-14_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-16 10:22:28	ga_ls7e_ard_3-2-1_113077_2022-02-16_final
2022-02-17 09:25:57	ga_ls7e_ard_3-2-1_104075_2022-02-16_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-18 10:10:19	ga_ls7e_ard_3-2-1_111078_2022-02-18_final
2022-02-18 10:10:43	ga_ls7e_ard_3-2-1_111079_2022-02-18_final
2022-02-18 10:11:31	ga_ls7e_ard_3-2-1_111081_2022-02-18_final
2022-02-23 08:51:06	ga_ls7e_ard_3-2-1_098082_2022-02-22_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-25 08:37:21	ga_ls7e_ard_3-2-1_096079_2022-02-24_final
2022-02-25 08:38:09	ga_ls7e_ard_3-2-1_096081_2022-02-24_final
2022-02-25 10:15:50	ga_ls7e_ard_3-2-1_112078_2022-02-25_final
2022-02-27 08:24:48	ga_ls7e_ard_3-2-1_094079_2022-02-26_final
2022-03-04 08:38:52	ga_ls7e_ard_3-2-1_097069_2022-03-03_final
2022-03-04 08:43:39	ga_ls7e_ard_3-2-1_097081_2022-03-03_final
2022-03-06 08:31:30	ga_ls7e_ard_3-2-1_095082_2022-03-05_final
2022-03-08 08:17:45	ga_ls7e_ard_3-2-1_093079_2022-03-07_final
2022-03-10 08:05:11	ga_ls7e_ard_3-2-1_091079_2022-03-09_final
2022-03-10 09:43:40	ga_ls7e_ard_3-2-1_107078_2022-03-10_final
2022-03-11 08:44:21	ga_ls7e_ard_3-2-1_098069_2022-03-10_final
2022-03-13 08:34:59	ga_ls7e_ard_3-2-1_096077_2022-03-12_final
2022-03-13 08:35:23	ga_ls7e_ard_3-2-1_096078_2022-03-12_final
2022-03-13 10:15:03	ga_ls7e_ard_3-2-1_112080_2022-03-13_final
2022-03-15 08:23:13	ga_ls7e_ard_3-2-1_094079_2022-03-14_final
2022-03-15 10:02:29	ga_ls7e_ard_3-2-1_110080_2022-03-15_final
2022-03-17 08:11:27	ga_ls7e_ard_3-2-1_092081_2022-03-16_final
2022-03-19 09:36:58	ga_ls7e_ard_3-2-1_106079_2022-03-19_final
2022-03-19 09:38:10	ga_ls7e_ard_3-2-1_106082_2022-03-19_final
2022-03-20 08:39:40	ga_ls7e_ard_3-2-1_097075_2022-03-19_final
2022-03-20 10:19:20	ga_ls7e_ard_3-2-1_113077_2022-03-20_final
2022-03-20 10:20:08	ga_ls7e_ard_3-2-1_113079_2022-03-20_final
2022-03-21 09:22:50	ga_ls7e_ard_3-2-1_104075_2022-03-20_final
2022-03-22 08:28:43	ga_ls7e_ard_3-2-1_095079_2022-03-21_final
2022-03-22 10:06:24	ga_ls7e_ard_3-2-1_111076_2022-03-22_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-25 08:57:44	ga_ls7e_ard_3-2-1_100075_2022-03-24_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-29 10:12:19	ga_ls7e_ard_3-2-1_112077_2022-03-29_final
2022-04-01 09:03:15	ga_ls7e_ard_3-2-1_101075_2022-03-31_final
2022-04-02 08:10:44	ga_ls7e_ard_3-2-1_092083_2022-04-01_final
2022-04-03 08:51:05	ga_ls7e_ard_3-2-1_099076_2022-04-02_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