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
2020-08-11 08:56:16	ga_ls7e_ard_3-1-0_091088_2020-08-10_final
2020-08-13 10:15:05	ga_ls7e_ard_3-1-0_105069_2020-08-13_final
2020-08-20 10:22:48	ga_ls7e_ard_3-1-0_106074_2020-08-20_final
2020-08-25 09:06:08	ga_ls7e_ard_3-1-0_093084_2020-08-24_final
2020-08-31 10:03:09	ga_ls7e_ard_3-1-0_103073_2020-08-31_final
2020-09-01 10:47:33	ga_ls7e_ard_3-1-0_110076_2020-09-01_final
2020-09-03 08:59:22	ga_ls7e_ard_3-1-0_092084_2020-09-02_final
2020-10-03 09:10:10	ga_ls7e_ard_3-1-0_094085_2020-10-02_final
2020-10-04 09:47:47	ga_ls7e_ard_3-1-0_101071_2020-10-04_final
2020-10-16 10:11:20	ga_ls7e_ard_3-1-0_105070_2020-10-16_final
2020-10-18 10:02:50	ga_ls7e_ard_3-1-0_103080_2020-10-18_final
2020-10-19 10:46:49	ga_ls7e_ard_3-1-0_110082_2020-10-19_final
2020-10-19 10:47:37	ga_ls7e_ard_3-1-0_110084_2020-10-19_final
2020-10-21 08:53:51	ga_ls7e_ard_3-1-0_092078_2020-10-20_final
2020-10-24 09:21:46	ga_ls7e_ard_3-1-0_097071_2020-10-23_final
2020-10-24 10:59:03	ga_ls7e_ard_3-1-0_113067_2020-10-24_final
2020-10-30 08:47:52	ga_ls7e_ard_3-1-0_091080_2020-10-29_final
2020-10-31 09:26:41	ga_ls7e_ard_3-1-0_098069_2020-10-30_final
2020-11-01 10:09:52	ga_ls7e_ard_3-1-0_105069_2020-11-01_final
2020-11-08 10:19:58	ga_ls7e_ard_3-1-0_106080_2020-11-08_final
2020-11-13 09:00:53	ga_ls7e_ard_3-1-0_093084_2020-11-12_final
2020-11-14 09:43:40	ga_ls7e_ard_3-1-0_100083_2020-11-14_final
2020-11-16 11:07:15	ga_ls7e_ard_3-1-0_114076_2020-11-16_final
2020-11-18 09:15:04	ga_ls7e_ard_3-1-0_096074_2020-11-17_final
2020-11-21 09:46:58	ga_ls7e_ard_3-1-0_101077_2020-11-21_final
2020-11-25 09:25:09	ga_ls7e_ard_3-1-0_097085_2020-11-24_final
2020-11-29 10:33:02	ga_ls7e_ard_3-1-0_109070_2020-11-29_final
2020-11-29 10:37:49	ga_ls7e_ard_3-1-0_109082_2020-11-29_final
2020-12-02 11:08:06	ga_ls7e_ard_3-1-0_114081_2020-12-02_final
2020-12-05 09:58:18	ga_ls7e_ard_3-1-0_103077_2020-12-05_final
2020-12-11 09:22:46	ga_ls7e_ard_3-1-0_097082_2020-12-10_final
2020-12-11 10:55:40	ga_ls7e_ard_3-1-0_113067_2020-12-11_final
2021-07-15 09:55:06	ga_ls7e_ard_3-2-0_105082_2021-07-15_final
2021-08-03 10:18:21	ga_ls7e_ard_3-2-0_110067_2021-08-03_final
2021-08-07 09:55:16	ga_ls7e_ard_3-2-0_106072_2021-08-07_final
2021-08-14 08:25:56	ga_ls7e_ard_3-2-0_091082_2021-08-13_final
2021-08-14 10:01:38	ga_ls7e_ard_3-2-0_107074_2021-08-14_final
2021-08-19 08:44:26	ga_ls7e_ard_3-2-0_094083_2021-08-18_final
2021-08-19 08:45:14	ga_ls7e_ard_3-2-0_094085_2021-08-18_final
2021-08-25 09:41:20	ga_ls7e_ard_3-2-0_104072_2021-08-25_final
2021-08-28 08:38:17	ga_ls7e_ard_3-2-0_093085_2021-08-27_final
2021-08-28 08:39:29	ga_ls7e_ard_3-2-0_093088_2021-08-27_final
2021-08-29 09:20:40	ga_ls7e_ard_3-2-0_100083_2021-08-28_final
2021-08-30 10:00:14	ga_ls7e_ard_3-2-0_107074_2021-08-30_final
2021-09-01 09:50:30	ga_ls7e_ard_3-2-0_105081_2021-09-01_final
2021-09-04 10:19:09	ga_ls7e_ard_3-2-0_110076_2021-09-04_final
2021-09-07 09:14:06	ga_ls7e_ard_3-2-0_099084_2021-09-06_final
2021-09-08 08:18:47	ga_ls7e_ard_3-2-0_090085_2021-09-07_final
2021-09-16 10:43:12	ga_ls7e_ard_3-2-0_114077_2021-09-16_final
2021-09-20 08:43:14	ga_ls7e_ard_3-2-0_094087_2021-09-19_final
2021-09-24 08:18:58	ga_ls7e_ard_3-2-0_090089_2021-09-23_final
2021-10-01 09:57:24	ga_ls7e_ard_3-2-0_107074_2021-10-01_final
2021-10-05 09:31:56	ga_ls7e_ard_3-2-0_103073_2021-10-05_final
2021-10-11 10:36:00	ga_ls7e_ard_3-2-0_113080_2021-10-11_final
2021-10-16 09:13:37	ga_ls7e_ard_3-2-0_100076_2021-10-15_final
2021-10-17 09:56:00	ga_ls7e_ard_3-2-0_107074_2021-10-17_final
2021-10-27 08:57:17	ga_ls7e_ard_3-2-0_097084_2021-10-26_final
2021-10-28 09:36:03	ga_ls7e_ard_3-2-0_104073_2021-10-28_final
2021-10-29 10:20:01	ga_ls7e_ard_3-2-0_111075_2021-10-29_final
2021-11-02 08:20:26	ga_ls7e_ard_3-2-0_091086_2021-11-01_final
2021-11-03 09:01:36	ga_ls7e_ard_3-2-0_098081_2021-11-02_final
2021-11-06 09:29:02	ga_ls7e_ard_3-2-0_103073_2021-11-05_final
2021-11-07 08:38:06	ga_ls7e_ard_3-2-0_094085_2021-11-06_final
2021-11-07 10:15:47	ga_ls7e_ard_3-2-0_110082_2021-11-07_final
2021-11-16 10:08:20	ga_ls7e_ard_3-2-1_109081_2021-11-16_final
2021-11-19 08:55:40	ga_ls7e_ard_3-2-1_098070_2021-11-18_final
2021-11-19 10:36:08	ga_ls7e_ard_3-2-1_114074_2021-11-19_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-11-28 10:32:18	ga_ls7e_ard_3-2-1_113082_2021-11-28_final
2021-12-02 08:29:31	ga_ls7e_ard_3-2-1_093085_2021-12-01_final
2021-12-04 09:54:39	ga_ls7e_ard_3-2-1_107082_2021-12-04_final
2021-12-09 08:33:51	ga_ls7e_ard_3-2-1_094082_2021-12-08_final
2021-12-12 10:41:20	ga_ls7e_ard_3-2-1_115077_2021-12-12_final
2021-12-13 08:09:33	ga_ls7e_ard_3-2-1_090084_2021-12-12_final
2021-12-14 08:52:42	ga_ls7e_ard_3-2-1_097084_2021-12-13_final
2021-12-23 10:21:44	ga_ls7e_ard_3-2-1_112077_2021-12-23_final
2022-01-03 10:03:17	ga_ls7e_ard_3-2-1_109080_2022-01-03_final
2022-01-08 08:40:04	ga_ls7e_ard_3-2-1_096074_2022-01-07_final
2022-01-12 09:53:27	ga_ls7e_ard_3-2-1_108073_2022-01-12_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-26 08:31:11	ga_ls7e_ard_3-2-1_094087_2022-01-25_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-28 08:15:50	ga_ls7e_ard_3-2-1_092080_2022-01-27_final
2022-01-29 08:59:23	ga_ls7e_ard_3-2-1_099081_2022-01-28_final
2022-02-01 09:25:36	ga_ls7e_ard_3-2-1_104070_2022-01-31_final
2022-02-04 08:22:54	ga_ls7e_ard_3-2-1_093084_2022-02-03_final
2022-02-07 08:52:42	ga_ls7e_ard_3-2-1_098082_2022-02-06_final
2022-02-12 09:06:44	ga_ls7e_ard_3-2-1_101072_2022-02-11_final
2022-02-16 08:42:23	ga_ls7e_ard_3-2-1_097074_2022-02-15_final
2022-03-03 09:35:47	ga_ls7e_ard_3-2-1_106072_2022-03-03_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-20 08:43:39	ga_ls7e_ard_3-2-1_097085_2022-03-19_final
2022-03-22 08:30:43	ga_ls7e_ard_3-2-1_095084_2022-03-21_final
2022-03-29 08:36:14	ga_ls7e_ard_3-2-1_096084_2022-03-28_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years