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
2021-07-24 09:43:21	ga_ls7e_ard_3-2-0_104070_2021-07-24_final
2021-07-24 09:46:32	ga_ls7e_ard_3-2-0_104078_2021-07-24_final
2021-07-27 10:19:34	ga_ls7e_ard_3-2-0_109084_2021-07-27_final
2021-08-01 08:58:00	ga_ls7e_ard_3-2-0_096082_2021-07-31_final
2021-08-04 09:25:02	ga_ls7e_ard_3-2-0_101073_2021-08-03_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
2021-08-07 09:55:40	ga_ls7e_ard_3-2-0_106073_2021-08-07_final
2021-08-26 08:50:25	ga_ls7e_ard_3-2-0_095084_2021-08-25_final
2021-08-26 10:25:42	ga_ls7e_ard_3-2-0_111075_2021-08-26_final
2021-08-30 10:01:02	ga_ls7e_ard_3-2-0_107076_2021-08-30_final
2021-09-01 09:48:06	ga_ls7e_ard_3-2-0_105075_2021-09-01_final
2021-09-02 08:56:00	ga_ls7e_ard_3-2-0_096084_2021-09-01_final
2021-09-06 10:04:13	ga_ls7e_ard_3-2-0_108070_2021-09-06_final
2021-09-06 10:08:12	ga_ls7e_ard_3-2-0_108080_2021-09-06_final
2021-09-06 10:09:24	ga_ls7e_ard_3-2-0_108083_2021-09-06_final
2021-09-08 09:52:53	ga_ls7e_ard_3-2-0_106073_2021-09-08_final
2021-09-10 09:38:45	ga_ls7e_ard_3-2-0_104069_2021-09-10_final
2021-09-11 10:21:31	ga_ls7e_ard_3-2-0_111068_2021-09-11_final
2021-09-12 09:25:49	ga_ls7e_ard_3-2-0_102068_2021-09-11_final
2021-09-12 09:26:13	ga_ls7e_ard_3-2-0_102069_2021-09-11_final
2021-09-13 10:11:23	ga_ls7e_ard_3-2-0_109074_2021-09-13_final
2021-09-15 08:24:21	ga_ls7e_ard_3-2-0_091085_2021-09-14_final
2021-09-16 09:00:20	ga_ls7e_ard_3-2-0_098067_2021-09-15_final
2021-09-16 09:06:43	ga_ls7e_ard_3-2-0_098083_2021-09-15_final
2021-09-19 09:33:46	ga_ls7e_ard_3-2-0_103074_2021-09-19_final
2021-09-27 08:48:23	ga_ls7e_ard_3-2-0_095086_2021-09-26_final
2021-09-30 09:17:25	ga_ls7e_ard_3-2-0_100082_2021-09-29_final
2021-10-01 08:21:43	ga_ls7e_ard_3-2-0_091082_2021-09-30_final
2021-10-01 09:58:36	ga_ls7e_ard_3-2-0_107077_2021-10-01_final
2021-10-02 09:02:30	ga_ls7e_ard_3-2-0_098076_2021-10-01_final
2021-10-03 08:07:59	ga_ls7e_ard_3-2-0_089079_2021-10-02_final
2021-10-07 09:23:00	ga_ls7e_ard_3-2-0_101082_2021-10-06_final
2021-10-09 09:08:52	ga_ls7e_ard_3-2-0_099078_2021-10-08_final
2021-10-10 09:52:02	ga_ls7e_ard_3-2-0_106078_2021-10-10_final
2021-10-11 10:35:36	ga_ls7e_ard_3-2-0_113079_2021-10-11_final
2021-10-14 09:24:58	ga_ls7e_ard_3-2-0_102073_2021-10-13_final
2021-10-15 08:30:27	ga_ls7e_ard_3-2-0_093076_2021-10-14_final
2021-10-15 10:08:56	ga_ls7e_ard_3-2-0_109075_2021-10-15_final
2021-10-15 10:12:07	ga_ls7e_ard_3-2-0_109083_2021-10-15_final
2021-10-18 09:02:41	ga_ls7e_ard_3-2-0_098080_2021-10-17_final
2021-10-24 10:00:44	ga_ls7e_ard_3-2-0_108072_2021-10-24_final
2021-10-25 09:08:13	ga_ls7e_ard_3-2-0_099080_2021-10-24_final
2021-10-26 09:51:23	ga_ls7e_ard_3-2-0_106080_2021-10-26_final
2021-10-27 10:35:45	ga_ls7e_ard_3-2-0_113083_2021-10-27_final
2021-10-30 09:22:19	ga_ls7e_ard_3-2-0_102070_2021-10-29_final
2021-11-03 09:00:25	ga_ls7e_ard_3-2-0_098078_2021-11-02_final
2021-11-07 10:11:24	ga_ls7e_ard_3-2-0_110071_2021-11-07_final
2021-11-09 09:58:03	ga_ls7e_ard_3-2-0_108069_2021-11-09_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-18 09:53:23	ga_ls7e_ard_3-2-1_107075_2021-11-18_final
2021-11-21 10:24:23	ga_ls7e_ard_3-2-1_112076_2021-11-21_final
2021-12-02 08:29:31	ga_ls7e_ard_3-2-1_093085_2021-12-01_final
2021-12-05 08:56:33	ga_ls7e_ard_3-2-1_098076_2021-12-04_final
2021-12-05 10:36:14	ga_ls7e_ard_3-2-1_114078_2021-12-05_final
2021-12-12 09:04:51	ga_ls7e_ard_3-2-1_099083_2021-12-11_final
2021-12-16 10:15:26	ga_ls7e_ard_3-2-1_111075_2021-12-16_final
2021-12-18 08:24:01	ga_ls7e_ard_3-2-1_093075_2021-12-17_final
2021-12-18 08:28:24	ga_ls7e_ard_3-2-1_093086_2021-12-17_final
2021-12-19 09:07:34	ga_ls7e_ard_3-2-1_100076_2021-12-18_final
2021-12-20 08:12:39	ga_ls7e_ard_3-2-1_091078_2021-12-19_final
2021-12-26 09:14:15	ga_ls7e_ard_3-2-1_101079_2021-12-25_final
2021-12-28 09:00:54	ga_ls7e_ard_3-2-1_099077_2021-12-27_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2022-01-01 10:13:51	ga_ls7e_ard_3-2-1_111075_2022-01-01_final
2022-01-02 09:18:56	ga_ls7e_ard_3-2-1_102077_2022-01-01_final
2022-01-02 09:19:20	ga_ls7e_ard_3-2-1_102078_2022-01-01_final
2022-01-03 10:00:29	ga_ls7e_ard_3-2-1_109073_2022-01-03_final
2022-01-06 10:34:17	ga_ls7e_ard_3-2-1_114081_2022-01-06_final
2022-01-10 10:05:12	ga_ls7e_ard_3-2-1_110071_2022-01-10_final
2022-01-13 10:38:13	ga_ls7e_ard_3-2-1_115077_2022-01-13_final
2022-01-14 08:05:13	ga_ls7e_ard_3-2-1_090081_2022-01-13_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-22 08:48:43	ga_ls7e_ard_3-2-1_098068_2022-01-21_final
2022-01-22 10:31:58	ga_ls7e_ard_3-2-1_114079_2022-01-22_final
2022-01-28 08:18:13	ga_ls7e_ard_3-2-1_092086_2022-01-27_final
2022-02-05 09:00:53	ga_ls7e_ard_3-2-1_100071_2022-02-04_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-07 10:29:35	ga_ls7e_ard_3-2-1_114077_2022-02-07_final
2022-02-14 10:35:50	ga_ls7e_ard_3-2-1_115079_2022-02-14_final
2022-02-15 09:36:55	ga_ls7e_ard_3-2-1_106071_2022-02-15_final
2022-02-15 09:37:19	ga_ls7e_ard_3-2-1_106072_2022-02-15_final
2022-02-16 08:41:35	ga_ls7e_ard_3-2-1_097072_2022-02-15_final
2022-02-20 09:56:58	ga_ls7e_ard_3-2-1_109076_2022-02-20_final
2022-02-21 09:01:15	ga_ls7e_ard_3-2-1_100076_2022-02-20_final
2022-02-22 08:10:44	ga_ls7e_ard_3-2-1_091089_2022-02-21_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-05 09:23:14	ga_ls7e_ard_3-2-1_104072_2022-03-04_final
2022-03-13 08:32:35	ga_ls7e_ard_3-2-1_096071_2022-03-12_final
2022-03-13 08:37:46	ga_ls7e_ard_3-2-1_096084_2022-03-12_final
2022-03-15 10:04:05	ga_ls7e_ard_3-2-1_110084_2022-03-15_final
2022-03-17 08:11:51	ga_ls7e_ard_3-2-1_092082_2022-03-16_final
2022-03-18 08:54:12	ga_ls7e_ard_3-2-1_099080_2022-03-17_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_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
2022-03-26 09:38:55	ga_ls7e_ard_3-2-1_107070_2022-03-26_final
2022-03-26 09:43:18	ga_ls7e_ard_3-2-1_107081_2022-03-26_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-04-03 10:29:10	ga_ls7e_ard_3-2-1_115074_2022-04-03_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