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 08:54:59	ga_ls7e_ard_3-2-0_096085_2021-09-17_final
2021-09-20 08:41:39	ga_ls7e_ard_3-2-0_094083_2021-09-19_final
2021-09-20 10:15:44	ga_ls7e_ard_3-2-0_110071_2021-09-20_final
2021-09-20 10:20:31	ga_ls7e_ard_3-2-0_110083_2021-09-20_final
2021-10-25 09:09:49	ga_ls7e_ard_3-2-0_099084_2021-10-24_final
2021-11-01 09:10:58	ga_ls7e_ard_3-2-0_100073_2021-10-31_final
2021-11-02 09:52:56	ga_ls7e_ard_3-2-0_107070_2021-11-02_final
2021-11-03 08:58:49	ga_ls7e_ard_3-2-0_098074_2021-11-02_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 10:15:47	ga_ls7e_ard_3-2-0_110082_2021-11-07_final
2021-11-08 09:15:41	ga_ls7e_ard_3-2-0_101071_2021-11-07_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-10 10:44:00	ga_ls7e_ard_3-2-0_115076_2021-11-10_final
2021-11-13 09:32:56	ga_ls7e_ard_3-2-1_104069_2021-11-13_final
2021-11-13 09:33:20	ga_ls7e_ard_3-2-1_104070_2021-11-13_final
2021-11-25 10:00:52	ga_ls7e_ard_3-2-1_108080_2021-11-25_final
2021-11-26 10:42:51	ga_ls7e_ard_3-2-1_115077_2021-11-26_final
2021-11-29 09:31:24	ga_ls7e_ard_3-2-1_104069_2021-11-29_final
2021-12-04 09:50:40	ga_ls7e_ard_3-2-1_107072_2021-12-04_final
2021-12-06 09:37:19	ga_ls7e_ard_3-2-1_105070_2021-12-06_final
2021-12-10 09:15:01	ga_ls7e_ard_3-2-1_101077_2021-12-09_final
2021-12-11 09:56:35	ga_ls7e_ard_3-2-1_108073_2021-12-11_final
2021-12-12 09:01:40	ga_ls7e_ard_3-2-1_099075_2021-12-11_final
2021-12-12 10:41:20	ga_ls7e_ard_3-2-1_115077_2021-12-12_final
2021-12-14 10:27:36	ga_ls7e_ard_3-2-1_113074_2021-12-14_final
2021-12-17 09:17:44	ga_ls7e_ard_3-2-1_102070_2021-12-16_final
2021-12-18 10:02:05	ga_ls7e_ard_3-2-1_109073_2021-12-18_final
2021-12-24 09:23:13	ga_ls7e_ard_3-2-1_103070_2021-12-23_final
2021-12-25 10:07:35	ga_ls7e_ard_3-2-1_110073_2021-12-25_final
2021-12-26 09:13:27	ga_ls7e_ard_3-2-1_101077_2021-12-25_final
2021-12-26 09:15:51	ga_ls7e_ard_3-2-1_101083_2021-12-25_final
2021-12-27 09:58:13	ga_ls7e_ard_3-2-1_108081_2021-12-27_final
2022-01-01 08:34:34	ga_ls7e_ard_3-2-1_095074_2021-12-31_final
2022-01-03 08:23:12	ga_ls7e_ard_3-2-1_093077_2022-01-02_final
2022-01-03 10:00:05	ga_ls7e_ard_3-2-1_109072_2022-01-03_final
2022-01-03 10:00:53	ga_ls7e_ard_3-2-1_109074_2022-01-03_final
2022-01-04 09:08:45	ga_ls7e_ard_3-2-1_100083_2022-01-03_final
2022-01-05 08:10:15	ga_ls7e_ard_3-2-1_091076_2022-01-04_final
2022-01-05 08:10:39	ga_ls7e_ard_3-2-1_091077_2022-01-04_final
2022-01-05 08:11:26	ga_ls7e_ard_3-2-1_091079_2022-01-04_final
2022-01-06 08:51:25	ga_ls7e_ard_3-2-1_098071_2022-01-05_final
2022-01-08 10:19:45	ga_ls7e_ard_3-2-1_112076_2022-01-08_final
2022-01-12 08:20:10	ga_ls7e_ard_3-2-1_092087_2022-01-11_final
2022-01-12 09:54:39	ga_ls7e_ard_3-2-1_108076_2022-01-12_final
2022-01-14 08:06:25	ga_ls7e_ard_3-2-1_090084_2022-01-13_final
2022-01-14 09:41:18	ga_ls7e_ard_3-2-1_106074_2022-01-14_final
2022-01-15 08:47:35	ga_ls7e_ard_3-2-1_097079_2022-01-14_final
2022-01-17 10:15:31	ga_ls7e_ard_3-2-1_111083_2022-01-17_final
2022-01-19 08:21:17	ga_ls7e_ard_3-2-1_093076_2022-01-18_final
2022-01-19 10:00:10	ga_ls7e_ard_3-2-1_109076_2022-01-19_final
2022-01-21 08:13:56	ga_ls7e_ard_3-2-1_091089_2022-01-20_final
2022-01-21 09:47:13	ga_ls7e_ard_3-2-1_107075_2022-01-21_final
2022-01-24 10:20:37	ga_ls7e_ard_3-2-1_112082_2022-01-24_final
2022-01-26 08:29:11	ga_ls7e_ard_3-2-1_094082_2022-01-25_final
2022-01-27 09:11:09	ga_ls7e_ard_3-2-1_101079_2022-01-26_final
2022-01-28 08:18:37	ga_ls7e_ard_3-2-1_092087_2022-01-27_final
2022-01-29 09:00:35	ga_ls7e_ard_3-2-1_099084_2022-01-28_final
2022-01-29 10:37:52	ga_ls7e_ard_3-2-1_115080_2022-01-29_final
2022-01-30 08:06:52	ga_ls7e_ard_3-2-1_090089_2022-01-29_final
2022-01-30 09:41:45	ga_ls7e_ard_3-2-1_106079_2022-01-30_final
2022-02-03 09:13:02	ga_ls7e_ard_3-2-1_102070_2022-02-02_final
2022-02-06 09:44:50	ga_ls7e_ard_3-2-1_107073_2022-02-06_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-09 08:36:09	ga_ls7e_ard_3-2-1_096072_2022-02-08_final
2022-02-11 08:24:22	ga_ls7e_ard_3-2-1_094074_2022-02-10_final
2022-02-11 08:29:10	ga_ls7e_ard_3-2-1_094086_2022-02-10_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-12 09:08:19	ga_ls7e_ard_3-2-1_101076_2022-02-11_final
2022-02-13 09:54:16	ga_ls7e_ard_3-2-1_108083_2022-02-13_final
2022-02-20 08:21:41	ga_ls7e_ard_3-2-1_093085_2022-02-19_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-24 09:29:29	ga_ls7e_ard_3-2-1_105070_2022-02-23_final
2022-02-27 08:26:48	ga_ls7e_ard_3-2-1_094084_2022-02-26_final
2022-02-27 10:02:53	ga_ls7e_ard_3-2-1_110077_2022-02-27_final
2022-02-27 10:04:05	ga_ls7e_ard_3-2-1_110080_2022-02-27_final
2022-02-27 10:05:17	ga_ls7e_ard_3-2-1_110083_2022-02-27_final
2022-02-28 09:07:34	ga_ls7e_ard_3-2-1_101078_2022-02-27_final
2022-03-02 10:34:41	ga_ls7e_ard_3-2-1_115080_2022-03-02_final
2022-03-05 09:21:38	ga_ls7e_ard_3-2-1_104068_2022-03-04_final
2022-03-05 09:22:50	ga_ls7e_ard_3-2-1_104071_2022-03-04_final
2022-03-06 10:07:35	ga_ls7e_ard_3-2-1_111075_2022-03-06_final
2022-03-08 08:16:09	ga_ls7e_ard_3-2-1_093075_2022-03-07_final
2022-03-09 08:58:54	ga_ls7e_ard_3-2-1_100074_2022-03-08_final
2022-03-09 09:02:54	ga_ls7e_ard_3-2-1_100084_2022-03-08_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-20 10:20:32	ga_ls7e_ard_3-2-1_113080_2022-03-20_final
2022-03-22 10:05:12	ga_ls7e_ard_3-2-1_111073_2022-03-22_final
2022-03-23 09:09:05	ga_ls7e_ard_3-2-1_102072_2022-03-22_final
2022-03-25 09:00:56	ga_ls7e_ard_3-2-1_100083_2022-03-24_final
2022-03-26 08:02:26	ga_ls7e_ard_3-2-1_091076_2022-03-25_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-29 08:31:51	ga_ls7e_ard_3-2-1_096073_2022-03-28_final
2022-03-29 08:37:02	ga_ls7e_ard_3-2-1_096086_2022-03-28_final
2022-03-29 10:13:31	ga_ls7e_ard_3-2-1_112080_2022-03-29_final
2022-03-31 10:00:58	ga_ls7e_ard_3-2-1_110080_2022-03-31_final
2022-04-05 08:36:32	ga_ls7e_ard_3-2-1_097071_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years