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
2021-10-12 09:40:18	ga_ls7e_ard_3-2-0_104080_2021-10-12_final
2021-10-13 10:23:52	ga_ls7e_ard_3-2-0_111081_2021-10-13_final
2021-10-15 10:08:08	ga_ls7e_ard_3-2-0_109073_2021-10-15_final
2021-10-15 10:08:56	ga_ls7e_ard_3-2-0_109075_2021-10-15_final
2021-10-16 09:11:38	ga_ls7e_ard_3-2-0_100071_2021-10-15_final
2021-10-16 09:14:49	ga_ls7e_ard_3-2-0_100079_2021-10-15_final
2021-10-25 10:44:42	ga_ls7e_ard_3-2-0_115074_2021-10-25_final
2021-10-25 10:45:54	ga_ls7e_ard_3-2-0_115077_2021-10-25_final
2021-10-27 08:51:41	ga_ls7e_ard_3-2-0_097070_2021-10-26_final
2021-10-27 08:53:41	ga_ls7e_ard_3-2-0_097075_2021-10-26_final
2021-10-28 09:38:51	ga_ls7e_ard_3-2-0_104080_2021-10-28_final
2021-10-29 10:20:25	ga_ls7e_ard_3-2-0_111076_2021-10-29_final
2021-10-30 09:24:42	ga_ls7e_ard_3-2-0_102076_2021-10-29_final
2021-10-31 08:28:12	ga_ls7e_ard_3-2-0_093074_2021-10-30_final
2021-10-31 10:08:16	ga_ls7e_ard_3-2-0_109077_2021-10-31_final
2021-11-02 08:18:50	ga_ls7e_ard_3-2-0_091082_2021-11-01_final
2021-11-02 08:21:38	ga_ls7e_ard_3-2-0_091089_2021-11-01_final
2021-11-04 09:39:59	ga_ls7e_ard_3-2-0_105069_2021-11-04_final
2021-11-15 09:25:10	ga_ls7e_ard_3-2-1_102081_2021-11-14_final
2021-11-17 09:11:49	ga_ls7e_ard_3-2-1_100079_2021-11-16_final
2021-11-18 08:14:54	ga_ls7e_ard_3-2-1_091076_2021-11-17_final
2021-11-18 08:16:06	ga_ls7e_ard_3-2-1_091079_2021-11-17_final
2021-11-20 08:03:33	ga_ls7e_ard_3-2-1_089079_2021-11-19_final
2021-11-21 08:44:18	ga_ls7e_ard_3-2-1_096073_2021-11-20_final
2021-11-22 09:27:04	ga_ls7e_ard_3-2-1_103072_2021-11-21_final
2021-11-22 09:28:40	ga_ls7e_ard_3-2-1_103076_2021-11-21_final
2021-11-23 10:09:26	ga_ls7e_ard_3-2-1_110070_2021-11-23_final
2021-11-26 09:01:10	ga_ls7e_ard_3-2-1_099070_2021-11-25_final
2021-11-29 09:35:47	ga_ls7e_ard_3-2-1_104080_2021-11-29_final
2021-12-04 09:50:16	ga_ls7e_ard_3-2-1_107071_2021-12-04_final
2021-12-04 09:55:03	ga_ls7e_ard_3-2-1_107083_2021-12-04_final
2021-12-07 10:26:04	ga_ls7e_ard_3-2-1_112084_2021-12-07_final
2021-12-09 10:09:32	ga_ls7e_ard_3-2-1_110074_2021-12-09_final
2021-12-13 08:07:57	ga_ls7e_ard_3-2-1_090080_2021-12-12_final
2021-12-14 08:50:43	ga_ls7e_ard_3-2-1_097079_2021-12-13_final
2021-12-18 08:26:00	ga_ls7e_ard_3-2-1_093080_2021-12-17_final
2021-12-20 08:16:15	ga_ls7e_ard_3-2-1_091087_2021-12-19_final
2022-01-02 09:16:08	ga_ls7e_ard_3-2-1_102070_2022-01-01_final
2022-01-02 09:18:08	ga_ls7e_ard_3-2-1_102075_2022-01-01_final
2022-01-04 09:08:21	ga_ls7e_ard_3-2-1_100082_2022-01-03_final
2022-01-05 09:48:43	ga_ls7e_ard_3-2-1_107075_2022-01-05_final
2022-01-05 09:50:43	ga_ls7e_ard_3-2-1_107080_2022-01-05_final
2022-01-06 10:33:53	ga_ls7e_ard_3-2-1_114080_2022-01-06_final
2022-01-10 10:06:48	ga_ls7e_ard_3-2-1_110075_2022-01-10_final
2022-01-12 08:17:46	ga_ls7e_ard_3-2-1_092081_2022-01-11_final
2022-01-12 08:19:46	ga_ls7e_ard_3-2-1_092086_2022-01-11_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-12 09:57:03	ga_ls7e_ard_3-2-1_108082_2022-01-12_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-15 08:49:11	ga_ls7e_ard_3-2-1_097083_2022-01-14_final
2022-01-17 08:34:38	ga_ls7e_ard_3-2-1_095078_2022-01-16_final
2022-01-17 08:35:26	ga_ls7e_ard_3-2-1_095080_2022-01-16_final
2022-01-18 09:14:13	ga_ls7e_ard_3-2-1_102069_2022-01-17_final
2022-01-24 10:19:25	ga_ls7e_ard_3-2-1_112079_2022-01-24_final
2022-01-25 09:23:18	ga_ls7e_ard_3-2-1_103078_2022-01-24_final
2022-01-27 09:12:21	ga_ls7e_ard_3-2-1_101082_2022-01-26_final
2022-01-28 09:55:30	ga_ls7e_ard_3-2-1_108082_2022-01-28_final
2022-01-29 08:59:47	ga_ls7e_ard_3-2-1_099082_2022-01-28_final
2022-01-31 08:47:14	ga_ls7e_ard_3-2-1_097082_2022-01-30_final
2022-02-02 08:31:05	ga_ls7e_ard_3-2-1_095073_2022-02-01_final
2022-02-02 08:35:28	ga_ls7e_ard_3-2-1_095084_2022-02-01_final
2022-02-02 10:14:21	ga_ls7e_ard_3-2-1_111084_2022-02-02_final
2022-02-04 09:58:35	ga_ls7e_ard_3-2-1_109076_2022-02-04_final
2022-02-05 09:04:04	ga_ls7e_ard_3-2-1_100079_2022-02-04_final
2022-02-08 07:56:11	ga_ls7e_ard_3-2-1_089080_2022-02-07_final
2022-02-11 08:25:34	ga_ls7e_ard_3-2-1_094077_2022-02-10_final
2022-02-14 08:58:09	ga_ls7e_ard_3-2-1_099082_2022-02-13_final
2022-02-15 08:01:38	ga_ls7e_ard_3-2-1_090080_2022-02-14_final
2022-02-16 08:41:11	ga_ls7e_ard_3-2-1_097071_2022-02-15_final
2022-02-16 10:21:16	ga_ls7e_ard_3-2-1_113074_2022-02-16_final
2022-02-18 08:31:26	ga_ls7e_ard_3-2-1_095078_2022-02-17_final
2022-02-18 10:10:43	ga_ls7e_ard_3-2-1_111079_2022-02-18_final
2022-02-23 08:51:30	ga_ls7e_ard_3-2-1_098083_2022-02-22_final
2022-02-23 10:26:47	ga_ls7e_ard_3-2-1_114074_2022-02-23_final
2022-02-26 09:18:31	ga_ls7e_ard_3-2-1_103074_2022-02-25_final
2022-02-27 08:26:48	ga_ls7e_ard_3-2-1_094084_2022-02-26_final
2022-03-01 08:12:39	ga_ls7e_ard_3-2-1_092080_2022-02-28_final
2022-03-06 10:07:59	ga_ls7e_ard_3-2-1_111076_2022-03-06_final
2022-03-08 08:18:33	ga_ls7e_ard_3-2-1_093081_2022-03-07_final
2022-03-10 09:40:52	ga_ls7e_ard_3-2-1_107071_2022-03-10_final
2022-03-10 09:41:40	ga_ls7e_ard_3-2-1_107073_2022-03-10_final
2022-03-11 08:50:44	ga_ls7e_ard_3-2-1_098085_2022-03-10_final
2022-03-12 09:31:06	ga_ls7e_ard_3-2-1_105078_2022-03-12_final
2022-03-15 08:22:49	ga_ls7e_ard_3-2-1_094078_2022-03-14_final
2022-03-17 08:10:39	ga_ls7e_ard_3-2-1_092079_2022-03-16_final
2022-03-17 09:49:07	ga_ls7e_ard_3-2-1_108078_2022-03-17_final
2022-03-17 09:49:31	ga_ls7e_ard_3-2-1_108079_2022-03-17_final
2022-03-19 07:58:54	ga_ls7e_ard_3-2-1_090081_2022-03-18_final
2022-03-22 10:06:48	ga_ls7e_ard_3-2-1_111077_2022-03-22_final
2022-03-24 09:55:03	ga_ls7e_ard_3-2-1_109079_2022-03-24_final
2022-03-24 09:55:27	ga_ls7e_ard_3-2-1_109080_2022-03-24_final
2022-03-26 09:40:30	ga_ls7e_ard_3-2-1_107074_2022-03-26_final
2022-03-28 09:29:09	ga_ls7e_ard_3-2-1_105077_2022-03-27_final
2022-03-28 09:29:33	ga_ls7e_ard_3-2-1_105078_2022-03-27_final
2022-03-29 08:34:38	ga_ls7e_ard_3-2-1_096080_2022-03-28_final
2022-03-31 08:21:17	ga_ls7e_ard_3-2-1_094078_2022-03-30_final
2022-03-31 09:59:46	ga_ls7e_ard_3-2-1_110077_2022-03-31_final
2022-04-02 08:09:56	ga_ls7e_ard_3-2-1_092081_2022-04-01_final
2022-04-02 09:47:12	ga_ls7e_ard_3-2-1_108077_2022-04-02_final
2022-04-03 08:54:17	ga_ls7e_ard_3-2-1_099084_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years