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:

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First 100 results (query limit)

Time (local)	Label
2021-09-20 08:38:51	ga_ls7e_ard_3-2-0_094076_2021-09-19_final
2021-09-20 10:14:08	ga_ls7e_ard_3-2-0_110067_2021-09-20_final
2021-10-26 09:47:00	ga_ls7e_ard_3-2-0_106069_2021-10-26_final
2021-11-14 10:19:17	ga_ls7e_ard_3-2-1_111077_2021-11-14_final
2021-11-14 10:19:41	ga_ls7e_ard_3-2-1_111078_2021-11-14_final
2021-11-15 09:24:46	ga_ls7e_ard_3-2-1_102080_2021-11-14_final
2021-11-17 09:12:13	ga_ls7e_ard_3-2-1_100080_2021-11-16_final
2021-11-19 08:58:52	ga_ls7e_ard_3-2-1_098078_2021-11-18_final
2021-11-27 09:45:08	ga_ls7e_ard_3-2-1_106072_2021-11-27_final
2021-11-27 09:45:32	ga_ls7e_ard_3-2-1_106073_2021-11-27_final
2021-11-30 08:42:04	ga_ls7e_ard_3-2-1_095085_2021-11-29_final
2021-11-30 10:17:45	ga_ls7e_ard_3-2-1_111077_2021-11-30_final
2021-12-01 09:22:26	ga_ls7e_ard_3-2-1_102078_2021-11-30_final
2021-12-02 08:26:44	ga_ls7e_ard_3-2-1_093078_2021-12-01_final
2021-12-02 08:28:20	ga_ls7e_ard_3-2-1_093082_2021-12-01_final
2021-12-05 08:59:45	ga_ls7e_ard_3-2-1_098084_2021-12-04_final
2021-12-07 10:23:17	ga_ls7e_ard_3-2-1_112077_2021-12-07_final
2021-12-08 09:27:10	ga_ls7e_ard_3-2-1_103076_2021-12-07_final
2021-12-08 09:27:58	ga_ls7e_ard_3-2-1_103078_2021-12-07_final
2021-12-09 08:32:39	ga_ls7e_ard_3-2-1_094079_2021-12-08_final
2021-12-09 10:11:32	ga_ls7e_ard_3-2-1_110079_2021-12-09_final
2021-12-11 08:22:06	ga_ls7e_ard_3-2-1_092084_2021-12-10_final
2021-12-11 08:22:30	ga_ls7e_ard_3-2-1_092085_2021-12-10_final
2021-12-11 09:59:46	ga_ls7e_ard_3-2-1_108081_2021-12-11_final
2021-12-12 09:00:28	ga_ls7e_ard_3-2-1_099072_2021-12-11_final
2021-12-14 08:48:19	ga_ls7e_ard_3-2-1_097073_2021-12-13_final
2021-12-17 09:19:20	ga_ls7e_ard_3-2-1_102074_2021-12-16_final
2021-12-18 08:28:48	ga_ls7e_ard_3-2-1_093087_2021-12-17_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-19 09:06:46	ga_ls7e_ard_3-2-1_100074_2021-12-18_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-19 09:10:46	ga_ls7e_ard_3-2-1_100084_2021-12-18_final
2021-12-20 08:14:15	ga_ls7e_ard_3-2-1_091082_2021-12-19_final
2021-12-20 08:15:51	ga_ls7e_ard_3-2-1_091086_2021-12-19_final
2021-12-21 08:54:37	ga_ls7e_ard_3-2-1_098075_2021-12-20_final
2021-12-24 09:27:13	ga_ls7e_ard_3-2-1_103080_2021-12-23_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-28 09:00:06	ga_ls7e_ard_3-2-1_099075_2021-12-27_final
2021-12-28 09:02:06	ga_ls7e_ard_3-2-1_099080_2021-12-27_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2022-01-03 10:00:53	ga_ls7e_ard_3-2-1_109074_2022-01-03_final
2022-01-04 09:05:10	ga_ls7e_ard_3-2-1_100074_2022-01-03_final
2022-01-05 08:12:38	ga_ls7e_ard_3-2-1_091082_2022-01-04_final
2022-01-07 09:34:35	ga_ls7e_ard_3-2-1_105071_2022-01-07_final
2022-01-07 09:37:46	ga_ls7e_ard_3-2-1_105079_2022-01-07_final
2022-01-08 10:19:45	ga_ls7e_ard_3-2-1_112076_2022-01-08_final
2022-01-09 09:20:50	ga_ls7e_ard_3-2-1_103068_2022-01-08_final
2022-01-12 08:19:46	ga_ls7e_ard_3-2-1_092086_2022-01-11_final
2022-01-15 08:48:47	ga_ls7e_ard_3-2-1_097082_2022-01-14_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-21 08:09:56	ga_ls7e_ard_3-2-1_091079_2022-01-20_final
2022-01-23 07:58:35	ga_ls7e_ard_3-2-1_089082_2022-01-22_final
2022-01-27 09:11:33	ga_ls7e_ard_3-2-1_101080_2022-01-26_final
2022-01-28 08:18:37	ga_ls7e_ard_3-2-1_092087_2022-01-27_final
2022-01-29 08:57:24	ga_ls7e_ard_3-2-1_099076_2022-01-28_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-31 08:45:14	ga_ls7e_ard_3-2-1_097077_2022-01-30_final
2022-01-31 08:46:02	ga_ls7e_ard_3-2-1_097079_2022-01-30_final
2022-02-02 08:34:16	ga_ls7e_ard_3-2-1_095081_2022-02-01_final
2022-02-08 09:33:52	ga_ls7e_ard_3-2-1_105077_2022-02-08_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-16 08:42:47	ga_ls7e_ard_3-2-1_097075_2022-02-15_final
2022-02-18 08:30:38	ga_ls7e_ard_3-2-1_095076_2022-02-17_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-19 09:13:00	ga_ls7e_ard_3-2-1_102074_2022-02-18_final
2022-02-19 09:15:00	ga_ls7e_ard_3-2-1_102079_2022-02-18_final
2022-02-19 09:15:24	ga_ls7e_ard_3-2-1_102080_2022-02-18_final
2022-02-20 09:54:35	ga_ls7e_ard_3-2-1_109070_2022-02-20_final
2022-02-22 09:44:49	ga_ls7e_ard_3-2-1_107077_2022-02-22_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-02-25 08:40:09	ga_ls7e_ard_3-2-1_096086_2022-02-24_final
2022-02-25 10:16:38	ga_ls7e_ard_3-2-1_112080_2022-02-25_final
2022-03-01 08:10:39	ga_ls7e_ard_3-2-1_092075_2022-02-28_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-02 08:57:01	ga_ls7e_ard_3-2-1_099083_2022-03-01_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
2022-03-04 10:21:44	ga_ls7e_ard_3-2-1_113079_2022-03-04_final
2022-03-05 09:26:01	ga_ls7e_ard_3-2-1_104079_2022-03-04_final
2022-03-06 08:27:54	ga_ls7e_ard_3-2-1_095073_2022-03-05_final
2022-03-07 09:13:04	ga_ls7e_ard_3-2-1_102078_2022-03-06_final
2022-03-10 09:42:28	ga_ls7e_ard_3-2-1_107075_2022-03-10_final
2022-03-11 10:25:13	ga_ls7e_ard_3-2-1_114074_2022-03-11_final
2022-03-12 09:29:54	ga_ls7e_ard_3-2-1_105075_2022-03-11_final
2022-03-14 09:18:32	ga_ls7e_ard_3-2-1_103078_2022-03-13_final
2022-03-15 08:21:37	ga_ls7e_ard_3-2-1_094075_2022-03-14_final
2022-03-15 09:59:18	ga_ls7e_ard_3-2-1_110072_2022-03-15_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-19 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-24 08:15:46	ga_ls7e_ard_3-2-1_093078_2022-03-23_final
2022-03-25 08:56:32	ga_ls7e_ard_3-2-1_100072_2022-03-24_final
2022-03-25 08:56:56	ga_ls7e_ard_3-2-1_100073_2022-03-24_final
2022-03-26 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-03-30 09:15:48	ga_ls7e_ard_3-2-1_103075_2022-03-29_final
2022-03-30 09:16:36	ga_ls7e_ard_3-2-1_103077_2022-03-29_final
2022-03-31 10:00:58	ga_ls7e_ard_3-2-1_110080_2022-03-31_final
2022-04-03 10:30:46	ga_ls7e_ard_3-2-1_115078_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