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 08:43:14	ga_ls7e_ard_3-2-0_094087_2021-09-19_final
2021-09-20 10:15:44	ga_ls7e_ard_3-2-0_110071_2021-09-20_final
2021-10-26 09:51:47	ga_ls7e_ard_3-2-0_106081_2021-10-26_final
2021-11-14 10:20:29	ga_ls7e_ard_3-2-1_111080_2021-11-14_final
2021-11-15 09:21:35	ga_ls7e_ard_3-2-1_102072_2021-11-14_final
2021-11-19 08:54:28	ga_ls7e_ard_3-2-1_098067_2021-11-18_final
2021-11-19 10:38:32	ga_ls7e_ard_3-2-1_114080_2021-11-19_final
2021-11-19 10:38:56	ga_ls7e_ard_3-2-1_114081_2021-11-19_final
2021-11-21 08:47:06	ga_ls7e_ard_3-2-1_096080_2021-11-20_final
2021-11-26 10:41:39	ga_ls7e_ard_3-2-1_115074_2021-11-26_final
2021-12-02 08:29:31	ga_ls7e_ard_3-2-1_093085_2021-12-01_final
2021-12-08 09:26:46	ga_ls7e_ard_3-2-1_103075_2021-12-07_final
2021-12-09 08:34:15	ga_ls7e_ard_3-2-1_094083_2021-12-08_final
2021-12-10 09:15:01	ga_ls7e_ard_3-2-1_101077_2021-12-09_final
2021-12-10 09:16:13	ga_ls7e_ard_3-2-1_101080_2021-12-09_final
2021-12-10 09:17:01	ga_ls7e_ard_3-2-1_101082_2021-12-09_final
2021-12-11 08:21:18	ga_ls7e_ard_3-2-1_092082_2021-12-10_final
2021-12-14 08:49:55	ga_ls7e_ard_3-2-1_097077_2021-12-13_final
2021-12-14 10:29:11	ga_ls7e_ard_3-2-1_113078_2021-12-14_final
2021-12-18 10:03:17	ga_ls7e_ard_3-2-1_109076_2021-12-18_final
2021-12-20 09:51:56	ga_ls7e_ard_3-2-1_107079_2021-12-20_final
2021-12-21 08:57:49	ga_ls7e_ard_3-2-1_098083_2021-12-20_final
2021-12-21 10:33:06	ga_ls7e_ard_3-2-1_114074_2021-12-21_final
2021-12-24 09:23:13	ga_ls7e_ard_3-2-1_103070_2021-12-23_final
2021-12-25 10:09:35	ga_ls7e_ard_3-2-1_110078_2021-12-25_final
2021-12-27 09:53:49	ga_ls7e_ard_3-2-1_108070_2021-12-27_final
2021-12-27 09:54:13	ga_ls7e_ard_3-2-1_108071_2021-12-27_final
2021-12-27 09:54:37	ga_ls7e_ard_3-2-1_108072_2021-12-27_final
2021-12-29 09:45:39	ga_ls7e_ard_3-2-1_106081_2021-12-29_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2022-01-01 10:12:15	ga_ls7e_ard_3-2-1_111071_2022-01-01_final
2022-01-03 10:03:17	ga_ls7e_ard_3-2-1_109080_2022-01-03_final
2022-01-10 08:27:31	ga_ls7e_ard_3-2-1_094074_2022-01-09_final
2022-01-13 08:58:32	ga_ls7e_ard_3-2-1_099075_2022-01-12_final
2022-01-13 09:00:32	ga_ls7e_ard_3-2-1_099080_2022-01-12_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-14 09:44:06	ga_ls7e_ard_3-2-1_106081_2022-01-14_final
2022-01-15 10:26:28	ga_ls7e_ard_3-2-1_113079_2022-01-15_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-19 08:20:54	ga_ls7e_ard_3-2-1_093075_2022-01-18_final
2022-01-21 08:10:44	ga_ls7e_ard_3-2-1_091081_2022-01-20_final
2022-01-21 09:49:37	ga_ls7e_ard_3-2-1_107081_2022-01-21_final
2022-01-23 07:56:35	ga_ls7e_ard_3-2-1_089077_2022-01-22_final
2022-01-23 07:58:35	ga_ls7e_ard_3-2-1_089082_2022-01-22_final
2022-01-23 09:34:40	ga_ls7e_ard_3-2-1_105075_2022-01-23_final
2022-01-25 09:22:06	ga_ls7e_ard_3-2-1_103075_2022-01-24_final
2022-01-26 08:26:47	ga_ls7e_ard_3-2-1_094076_2022-01-25_final
2022-01-28 08:17:26	ga_ls7e_ard_3-2-1_092084_2022-01-27_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-30 09:40:33	ga_ls7e_ard_3-2-1_106076_2022-01-30_final
2022-02-02 08:32:40	ga_ls7e_ard_3-2-1_095077_2022-02-01_final
2022-02-02 08:34:40	ga_ls7e_ard_3-2-1_095082_2022-02-01_final
2022-02-02 08:35:52	ga_ls7e_ard_3-2-1_095085_2022-02-01_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-07 08:51:30	ga_ls7e_ard_3-2-1_098079_2022-02-06_final
2022-02-07 10:28:23	ga_ls7e_ard_3-2-1_114074_2022-02-07_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-08 07:57:23	ga_ls7e_ard_3-2-1_089083_2022-02-07_final
2022-02-10 09:21:18	ga_ls7e_ard_3-2-1_103077_2022-02-09_final
2022-02-11 10:02:27	ga_ls7e_ard_3-2-1_110072_2022-02-11_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-13 09:54:16	ga_ls7e_ard_3-2-1_108083_2022-02-13_final
2022-02-14 10:35:26	ga_ls7e_ard_3-2-1_115078_2022-02-14_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-21 09:00:28	ga_ls7e_ard_3-2-1_100074_2022-02-20_final
2022-02-22 08:07:08	ga_ls7e_ard_3-2-1_091080_2022-02-21_final
2022-02-22 09:47:13	ga_ls7e_ard_3-2-1_107083_2022-02-22_final
2022-02-23 10:28:47	ga_ls7e_ard_3-2-1_114079_2022-02-23_final
2022-02-24 09:30:17	ga_ls7e_ard_3-2-1_105072_2022-02-24_final
2022-02-25 08:39:45	ga_ls7e_ard_3-2-1_096085_2022-02-24_final
2022-02-25 10:14:14	ga_ls7e_ard_3-2-1_112074_2022-02-25_final
2022-02-27 10:02:53	ga_ls7e_ard_3-2-1_110077_2022-02-27_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-01 09:49:56	ga_ls7e_ard_3-2-1_108076_2022-03-01_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-02 10:34:17	ga_ls7e_ard_3-2-1_115079_2022-03-02_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-04 10:23:20	ga_ls7e_ard_3-2-1_113083_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
2022-03-10 08:07:11	ga_ls7e_ard_3-2-1_091084_2022-03-09_final
2022-03-11 08:46:45	ga_ls7e_ard_3-2-1_098075_2022-03-10_final
2022-03-11 08:47:57	ga_ls7e_ard_3-2-1_098078_2022-03-10_final
2022-03-11 08:49:08	ga_ls7e_ard_3-2-1_098081_2022-03-10_final
2022-03-18 08:52:12	ga_ls7e_ard_3-2-1_099075_2022-03-17_final
2022-03-22 08:26:43	ga_ls7e_ard_3-2-1_095074_2022-03-21_final
2022-03-24 08:18:10	ga_ls7e_ard_3-2-1_093084_2022-03-23_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_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
2022-03-27 08:45:11	ga_ls7e_ard_3-2-1_098075_2022-03-26_final
2022-03-31 10:00:34	ga_ls7e_ard_3-2-1_110079_2022-03-31_final
2022-04-01 09:01:39	ga_ls7e_ard_3-2-1_101071_2022-03-31_final
2022-04-02 08:07:32	ga_ls7e_ard_3-2-1_092075_2022-04-01_final
2022-04-02 09:44:49	ga_ls7e_ard_3-2-1_108071_2022-04-02_final
2022-04-03 08:50:41	ga_ls7e_ard_3-2-1_099075_2022-04-02_final
2022-04-04 07:58:10	ga_ls7e_ard_3-2-1_090083_2022-04-03_final
2022-04-04 09:35:03	ga_ls7e_ard_3-2-1_106078_2022-04-04_final
2022-04-05 08:36:56	ga_ls7e_ard_3-2-1_097072_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years