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
2021-09-20 10:15:20	ga_ls7e_ard_3-2-0_110070_2021-09-20_final
2021-10-01 09:57:24	ga_ls7e_ard_3-2-0_107074_2021-10-01_final
2021-10-02 10:42:34	ga_ls7e_ard_3-2-0_114079_2021-10-02_final
2021-10-08 10:05:46	ga_ls7e_ard_3-2-0_108081_2021-10-08_final
2021-10-10 09:53:14	ga_ls7e_ard_3-2-0_106081_2021-10-10_final
2021-10-11 08:53:08	ga_ls7e_ard_3-2-0_097070_2021-10-10_final
2021-10-14 09:24:10	ga_ls7e_ard_3-2-0_102071_2021-10-13_final
2021-10-17 08:18:19	ga_ls7e_ard_3-2-0_091077_2021-10-16_final
2021-10-25 09:04:14	ga_ls7e_ard_3-2-0_099070_2021-10-24_final
2021-10-25 09:08:13	ga_ls7e_ard_3-2-0_099080_2021-10-24_final
2021-10-26 08:16:06	ga_ls7e_ard_3-2-0_090089_2021-10-25_final
2021-10-30 09:23:54	ga_ls7e_ard_3-2-0_102074_2021-10-29_final
2021-10-31 10:08:16	ga_ls7e_ard_3-2-0_109077_2021-10-31_final
2021-11-01 09:14:33	ga_ls7e_ard_3-2-0_100082_2021-10-31_final
2021-11-02 08:17:15	ga_ls7e_ard_3-2-0_091078_2021-11-01_final
2021-11-03 08:57:37	ga_ls7e_ard_3-2-0_098071_2021-11-02_final
2021-11-03 09:01:12	ga_ls7e_ard_3-2-0_098080_2021-11-02_final
2021-11-05 08:45:04	ga_ls7e_ard_3-2-0_096071_2021-11-04_final
2021-11-07 08:36:06	ga_ls7e_ard_3-2-0_094080_2021-11-06_final
2021-11-07 10:11:24	ga_ls7e_ard_3-2-0_110071_2021-11-07_final
2021-11-11 09:47:29	ga_ls7e_ard_3-2-0_106074_2021-11-11_final
2021-11-12 10:33:50	ga_ls7e_ard_3-2-1_113082_2021-11-12_final
2021-11-14 08:42:24	ga_ls7e_ard_3-2-1_095082_2021-11-13_final
2021-11-14 10:22:05	ga_ls7e_ard_3-2-1_111084_2021-11-14_final
2021-11-15 09:22:23	ga_ls7e_ard_3-2-1_102074_2021-11-14_final
2021-11-21 08:48:42	ga_ls7e_ard_3-2-1_096084_2021-11-20_final
2021-11-23 10:09:50	ga_ls7e_ard_3-2-1_110071_2021-11-23_final
2021-11-25 10:01:40	ga_ls7e_ard_3-2-1_108082_2021-11-25_final
2021-11-30 08:41:16	ga_ls7e_ard_3-2-1_095083_2021-11-29_final
2021-11-30 10:16:57	ga_ls7e_ard_3-2-1_111075_2021-11-30_final
2021-12-02 08:29:31	ga_ls7e_ard_3-2-1_093085_2021-12-01_final
2021-12-04 08:14:11	ga_ls7e_ard_3-2-1_091078_2021-12-03_final
2021-12-05 08:54:09	ga_ls7e_ard_3-2-1_098070_2021-12-04_final
2021-12-05 08:54:57	ga_ls7e_ard_3-2-1_098072_2021-12-04_final
2021-12-07 08:46:24	ga_ls7e_ard_3-2-1_096082_2021-12-06_final
2021-12-07 10:26:04	ga_ls7e_ard_3-2-1_112084_2021-12-07_final
2021-12-11 08:19:18	ga_ls7e_ard_3-2-1_092077_2021-12-10_final
2021-12-11 08:22:30	ga_ls7e_ard_3-2-1_092085_2021-12-10_final
2021-12-12 09:04:51	ga_ls7e_ard_3-2-1_099083_2021-12-11_final
2021-12-12 10:40:33	ga_ls7e_ard_3-2-1_115075_2021-12-12_final
2021-12-13 08:09:57	ga_ls7e_ard_3-2-1_090085_2021-12-12_final
2021-12-14 08:47:31	ga_ls7e_ard_3-2-1_097071_2021-12-13_final
2021-12-16 10:12:39	ga_ls7e_ard_3-2-1_111068_2021-12-16_final
2021-12-16 10:15:26	ga_ls7e_ard_3-2-1_111075_2021-12-16_final
2021-12-16 10:19:02	ga_ls7e_ard_3-2-1_111084_2021-12-16_final
2021-12-17 09:18:08	ga_ls7e_ard_3-2-1_102071_2021-12-16_final
2021-12-21 08:53:25	ga_ls7e_ard_3-2-1_098072_2021-12-20_final
2021-12-22 08:00:30	ga_ls7e_ard_3-2-1_089079_2021-12-21_final
2021-12-23 10:24:08	ga_ls7e_ard_3-2-1_112083_2021-12-23_final
2021-12-24 09:23:37	ga_ls7e_ard_3-2-1_103071_2021-12-23_final
2021-12-25 08:29:54	ga_ls7e_ard_3-2-1_094076_2021-12-24_final
2021-12-28 10:38:35	ga_ls7e_ard_3-2-1_115074_2021-12-28_final
2021-12-29 09:45:15	ga_ls7e_ard_3-2-1_106080_2021-12-29_final
2022-01-01 08:38:58	ga_ls7e_ard_3-2-1_095085_2021-12-31_final
2022-01-01 10:13:51	ga_ls7e_ard_3-2-1_111075_2022-01-01_final
2022-01-02 09:15:44	ga_ls7e_ard_3-2-1_102069_2022-01-01_final
2022-01-05 08:13:26	ga_ls7e_ard_3-2-1_091084_2022-01-04_final
2022-01-06 08:55:00	ga_ls7e_ard_3-2-1_098080_2022-01-05_final
2022-01-06 10:33:53	ga_ls7e_ard_3-2-1_114080_2022-01-06_final
2022-01-09 09:26:26	ga_ls7e_ard_3-2-1_103082_2022-01-08_final
2022-01-14 09:41:18	ga_ls7e_ard_3-2-1_106074_2022-01-14_final
2022-01-17 10:12:19	ga_ls7e_ard_3-2-1_111075_2022-01-17_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-17 10:15:31	ga_ls7e_ard_3-2-1_111083_2022-01-17_final
2022-01-19 08:22:05	ga_ls7e_ard_3-2-1_093078_2022-01-18_final
2022-01-25 09:22:06	ga_ls7e_ard_3-2-1_103075_2022-01-24_final
2022-01-31 08:44:02	ga_ls7e_ard_3-2-1_097074_2022-01-30_final
2022-01-31 08:45:38	ga_ls7e_ard_3-2-1_097078_2022-01-30_final
2022-02-06 08:08:45	ga_ls7e_ard_3-2-1_091080_2022-02-05_final
2022-02-06 09:44:50	ga_ls7e_ard_3-2-1_107073_2022-02-06_final
2022-02-06 09:49:13	ga_ls7e_ard_3-2-1_107084_2022-02-06_final
2022-02-08 07:57:23	ga_ls7e_ard_3-2-1_089083_2022-02-07_final
2022-02-09 10:19:25	ga_ls7e_ard_3-2-1_112083_2022-02-09_final
2022-02-10 09:22:29	ga_ls7e_ard_3-2-1_103080_2022-02-09_final
2022-02-11 10:06:27	ga_ls7e_ard_3-2-1_110082_2022-02-11_final
2022-02-11 10:06:50	ga_ls7e_ard_3-2-1_110083_2022-02-11_final
2022-02-16 08:44:23	ga_ls7e_ard_3-2-1_097079_2022-02-15_final
2022-02-16 10:21:16	ga_ls7e_ard_3-2-1_113074_2022-02-16_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-22 09:47:37	ga_ls7e_ard_3-2-1_107084_2022-02-22_final
2022-02-25 10:17:50	ga_ls7e_ard_3-2-1_112083_2022-02-25_final
2022-02-26 09:17:43	ga_ls7e_ard_3-2-1_103072_2022-02-25_final
2022-02-28 09:06:22	ga_ls7e_ard_3-2-1_101075_2022-02-27_final
2022-02-28 09:08:46	ga_ls7e_ard_3-2-1_101081_2022-02-27_final
2022-03-01 09:51:32	ga_ls7e_ard_3-2-1_108080_2022-03-01_final
2022-03-11 08:50:44	ga_ls7e_ard_3-2-1_098085_2022-03-10_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-13 08:32:35	ga_ls7e_ard_3-2-1_096071_2022-03-12_final
2022-03-13 08:33:47	ga_ls7e_ard_3-2-1_096074_2022-03-12_final
2022-03-19 09:32:59	ga_ls7e_ard_3-2-1_106069_2022-03-19_final
2022-03-22 08:30:43	ga_ls7e_ard_3-2-1_095084_2022-03-21_final
2022-03-22 10:08:47	ga_ls7e_ard_3-2-1_111082_2022-03-22_final
2022-03-27 08:43:36	ga_ls7e_ard_3-2-1_098071_2022-03-26_final
2022-03-27 10:24:28	ga_ls7e_ard_3-2-1_114076_2022-03-27_final
2022-03-27 10:26:28	ga_ls7e_ard_3-2-1_114081_2022-03-27_final
2022-03-28 09:26:22	ga_ls7e_ard_3-2-1_105070_2022-03-27_final
2022-03-29 10:15:07	ga_ls7e_ard_3-2-1_112084_2022-03-29_final
2022-03-31 09:58:10	ga_ls7e_ard_3-2-1_110073_2022-03-31_final
2022-03-31 09:59:22	ga_ls7e_ard_3-2-1_110076_2022-03-31_final
2022-03-31 09:59:46	ga_ls7e_ard_3-2-1_110077_2022-03-31_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