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 10:16:08	ga_ls7e_ard_3-2-0_110072_2021-09-20_final
2021-10-25 10:46:42	ga_ls7e_ard_3-2-0_115079_2021-10-25_final
2021-11-12 10:31:27	ga_ls7e_ard_3-2-1_113076_2021-11-12_final
2021-11-13 09:35:44	ga_ls7e_ard_3-2-1_104076_2021-11-13_final
2021-11-13 09:36:08	ga_ls7e_ard_3-2-1_104077_2021-11-13_final
2021-11-14 08:42:00	ga_ls7e_ard_3-2-1_095081_2021-11-13_final
2021-11-14 10:20:53	ga_ls7e_ard_3-2-1_111081_2021-11-14_final
2021-11-15 09:21:35	ga_ls7e_ard_3-2-1_102072_2021-11-14_final
2021-11-19 08:55:40	ga_ls7e_ard_3-2-1_098070_2021-11-18_final
2021-11-23 08:35:20	ga_ls7e_ard_3-2-1_094082_2021-11-22_final
2021-11-25 10:00:52	ga_ls7e_ard_3-2-1_108080_2021-11-25_final
2021-11-27 08:09:27	ga_ls7e_ard_3-2-1_090080_2021-11-26_final
2021-11-28 10:31:30	ga_ls7e_ard_3-2-1_113080_2021-11-28_final
2021-11-28 10:32:18	ga_ls7e_ard_3-2-1_113082_2021-11-28_final
2021-12-01 09:19:39	ga_ls7e_ard_3-2-1_102071_2021-11-30_final
2021-12-05 10:35:02	ga_ls7e_ard_3-2-1_114075_2021-12-05_final
2021-12-08 09:25:10	ga_ls7e_ard_3-2-1_103071_2021-12-07_final
2021-12-12 10:41:20	ga_ls7e_ard_3-2-1_115077_2021-12-12_final
2021-12-14 08:51:07	ga_ls7e_ard_3-2-1_097080_2021-12-13_final
2021-12-14 08:52:18	ga_ls7e_ard_3-2-1_097083_2021-12-13_final
2021-12-21 08:55:25	ga_ls7e_ard_3-2-1_098077_2021-12-20_final
2021-12-21 08:55:49	ga_ls7e_ard_3-2-1_098078_2021-12-20_final
2021-12-21 10:34:18	ga_ls7e_ard_3-2-1_114077_2021-12-21_final
2021-12-22 09:38:34	ga_ls7e_ard_3-2-1_105077_2021-12-22_final
2021-12-23 08:40:28	ga_ls7e_ard_3-2-1_096071_2021-12-22_final
2021-12-23 08:42:04	ga_ls7e_ard_3-2-1_096075_2021-12-22_final
2021-12-25 10:06:47	ga_ls7e_ard_3-2-1_110071_2021-12-25_final
2022-01-01 08:37:22	ga_ls7e_ard_3-2-1_095081_2021-12-31_final
2022-01-03 10:04:05	ga_ls7e_ard_3-2-1_109082_2022-01-03_final
2022-01-05 08:13:02	ga_ls7e_ard_3-2-1_091083_2022-01-04_final
2022-01-08 08:38:52	ga_ls7e_ard_3-2-1_096071_2022-01-07_final
2022-01-08 10:20:09	ga_ls7e_ard_3-2-1_112077_2022-01-08_final
2022-01-08 10:22:08	ga_ls7e_ard_3-2-1_112082_2022-01-08_final
2022-01-10 10:09:36	ga_ls7e_ard_3-2-1_110082_2022-01-10_final
2022-01-11 09:09:53	ga_ls7e_ard_3-2-1_101072_2022-01-10_final
2022-01-12 08:15:46	ga_ls7e_ard_3-2-1_092076_2022-01-11_final
2022-01-12 09:57:51	ga_ls7e_ard_3-2-1_108084_2022-01-12_final
2022-01-14 08:04:25	ga_ls7e_ard_3-2-1_090079_2022-01-13_final
2022-01-19 08:21:41	ga_ls7e_ard_3-2-1_093077_2022-01-18_final
2022-01-19 09:58:34	ga_ls7e_ard_3-2-1_109072_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
2022-01-22 10:30:47	ga_ls7e_ard_3-2-1_114076_2022-01-22_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-28 08:17:50	ga_ls7e_ard_3-2-1_092085_2022-01-27_final
2022-01-28 09:54:42	ga_ls7e_ard_3-2-1_108080_2022-01-28_final
2022-01-30 08:03:16	ga_ls7e_ard_3-2-1_090080_2022-01-29_final
2022-01-30 08:04:28	ga_ls7e_ard_3-2-1_090083_2022-01-29_final
2022-01-30 09:40:57	ga_ls7e_ard_3-2-1_106077_2022-01-30_final
2022-01-31 08:47:38	ga_ls7e_ard_3-2-1_097083_2022-01-30_final
2022-01-31 10:25:19	ga_ls7e_ard_3-2-1_113080_2022-01-31_final
2022-01-31 10:25:42	ga_ls7e_ard_3-2-1_113081_2022-01-31_final
2022-02-02 08:35:52	ga_ls7e_ard_3-2-1_095085_2022-02-01_final
2022-02-02 10:13:33	ga_ls7e_ard_3-2-1_111082_2022-02-02_final
2022-02-04 08:19:43	ga_ls7e_ard_3-2-1_093076_2022-02-03_final
2022-02-04 08:24:30	ga_ls7e_ard_3-2-1_093088_2022-02-03_final
2022-02-04 10:00:59	ga_ls7e_ard_3-2-1_109082_2022-02-04_final
2022-02-06 08:08:21	ga_ls7e_ard_3-2-1_091079_2022-02-05_final
2022-02-07 08:49:30	ga_ls7e_ard_3-2-1_098074_2022-02-06_final
2022-02-07 08:51:54	ga_ls7e_ard_3-2-1_098080_2022-02-06_final
2022-02-09 08:36:56	ga_ls7e_ard_3-2-1_096074_2022-02-08_final
2022-02-11 10:03:39	ga_ls7e_ard_3-2-1_110075_2022-02-11_final
2022-02-13 09:54:40	ga_ls7e_ard_3-2-1_108084_2022-02-13_final
2022-02-14 10:35:02	ga_ls7e_ard_3-2-1_115077_2022-02-14_final
2022-02-14 10:36:14	ga_ls7e_ard_3-2-1_115080_2022-02-14_final
2022-02-15 08:01:38	ga_ls7e_ard_3-2-1_090080_2022-02-14_final
2022-02-15 08:02:49	ga_ls7e_ard_3-2-1_090083_2022-02-14_final
2022-02-16 08:45:11	ga_ls7e_ard_3-2-1_097081_2022-02-15_final
2022-02-16 08:45:35	ga_ls7e_ard_3-2-1_097082_2022-02-15_final
2022-02-17 09:26:45	ga_ls7e_ard_3-2-1_104077_2022-02-16_final
2022-02-18 08:29:51	ga_ls7e_ard_3-2-1_095074_2022-02-17_final
2022-02-18 08:33:26	ga_ls7e_ard_3-2-1_095083_2022-02-17_final
2022-02-20 08:22:05	ga_ls7e_ard_3-2-1_093086_2022-02-19_final
2022-02-21 09:02:51	ga_ls7e_ard_3-2-1_100080_2022-02-20_final
2022-02-23 10:26:47	ga_ls7e_ard_3-2-1_114074_2022-02-23_final
2022-02-23 10:27:35	ga_ls7e_ard_3-2-1_114076_2022-02-23_final
2022-02-23 10:27:59	ga_ls7e_ard_3-2-1_114077_2022-02-23_final
2022-02-27 08:25:36	ga_ls7e_ard_3-2-1_094081_2022-02-26_final
2022-03-01 08:12:15	ga_ls7e_ard_3-2-1_092079_2022-02-28_final
2022-03-03 08:00:54	ga_ls7e_ard_3-2-1_090082_2022-03-02_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-06 08:31:54	ga_ls7e_ard_3-2-1_095083_2022-03-05_final
2022-03-06 10:10:47	ga_ls7e_ard_3-2-1_111083_2022-03-06_final
2022-03-07 09:12:40	ga_ls7e_ard_3-2-1_102077_2022-03-06_final
2022-03-10 08:07:11	ga_ls7e_ard_3-2-1_091084_2022-03-09_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-11 10:26:49	ga_ls7e_ard_3-2-1_114078_2022-03-11_final
2022-03-15 08:21:13	ga_ls7e_ard_3-2-1_094074_2022-03-14_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-22 08:30:19	ga_ls7e_ard_3-2-1_095083_2022-03-21_final
2022-03-22 10:06:00	ga_ls7e_ard_3-2-1_111075_2022-03-22_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-25 08:59:44	ga_ls7e_ard_3-2-1_100080_2022-03-24_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-26 09:43:42	ga_ls7e_ard_3-2-1_107082_2022-03-26_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-31 08:22:53	ga_ls7e_ard_3-2-1_094082_2022-03-30_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_final
2022-04-02 08:10:20	ga_ls7e_ard_3-2-1_092082_2022-04-01_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