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
2021-10-13 08:42:12	ga_ls7e_ard_3-2-0_095074_2021-10-12_final
2021-10-16 09:16:01	ga_ls7e_ard_3-2-0_100082_2021-10-15_final
2021-10-17 09:55:36	ga_ls7e_ard_3-2-0_107073_2021-10-17_final
2021-10-26 09:48:12	ga_ls7e_ard_3-2-0_106072_2021-10-26_final
2021-10-31 10:06:17	ga_ls7e_ard_3-2-0_109072_2021-10-31_final
2021-10-31 10:09:52	ga_ls7e_ard_3-2-0_109081_2021-10-31_final
2021-11-02 09:54:08	ga_ls7e_ard_3-2-0_107073_2021-11-02_final
2021-11-02 09:55:19	ga_ls7e_ard_3-2-0_107076_2021-11-02_final
2021-11-02 09:58:31	ga_ls7e_ard_3-2-0_107084_2021-11-02_final
2021-11-03 08:59:13	ga_ls7e_ard_3-2-0_098075_2021-11-02_final
2021-11-03 09:01:36	ga_ls7e_ard_3-2-0_098081_2021-11-02_final
2021-11-05 10:25:56	ga_ls7e_ard_3-2-0_112076_2021-11-05_final
2021-11-14 10:20:29	ga_ls7e_ard_3-2-1_111080_2021-11-14_final
2021-11-20 09:38:50	ga_ls7e_ard_3-2-1_105070_2021-11-20_final
2021-11-21 08:45:30	ga_ls7e_ard_3-2-1_096076_2021-11-20_final
2021-11-30 08:40:28	ga_ls7e_ard_3-2-1_095081_2021-11-29_final
2021-12-02 10:06:00	ga_ls7e_ard_3-2-1_109079_2021-12-02_final
2021-12-03 09:08:18	ga_ls7e_ard_3-2-1_100074_2021-12-02_final
2021-12-03 09:08:42	ga_ls7e_ard_3-2-1_100075_2021-12-02_final
2021-12-03 09:10:18	ga_ls7e_ard_3-2-1_100079_2021-12-02_final
2021-12-04 09:51:04	ga_ls7e_ard_3-2-1_107073_2021-12-04_final
2021-12-11 08:21:18	ga_ls7e_ard_3-2-1_092082_2021-12-10_final
2021-12-12 09:01:40	ga_ls7e_ard_3-2-1_099075_2021-12-11_final
2021-12-14 08:52:18	ga_ls7e_ard_3-2-1_097083_2021-12-13_final
2021-12-16 08:37:22	ga_ls7e_ard_3-2-1_095077_2021-12-15_final
2021-12-16 08:40:33	ga_ls7e_ard_3-2-1_095085_2021-12-15_final
2021-12-17 09:19:43	ga_ls7e_ard_3-2-1_102075_2021-12-16_final
2021-12-17 09:20:55	ga_ls7e_ard_3-2-1_102078_2021-12-16_final
2021-12-18 08:26:48	ga_ls7e_ard_3-2-1_093082_2021-12-17_final
2021-12-19 09:06:46	ga_ls7e_ard_3-2-1_100074_2021-12-18_final
2021-12-27 08:21:20	ga_ls7e_ard_3-2-1_092086_2021-12-26_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2022-01-01 10:16:39	ga_ls7e_ard_3-2-1_111082_2022-01-01_final
2022-01-03 08:24:48	ga_ls7e_ard_3-2-1_093081_2022-01-02_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-03 10:02:53	ga_ls7e_ard_3-2-1_109079_2022-01-03_final
2022-01-04 09:07:10	ga_ls7e_ard_3-2-1_100079_2022-01-03_final
2022-01-04 09:08:21	ga_ls7e_ard_3-2-1_100082_2022-01-03_final
2022-01-05 08:12:38	ga_ls7e_ard_3-2-1_091082_2022-01-04_final
2022-01-06 10:33:05	ga_ls7e_ard_3-2-1_114078_2022-01-06_final
2022-01-08 08:42:52	ga_ls7e_ard_3-2-1_096081_2022-01-07_final
2022-01-08 10:19:21	ga_ls7e_ard_3-2-1_112075_2022-01-08_final
2022-01-09 09:22:02	ga_ls7e_ard_3-2-1_103071_2022-01-08_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-10 08:31:55	ga_ls7e_ard_3-2-1_094085_2022-01-09_final
2022-01-10 10:09:36	ga_ls7e_ard_3-2-1_110082_2022-01-10_final
2022-01-10 10:10:23	ga_ls7e_ard_3-2-1_110084_2022-01-10_final
2022-01-11 09:13:53	ga_ls7e_ard_3-2-1_101082_2022-01-10_final
2022-01-12 08:16:58	ga_ls7e_ard_3-2-1_092079_2022-01-11_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-12 09:56:39	ga_ls7e_ard_3-2-1_108081_2022-01-12_final
2022-01-13 10:37:01	ga_ls7e_ard_3-2-1_115074_2022-01-13_final
2022-01-15 10:27:16	ga_ls7e_ard_3-2-1_113081_2022-01-15_final
2022-01-19 10:02:10	ga_ls7e_ard_3-2-1_109081_2022-01-19_final
2022-01-21 08:13:56	ga_ls7e_ard_3-2-1_091089_2022-01-20_final
2022-01-21 09:46:25	ga_ls7e_ard_3-2-1_107073_2022-01-21_final
2022-01-23 09:36:39	ga_ls7e_ard_3-2-1_105080_2022-01-23_final
2022-01-24 08:41:44	ga_ls7e_ard_3-2-1_096082_2022-01-23_final
2022-01-24 10:18:37	ga_ls7e_ard_3-2-1_112077_2022-01-24_final
2022-01-25 09:23:18	ga_ls7e_ard_3-2-1_103078_2022-01-24_final
2022-01-27 09:11:09	ga_ls7e_ard_3-2-1_101079_2022-01-26_final
2022-01-29 10:36:40	ga_ls7e_ard_3-2-1_115077_2022-01-29_final
2022-01-31 08:47:14	ga_ls7e_ard_3-2-1_097082_2022-01-30_final
2022-02-02 08:35:28	ga_ls7e_ard_3-2-1_095084_2022-02-01_final
2022-02-05 09:04:28	ga_ls7e_ard_3-2-1_100080_2022-02-04_final
2022-02-06 09:45:38	ga_ls7e_ard_3-2-1_107075_2022-02-06_final
2022-02-09 08:41:20	ga_ls7e_ard_3-2-1_096085_2022-02-08_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-11 10:06:03	ga_ls7e_ard_3-2-1_110081_2022-02-11_final
2022-02-14 08:55:21	ga_ls7e_ard_3-2-1_099075_2022-02-13_final
2022-02-14 08:55:45	ga_ls7e_ard_3-2-1_099076_2022-02-13_final
2022-02-18 08:33:26	ga_ls7e_ard_3-2-1_095083_2022-02-17_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-25 08:39:45	ga_ls7e_ard_3-2-1_096085_2022-02-24_final
2022-02-26 09:20:07	ga_ls7e_ard_3-2-1_103078_2022-02-25_final
2022-02-27 10:04:53	ga_ls7e_ard_3-2-1_110082_2022-02-27_final
2022-03-01 08:11:27	ga_ls7e_ard_3-2-1_092077_2022-02-28_final
2022-03-01 08:12:15	ga_ls7e_ard_3-2-1_092079_2022-02-28_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-03 08:00:30	ga_ls7e_ard_3-2-1_090081_2022-03-02_final
2022-03-05 09:25:13	ga_ls7e_ard_3-2-1_104077_2022-03-04_final
2022-03-08 08:16:09	ga_ls7e_ard_3-2-1_093075_2022-03-07_final
2022-03-08 08:18:33	ga_ls7e_ard_3-2-1_093081_2022-03-07_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-13 08:35:47	ga_ls7e_ard_3-2-1_096079_2022-03-12_final
2022-03-14 09:17:44	ga_ls7e_ard_3-2-1_103076_2022-03-13_final
2022-03-17 08:10:15	ga_ls7e_ard_3-2-1_092078_2022-03-16_final
2022-03-17 09:49:31	ga_ls7e_ard_3-2-1_108079_2022-03-17_final
2022-03-18 10:31:53	ga_ls7e_ard_3-2-1_115077_2022-03-18_final
2022-03-19 09:34:35	ga_ls7e_ard_3-2-1_106073_2022-03-19_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-22 10:06:00	ga_ls7e_ard_3-2-1_111075_2022-03-22_final
2022-03-23 09:09:53	ga_ls7e_ard_3-2-1_102074_2022-03-22_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-27 10:24:52	ga_ls7e_ard_3-2-1_114077_2022-03-27_final
2022-03-29 08:31:27	ga_ls7e_ard_3-2-1_096072_2022-03-28_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_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