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
2021-09-18 08:51:47	ga_ls7e_ard_3-2-0_096077_2021-09-17_final
2021-09-18 10:32:40	ga_ls7e_ard_3-2-0_112082_2021-09-18_final
2021-09-20 08:39:15	ga_ls7e_ard_3-2-0_094077_2021-09-19_final
2021-09-20 10:19:43	ga_ls7e_ard_3-2-0_110081_2021-09-20_final
2021-10-17 08:21:54	ga_ls7e_ard_3-2-0_091086_2021-10-16_final
2021-10-26 09:50:12	ga_ls7e_ard_3-2-0_106077_2021-10-26_final
2021-10-27 10:33:46	ga_ls7e_ard_3-2-0_113078_2021-10-27_final
2021-10-28 09:35:39	ga_ls7e_ard_3-2-0_104072_2021-10-28_final
2021-10-31 08:30:11	ga_ls7e_ard_3-2-0_093079_2021-10-30_final
2021-11-01 09:11:46	ga_ls7e_ard_3-2-0_100075_2021-10-31_final
2021-11-03 08:59:37	ga_ls7e_ard_3-2-0_098076_2021-11-02_final
2021-11-04 09:41:35	ga_ls7e_ard_3-2-0_105073_2021-11-04_final
2021-11-05 08:47:28	ga_ls7e_ard_3-2-0_096077_2021-11-04_final
2021-11-05 10:27:32	ga_ls7e_ard_3-2-0_112080_2021-11-05_final
2021-11-13 09:34:32	ga_ls7e_ard_3-2-1_104073_2021-11-13_final
2021-11-14 08:41:13	ga_ls7e_ard_3-2-1_095079_2021-11-13_final
2021-11-14 10:20:05	ga_ls7e_ard_3-2-1_111079_2021-11-14_final
2021-11-17 09:11:49	ga_ls7e_ard_3-2-1_100079_2021-11-16_final
2021-11-22 09:28:40	ga_ls7e_ard_3-2-1_103076_2021-11-21_final
2021-11-23 08:32:33	ga_ls7e_ard_3-2-1_094075_2021-11-22_final
2021-11-25 09:57:41	ga_ls7e_ard_3-2-1_108072_2021-11-25_final
2021-11-27 09:47:32	ga_ls7e_ard_3-2-1_106078_2021-11-27_final
2021-11-28 08:53:49	ga_ls7e_ard_3-2-1_097083_2021-11-27_final
2021-11-29 09:32:36	ga_ls7e_ard_3-2-1_104072_2021-11-29_final
2021-11-30 10:17:45	ga_ls7e_ard_3-2-1_111077_2021-11-30_final
2021-12-07 10:23:41	ga_ls7e_ard_3-2-1_112078_2021-12-07_final
2021-12-07 10:24:05	ga_ls7e_ard_3-2-1_112079_2021-12-07_final
2021-12-11 09:59:22	ga_ls7e_ard_3-2-1_108080_2021-12-11_final
2021-12-12 09:02:04	ga_ls7e_ard_3-2-1_099076_2021-12-11_final
2021-12-13 09:47:37	ga_ls7e_ard_3-2-1_106082_2021-12-13_final
2021-12-14 08:49:55	ga_ls7e_ard_3-2-1_097077_2021-12-13_final
2021-12-16 10:16:38	ga_ls7e_ard_3-2-1_111078_2021-12-16_final
2021-12-16 10:17:50	ga_ls7e_ard_3-2-1_111081_2021-12-16_final
2021-12-18 10:04:29	ga_ls7e_ard_3-2-1_109079_2021-12-18_final
2021-12-23 08:41:16	ga_ls7e_ard_3-2-1_096073_2021-12-22_final
2021-12-23 08:45:15	ga_ls7e_ard_3-2-1_096083_2021-12-22_final
2021-12-25 08:31:06	ga_ls7e_ard_3-2-1_094079_2021-12-24_final
2021-12-25 08:31:30	ga_ls7e_ard_3-2-1_094080_2021-12-24_final
2021-12-30 08:47:56	ga_ls7e_ard_3-2-1_097076_2021-12-29_final
2021-12-30 10:27:13	ga_ls7e_ard_3-2-1_113077_2021-12-30_final
2022-01-01 08:38:34	ga_ls7e_ard_3-2-1_095084_2021-12-31_final
2022-01-01 10:15:51	ga_ls7e_ard_3-2-1_111080_2022-01-01_final
2022-01-03 08:24:24	ga_ls7e_ard_3-2-1_093080_2022-01-02_final
2022-01-05 09:48:43	ga_ls7e_ard_3-2-1_107075_2022-01-05_final
2022-01-05 09:51:07	ga_ls7e_ard_3-2-1_107081_2022-01-05_final
2022-01-06 08:52:13	ga_ls7e_ard_3-2-1_098073_2022-01-05_final
2022-01-10 08:29:55	ga_ls7e_ard_3-2-1_094080_2022-01-09_final
2022-01-10 10:08:24	ga_ls7e_ard_3-2-1_110079_2022-01-10_final
2022-01-17 08:35:50	ga_ls7e_ard_3-2-1_095081_2022-01-16_final
2022-01-17 10:13:55	ga_ls7e_ard_3-2-1_111079_2022-01-17_final
2022-01-21 09:48:01	ga_ls7e_ard_3-2-1_107077_2022-01-21_final
2022-01-26 10:05:16	ga_ls7e_ard_3-2-1_110075_2022-01-26_final
2022-01-30 09:42:09	ga_ls7e_ard_3-2-1_106080_2022-01-30_final
2022-01-30 09:42:33	ga_ls7e_ard_3-2-1_106081_2022-01-30_final
2022-02-02 08:32:17	ga_ls7e_ard_3-2-1_095076_2022-02-01_final
2022-02-04 08:24:30	ga_ls7e_ard_3-2-1_093088_2022-02-03_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-09 10:18:37	ga_ls7e_ard_3-2-1_112081_2022-02-09_final
2022-02-11 08:27:34	ga_ls7e_ard_3-2-1_094082_2022-02-10_final
2022-02-11 08:27:58	ga_ls7e_ard_3-2-1_094083_2022-02-10_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-11 10:04:03	ga_ls7e_ard_3-2-1_110076_2022-02-11_final
2022-02-14 08:54:57	ga_ls7e_ard_3-2-1_099074_2022-02-13_final
2022-02-16 08:42:47	ga_ls7e_ard_3-2-1_097075_2022-02-15_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-18 08:30:14	ga_ls7e_ard_3-2-1_095075_2022-02-17_final
2022-02-18 10:10:19	ga_ls7e_ard_3-2-1_111078_2022-02-18_final
2022-02-18 10:11:07	ga_ls7e_ard_3-2-1_111080_2022-02-18_final
2022-02-20 08:20:05	ga_ls7e_ard_3-2-1_093081_2022-02-19_final
2022-02-23 08:51:06	ga_ls7e_ard_3-2-1_098082_2022-02-22_final
2022-02-25 08:36:57	ga_ls7e_ard_3-2-1_096078_2022-02-24_final
2022-02-25 08:37:21	ga_ls7e_ard_3-2-1_096079_2022-02-24_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-25 10:15:02	ga_ls7e_ard_3-2-1_112076_2022-02-25_final
2022-02-26 09:18:07	ga_ls7e_ard_3-2-1_103073_2022-02-25_final
2022-02-27 10:03:41	ga_ls7e_ard_3-2-1_110079_2022-02-27_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-04 08:43:15	ga_ls7e_ard_3-2-1_097080_2022-03-03_final
2022-03-06 08:29:06	ga_ls7e_ard_3-2-1_095076_2022-03-05_final
2022-03-06 08:30:18	ga_ls7e_ard_3-2-1_095079_2022-03-05_final
2022-03-10 08:09:11	ga_ls7e_ard_3-2-1_091089_2022-03-09_final
2022-03-12 09:30:42	ga_ls7e_ard_3-2-1_105077_2022-03-12_final
2022-03-13 08:36:11	ga_ls7e_ard_3-2-1_096080_2022-03-12_final
2022-03-13 08:38:10	ga_ls7e_ard_3-2-1_096085_2022-03-12_final
2022-03-14 09:15:21	ga_ls7e_ard_3-2-1_103070_2022-03-13_final
2022-03-15 08:23:13	ga_ls7e_ard_3-2-1_094079_2022-03-14_final
2022-03-19 09:37:46	ga_ls7e_ard_3-2-1_106081_2022-03-19_final
2022-03-20 10:20:08	ga_ls7e_ard_3-2-1_113079_2022-03-20_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-24 08:16:34	ga_ls7e_ard_3-2-1_093080_2022-03-23_final
2022-03-26 09:41:42	ga_ls7e_ard_3-2-1_107077_2022-03-26_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-03-29 08:33:50	ga_ls7e_ard_3-2-1_096078_2022-03-28_final
2022-03-30 09:15:24	ga_ls7e_ard_3-2-1_103074_2022-03-29_final
2022-03-31 08:23:17	ga_ls7e_ard_3-2-1_094083_2022-03-30_final
2022-04-01 09:02:03	ga_ls7e_ard_3-2-1_101072_2022-03-31_final
2022-04-03 08:50:18	ga_ls7e_ard_3-2-1_099074_2022-04-02_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