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
2021-08-31 10:43:25	ga_ls7e_ard_3-2-0_114074_2021-08-31_final
2021-09-04 10:22:20	ga_ls7e_ard_3-2-0_110084_2021-09-04_final
2021-09-13 08:34:06	ga_ls7e_ard_3-2-0_093078_2021-09-12_final
2021-09-16 09:06:43	ga_ls7e_ard_3-2-0_098083_2021-09-15_final
2021-09-17 08:09:49	ga_ls7e_ard_3-2-0_089080_2021-09-16_final
2021-10-10 09:49:15	ga_ls7e_ard_3-2-0_106071_2021-10-10_final
2021-10-13 08:46:35	ga_ls7e_ard_3-2-0_095085_2021-10-12_final
2021-10-15 08:30:03	ga_ls7e_ard_3-2-0_093075_2021-10-14_final
2021-10-17 08:17:55	ga_ls7e_ard_3-2-0_091076_2021-10-16_final
2021-10-18 08:58:17	ga_ls7e_ard_3-2-0_098069_2021-10-17_final
2021-10-18 10:41:33	ga_ls7e_ard_3-2-0_114080_2021-10-18_final
2021-10-20 10:29:01	ga_ls7e_ard_3-2-0_112080_2021-10-20_final
2021-10-24 08:27:27	ga_ls7e_ard_3-2-0_092086_2021-10-23_final
2021-10-24 10:00:21	ga_ls7e_ard_3-2-0_108071_2021-10-24_final
2021-10-25 10:45:06	ga_ls7e_ard_3-2-0_115075_2021-10-25_final
2021-10-27 08:51:41	ga_ls7e_ard_3-2-0_097070_2021-10-26_final
2021-10-27 08:56:29	ga_ls7e_ard_3-2-0_097082_2021-10-26_final
2021-10-27 10:35:21	ga_ls7e_ard_3-2-0_113082_2021-10-27_final
2021-10-31 08:32:35	ga_ls7e_ard_3-2-0_093085_2021-10-30_final
2021-10-31 10:10:40	ga_ls7e_ard_3-2-0_109083_2021-10-31_final
2021-11-02 08:20:26	ga_ls7e_ard_3-2-0_091086_2021-11-01_final
2021-11-03 08:56:49	ga_ls7e_ard_3-2-0_098069_2021-11-02_final
2021-11-03 10:38:05	ga_ls7e_ard_3-2-0_114075_2021-11-03_final
2021-11-04 09:39:59	ga_ls7e_ard_3-2-0_105069_2021-11-04_final
2021-11-07 08:34:55	ga_ls7e_ard_3-2-0_094077_2021-11-06_final
2021-11-12 10:33:26	ga_ls7e_ard_3-2-1_113081_2021-11-12_final
2021-11-15 09:20:47	ga_ls7e_ard_3-2-1_102070_2021-11-14_final
2021-11-16 10:05:08	ga_ls7e_ard_3-2-1_109073_2021-11-16_final
2021-11-16 10:09:08	ga_ls7e_ard_3-2-1_109083_2021-11-16_final
2021-11-18 08:18:54	ga_ls7e_ard_3-2-1_091086_2021-11-17_final
2021-11-19 10:36:08	ga_ls7e_ard_3-2-1_114074_2021-11-19_final
2021-11-20 09:41:37	ga_ls7e_ard_3-2-1_105077_2021-11-20_final
2021-11-25 08:25:35	ga_ls7e_ard_3-2-1_092089_2021-11-24_final
2021-11-26 09:01:10	ga_ls7e_ard_3-2-1_099070_2021-11-25_final
2021-11-26 09:03:34	ga_ls7e_ard_3-2-1_099076_2021-11-25_final
2021-11-26 10:43:38	ga_ls7e_ard_3-2-1_115079_2021-11-26_final
2021-11-28 08:48:38	ga_ls7e_ard_3-2-1_097070_2021-11-27_final
2021-11-28 08:54:37	ga_ls7e_ard_3-2-1_097085_2021-11-27_final
2021-11-30 08:40:52	ga_ls7e_ard_3-2-1_095082_2021-11-29_final
2021-12-05 10:37:01	ga_ls7e_ard_3-2-1_114080_2021-12-05_final
2021-12-08 09:26:22	ga_ls7e_ard_3-2-1_103074_2021-12-07_final
2021-12-10 09:17:24	ga_ls7e_ard_3-2-1_101083_2021-12-09_final
2021-12-11 10:00:34	ga_ls7e_ard_3-2-1_108083_2021-12-11_final
2021-12-12 10:41:44	ga_ls7e_ard_3-2-1_115078_2021-12-12_final
2021-12-13 08:08:21	ga_ls7e_ard_3-2-1_090081_2021-12-12_final
2021-12-14 08:52:42	ga_ls7e_ard_3-2-1_097084_2021-12-13_final
2021-12-18 08:24:01	ga_ls7e_ard_3-2-1_093075_2021-12-17_final
2021-12-18 10:06:05	ga_ls7e_ard_3-2-1_109083_2021-12-18_final
2021-12-19 09:09:58	ga_ls7e_ard_3-2-1_100082_2021-12-18_final
2021-12-20 08:14:39	ga_ls7e_ard_3-2-1_091083_2021-12-19_final
2021-12-20 09:51:08	ga_ls7e_ard_3-2-1_107077_2021-12-20_final
2021-12-22 09:35:23	ga_ls7e_ard_3-2-1_105069_2021-12-22_final
2021-12-23 08:40:04	ga_ls7e_ard_3-2-1_096070_2021-12-22_final
2021-12-29 09:45:39	ga_ls7e_ard_3-2-1_106081_2021-12-29_final
2021-12-30 10:28:48	ga_ls7e_ard_3-2-1_113081_2021-12-30_final
2022-01-05 08:15:26	ga_ls7e_ard_3-2-1_091089_2022-01-04_final
2022-01-05 09:47:31	ga_ls7e_ard_3-2-1_107072_2022-01-05_final
2022-01-10 10:05:12	ga_ls7e_ard_3-2-1_110071_2022-01-10_final
2022-01-10 10:06:24	ga_ls7e_ard_3-2-1_110074_2022-01-10_final
2022-01-10 10:07:36	ga_ls7e_ard_3-2-1_110077_2022-01-10_final
2022-01-11 09:11:05	ga_ls7e_ard_3-2-1_101075_2022-01-10_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-23 07:58:11	ga_ls7e_ard_3-2-1_089081_2022-01-22_final
2022-01-24 08:36:57	ga_ls7e_ard_3-2-1_096070_2022-01-23_final
2022-01-26 08:31:11	ga_ls7e_ard_3-2-1_094087_2022-01-25_final
2022-01-28 08:17:26	ga_ls7e_ard_3-2-1_092084_2022-01-27_final
2022-02-02 08:35:04	ga_ls7e_ard_3-2-1_095083_2022-02-01_final
2022-02-04 08:23:18	ga_ls7e_ard_3-2-1_093085_2022-02-03_final
2022-02-06 08:09:57	ga_ls7e_ard_3-2-1_091083_2022-02-05_final
2022-02-07 08:51:06	ga_ls7e_ard_3-2-1_098078_2022-02-06_final
2022-02-08 07:56:59	ga_ls7e_ard_3-2-1_089082_2022-02-07_final
2022-02-08 09:35:27	ga_ls7e_ard_3-2-1_105081_2022-02-08_final
2022-02-09 08:35:45	ga_ls7e_ard_3-2-1_096071_2022-02-08_final
2022-02-10 09:23:17	ga_ls7e_ard_3-2-1_103082_2022-02-09_final
2022-02-12 09:06:20	ga_ls7e_ard_3-2-1_101071_2022-02-11_final
2022-02-15 08:05:13	ga_ls7e_ard_3-2-1_090089_2022-02-14_final
2022-02-20 09:59:22	ga_ls7e_ard_3-2-1_109082_2022-02-20_final
2022-02-23 10:29:11	ga_ls7e_ard_3-2-1_114080_2022-02-23_final
2022-03-02 08:55:01	ga_ls7e_ard_3-2-1_099078_2022-03-01_final
2022-03-03 08:04:05	ga_ls7e_ard_3-2-1_090090_2022-03-02_final
2022-03-03 09:37:47	ga_ls7e_ard_3-2-1_106077_2022-03-03_final
2022-03-07 09:11:04	ga_ls7e_ard_3-2-1_102073_2022-03-06_final
2022-03-10 08:08:47	ga_ls7e_ard_3-2-1_091088_2022-03-09_final
2022-03-11 10:25:37	ga_ls7e_ard_3-2-1_114075_2022-03-11_final
2022-03-12 07:52:37	ga_ls7e_ard_3-2-1_089079_2022-03-11_final
2022-03-15 09:59:42	ga_ls7e_ard_3-2-1_110073_2022-03-15_final
2022-03-15 10:04:05	ga_ls7e_ard_3-2-1_110084_2022-03-15_final
2022-03-18 10:33:05	ga_ls7e_ard_3-2-1_115080_2022-03-18_final
2022-03-22 10:07:12	ga_ls7e_ard_3-2-1_111078_2022-03-22_final
2022-03-23 09:09:29	ga_ls7e_ard_3-2-1_102073_2022-03-22_final
2022-03-24 08:18:34	ga_ls7e_ard_3-2-1_093085_2022-03-23_final
2022-03-26 08:04:01	ga_ls7e_ard_3-2-1_091080_2022-03-25_final
2022-03-29 08:36:14	ga_ls7e_ard_3-2-1_096084_2022-03-28_final
2022-04-03 08:52:41	ga_ls7e_ard_3-2-1_099080_2022-04-02_final
2022-04-04 09:36:15	ga_ls7e_ard_3-2-1_106081_2022-04-04_final
2022-04-04 09:36:39	ga_ls7e_ard_3-2-1_106082_2022-04-04_final
2022-04-05 08:36:08	ga_ls7e_ard_3-2-1_097070_2022-04-04_final
2022-04-05 10:19:00	ga_ls7e_ard_3-2-1_113080_2022-04-05_final
2022-04-05 10:19:48	ga_ls7e_ard_3-2-1_113082_2022-04-05_final
2022-04-05 10:20:12	ga_ls7e_ard_3-2-1_113083_2022-04-05_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