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
2017-12-09 09:30:30	ga_ls7e_ard_3-0-0_091088_2017-12-09_final
2018-12-28 09:21:25	ga_ls7e_ard_3-0-0_091083_2018-12-27_final
2018-12-28 09:21:49	ga_ls7e_ard_3-0-0_091084_2018-12-27_final
2018-12-28 09:22:13	ga_ls7e_ard_3-0-0_091085_2018-12-27_final
2018-12-28 09:22:37	ga_ls7e_ard_3-1-0_091086_2018-12-27_final
2018-12-28 09:23:01	ga_ls7e_ard_3-0-0_091087_2018-12-27_final
2018-12-28 09:23:25	ga_ls7e_ard_3-0-0_091088_2018-12-27_final
2018-12-28 09:23:49	ga_ls7e_ard_3-0-0_091089_2018-12-27_final
2019-02-12 09:30:22	ga_ls7e_ard_3-0-0_093078_2019-02-12_final
2019-02-12 09:30:46	ga_ls7e_ard_3-0-0_093079_2019-02-12_final
2019-02-12 09:31:10	ga_ls7e_ard_3-0-0_093080_2019-02-12_final
2019-02-12 09:31:34	ga_ls7e_ard_3-0-0_093081_2019-02-12_final
2019-02-14 09:19:56	ga_ls7e_ard_3-0-0_091083_2019-02-13_final
2019-02-14 09:20:20	ga_ls7e_ard_3-0-0_091084_2019-02-13_final
2019-02-14 09:20:44	ga_ls7e_ard_3-0-0_091085_2019-02-13_final
2019-02-14 09:21:08	ga_ls7e_ard_3-1-0_091086_2019-02-13_final
2019-02-14 09:21:32	ga_ls7e_ard_3-0-0_091087_2019-02-13_final
2019-02-14 09:21:56	ga_ls7e_ard_3-0-0_091088_2019-02-13_final
2019-02-14 09:22:20	ga_ls7e_ard_3-0-0_091089_2019-02-13_final
2019-02-23 09:15:29	ga_ls7e_ard_3-1-0_090088_2019-02-22_final
2019-02-23 09:15:53	ga_ls7e_ard_3-1-0_090089_2019-02-22_final
2019-02-23 09:16:17	ga_ls7e_ard_3-1-0_090090_2019-02-22_final
2019-03-07 09:33:50	ga_ls7e_ard_3-1-0_094073_2019-03-07_final
2019-03-07 09:34:14	ga_ls7e_ard_3-1-0_094074_2019-03-07_final
2019-03-07 09:34:38	ga_ls7e_ard_3-1-0_094075_2019-03-07_final
2019-03-07 09:35:02	ga_ls7e_ard_3-1-0_094076_2019-03-07_final
2019-03-09 09:23:48	ga_ls7e_ard_3-1-0_092079_2019-03-08_final
2019-03-09 09:24:12	ga_ls7e_ard_3-1-0_092080_2019-03-08_final
2019-03-09 09:24:36	ga_ls7e_ard_3-1-0_092081_2019-03-08_final
2019-03-09 09:25:00	ga_ls7e_ard_3-1-0_092082_2019-03-08_final
2019-03-09 09:25:48	ga_ls7e_ard_3-1-0_092084_2019-03-08_final
2019-03-09 09:26:12	ga_ls7e_ard_3-1-0_092085_2019-03-08_final
2019-03-11 09:14:58	ga_ls7e_ard_3-1-0_090088_2019-03-10_final
2019-03-11 09:15:22	ga_ls7e_ard_3-1-0_090089_2019-03-10_final
2019-03-11 09:15:46	ga_ls7e_ard_3-1-0_090090_2019-03-10_final
2019-03-14 09:37:24	ga_ls7e_ard_3-1-0_095067_2019-03-14_final
2019-03-16 09:28:10	ga_ls7e_ard_3-1-0_093075_2019-03-15_final
2019-03-30 09:36:51	ga_ls7e_ard_3-0-0_095067_2019-03-30_final
2019-04-01 09:27:37	ga_ls7e_ard_3-0-0_093075_2019-03-31_final
2019-04-01 09:28:01	ga_ls7e_ard_3-0-0_093076_2019-03-31_final
2019-04-01 09:28:25	ga_ls7e_ard_3-0-0_093077_2019-03-31_final
2019-04-01 09:28:49	ga_ls7e_ard_3-0-0_093078_2019-03-31_final
2019-04-01 09:29:13	ga_ls7e_ard_3-0-0_093079_2019-03-31_final
2019-04-01 09:29:37	ga_ls7e_ard_3-0-0_093080_2019-03-31_final
2019-04-03 09:18:23	ga_ls7e_ard_3-0-0_091083_2019-04-02_final
2019-04-03 09:18:47	ga_ls7e_ard_3-0-0_091084_2019-04-02_final
2019-04-03 09:19:11	ga_ls7e_ard_3-0-0_091085_2019-04-02_final
2019-04-03 09:19:35	ga_ls7e_ard_3-1-0_091086_2019-04-02_final
2019-04-03 09:19:59	ga_ls7e_ard_3-0-0_091087_2019-04-02_final
2019-04-03 09:20:23	ga_ls7e_ard_3-0-0_091088_2019-04-02_final
2019-05-10 09:31:58	ga_ls7e_ard_3-0-0_094074_2019-05-10_final
2019-05-10 09:32:22	ga_ls7e_ard_3-0-0_094075_2019-05-10_final
2019-05-10 09:32:46	ga_ls7e_ard_3-0-0_094076_2019-05-10_final
2019-05-12 09:21:31	ga_ls7e_ard_3-0-0_092079_2019-05-11_final
2019-05-12 09:21:55	ga_ls7e_ard_3-0-0_092080_2019-05-11_final
2019-05-12 09:22:19	ga_ls7e_ard_3-0-0_092081_2019-05-11_final
2019-05-12 09:22:43	ga_ls7e_ard_3-0-0_092082_2019-05-11_final
2019-05-12 09:23:07	ga_ls7e_ard_3-0-0_092083_2019-05-11_final
2019-05-12 09:23:31	ga_ls7e_ard_3-0-0_092084_2019-05-11_final
2019-05-12 09:23:55	ga_ls7e_ard_3-0-0_092085_2019-05-11_final
2021-08-12 08:35:41	ga_ls7e_ard_3-2-0_093075_2021-08-11_final
2021-08-12 08:36:05	ga_ls7e_ard_3-2-0_093076_2021-08-11_final
2021-08-12 08:36:29	ga_ls7e_ard_3-2-0_093077_2021-08-11_final
2021-08-12 08:36:53	ga_ls7e_ard_3-2-0_093078_2021-08-11_final
2021-08-12 08:37:17	ga_ls7e_ard_3-2-0_093079_2021-08-11_final
2021-08-12 08:37:41	ga_ls7e_ard_3-2-0_093080_2021-08-11_final
2021-08-12 08:38:05	ga_ls7e_ard_3-2-0_093081_2021-08-11_final
2021-08-14 08:26:20	ga_ls7e_ard_3-2-0_091083_2021-08-13_final
2021-08-14 08:26:44	ga_ls7e_ard_3-2-0_091084_2021-08-13_final
2021-08-14 08:27:08	ga_ls7e_ard_3-2-0_091085_2021-08-13_final
2021-08-14 08:27:32	ga_ls7e_ard_3-2-0_091086_2021-08-13_final
2021-08-14 08:27:56	ga_ls7e_ard_3-2-0_091087_2021-08-13_final
2021-08-14 08:28:20	ga_ls7e_ard_3-2-0_091088_2021-08-13_final
2021-08-14 08:28:44	ga_ls7e_ard_3-2-0_091089_2021-08-13_final
2021-08-17 08:50:35	ga_ls7e_ard_3-2-0_096067_2021-08-16_final
2021-10-31 08:29:00	ga_ls7e_ard_3-2-0_093076_2021-10-30_final
2021-10-31 08:29:24	ga_ls7e_ard_3-2-0_093077_2021-10-30_final
2021-10-31 08:30:35	ga_ls7e_ard_3-2-0_093080_2021-10-30_final
2021-10-31 08:30:59	ga_ls7e_ard_3-2-0_093081_2021-10-30_final
2021-11-07 08:33:19	ga_ls7e_ard_3-2-0_094073_2021-11-06_final
2021-11-07 08:33:43	ga_ls7e_ard_3-2-0_094074_2021-11-06_final
2021-11-07 08:34:07	ga_ls7e_ard_3-2-0_094075_2021-11-06_final
2021-11-07 08:34:31	ga_ls7e_ard_3-2-0_094076_2021-11-06_final
2021-11-09 08:23:09	ga_ls7e_ard_3-2-0_092079_2021-11-08_final
2021-11-09 08:23:33	ga_ls7e_ard_3-2-0_092080_2021-11-08_final
2021-11-09 08:23:57	ga_ls7e_ard_3-2-0_092081_2021-11-08_final
2021-11-09 08:24:21	ga_ls7e_ard_3-2-0_092082_2021-11-08_final
2021-11-09 08:24:45	ga_ls7e_ard_3-2-0_092083_2021-11-08_final
2021-11-09 08:25:09	ga_ls7e_ard_3-2-0_092084_2021-11-08_final
2021-11-09 08:25:33	ga_ls7e_ard_3-2-0_092085_2021-11-08_final
2021-12-25 08:29:06	ga_ls7e_ard_3-2-1_094074_2021-12-24_final
2021-12-25 08:29:30	ga_ls7e_ard_3-2-1_094075_2021-12-24_final
2021-12-25 08:29:54	ga_ls7e_ard_3-2-1_094076_2021-12-24_final
2022-01-01 08:33:47	ga_ls7e_ard_3-2-1_095072_2021-12-31_final
2022-01-03 08:22:24	ga_ls7e_ard_3-2-1_093075_2022-01-02_final
2022-01-03 08:22:48	ga_ls7e_ard_3-2-1_093076_2022-01-02_final
2022-01-03 08:23:12	ga_ls7e_ard_3-2-1_093077_2022-01-02_final
2022-01-03 08:23:36	ga_ls7e_ard_3-2-1_093078_2022-01-02_final
2022-01-03 08:24:00	ga_ls7e_ard_3-2-1_093079_2022-01-02_final
2022-01-03 08:24:24	ga_ls7e_ard_3-2-1_093080_2022-01-02_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years