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
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
2019-02-19 09:34:20	ga_ls7e_ard_3-1-0_094073_2019-02-19_final
2019-02-19 09:34:44	ga_ls7e_ard_3-1-0_094074_2019-02-19_final
2019-02-19 09:35:08	ga_ls7e_ard_3-1-0_094075_2019-02-19_final
2019-02-19 09:35:32	ga_ls7e_ard_3-1-0_094076_2019-02-19_final
2019-02-21 09:24:19	ga_ls7e_ard_3-1-0_092079_2019-02-20_final
2019-02-21 09:24:42	ga_ls7e_ard_3-1-0_092080_2019-02-20_final
2019-02-21 09:25:06	ga_ls7e_ard_3-1-0_092081_2019-02-20_final
2019-02-21 09:25:30	ga_ls7e_ard_3-1-0_092082_2019-02-20_final
2019-02-21 09:25:54	ga_ls7e_ard_3-1-0_092083_2019-02-20_final
2019-02-21 09:26:18	ga_ls7e_ard_3-1-0_092084_2019-02-20_final
2019-02-21 09:26:42	ga_ls7e_ard_3-1-0_092085_2019-02-20_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
2019-03-25 09:23:17	ga_ls7e_ard_3-1-0_092079_2019-03-24_final
2019-03-27 09:14:26	ga_ls7e_ard_3-1-0_090088_2019-03-26_final
2019-03-27 09:14:50	ga_ls7e_ard_3-1-0_090089_2019-03-26_final
2019-03-27 09:15:14	ga_ls7e_ard_3-1-0_090090_2019-03-26_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
2019-05-14 09:12:41	ga_ls7e_ard_3-0-0_090088_2019-05-13_final
2019-05-14 09:13:05	ga_ls7e_ard_3-0-0_090089_2019-05-13_final
2019-05-14 09:13:29	ga_ls7e_ard_3-0-0_090090_2019-05-13_final
2021-06-27 08:30:30	ga_ls7e_ard_3-2-0_091083_2021-06-26_final
2021-06-27 08:31:18	ga_ls7e_ard_3-2-0_091085_2021-06-26_final
2021-06-27 08:31:42	ga_ls7e_ard_3-2-0_091086_2021-06-26_final
2021-06-27 08:32:06	ga_ls7e_ard_3-2-0_091087_2021-06-26_final
2021-06-27 08:32:30	ga_ls7e_ard_3-2-0_091088_2021-06-26_final
2021-06-27 08:32:54	ga_ls7e_ard_3-2-0_091089_2021-06-26_final
2021-07-04 08:34:30	ga_ls7e_ard_3-2-0_092079_2021-07-03_final
2021-07-04 08:34:54	ga_ls7e_ard_3-2-0_092080_2021-07-03_final
2021-07-04 08:35:17	ga_ls7e_ard_3-2-0_092081_2021-07-03_final
2021-07-04 08:35:41	ga_ls7e_ard_3-2-0_092082_2021-07-03_final
2021-07-04 08:36:05	ga_ls7e_ard_3-2-0_092083_2021-07-03_final
2021-07-04 08:36:29	ga_ls7e_ard_3-2-0_092084_2021-07-03_final
2021-07-04 08:36:53	ga_ls7e_ard_3-2-0_092085_2021-07-03_final
2021-07-11 08:38:29	ga_ls7e_ard_3-2-0_093075_2021-07-10_final
2021-07-11 08:38:53	ga_ls7e_ard_3-2-0_093076_2021-07-10_final
2021-07-11 08:39:17	ga_ls7e_ard_3-2-0_093077_2021-07-10_final
2021-07-11 08:39:41	ga_ls7e_ard_3-2-0_093078_2021-07-10_final
2021-07-11 08:40:05	ga_ls7e_ard_3-2-0_093079_2021-07-10_final
2021-07-11 08:40:29	ga_ls7e_ard_3-2-0_093080_2021-07-10_final
2021-07-11 08:40:53	ga_ls7e_ard_3-2-0_093081_2021-07-10_final
2021-07-13 08:29:09	ga_ls7e_ard_3-2-0_091083_2021-07-12_final
2021-07-13 08:29:33	ga_ls7e_ard_3-2-0_091084_2021-07-12_final
2021-07-13 08:29:57	ga_ls7e_ard_3-2-0_091085_2021-07-12_final
2021-07-13 08:30:21	ga_ls7e_ard_3-2-0_091086_2021-07-12_final
2021-07-13 08:30:45	ga_ls7e_ard_3-2-0_091087_2021-07-12_final
2021-07-13 08:31:08	ga_ls7e_ard_3-2-0_091088_2021-07-12_final
2021-07-13 08:31:32	ga_ls7e_ard_3-2-0_091089_2021-07-12_final
2021-11-18 08:17:42	ga_ls7e_ard_3-2-1_091083_2021-11-17_final
2021-11-18 08:18:06	ga_ls7e_ard_3-2-1_091084_2021-11-17_final
2021-11-18 08:18:30	ga_ls7e_ard_3-2-1_091085_2021-11-17_final
2021-11-18 08:18:54	ga_ls7e_ard_3-2-1_091086_2021-11-17_final
2021-11-18 08:19:18	ga_ls7e_ard_3-2-1_091087_2021-11-17_final
2021-11-18 08:19:42	ga_ls7e_ard_3-2-1_091088_2021-11-17_final
2021-11-23 08:31:45	ga_ls7e_ard_3-2-1_094073_2021-11-22_final
2021-11-23 08:32:09	ga_ls7e_ard_3-2-1_094074_2021-11-22_final
2021-11-23 08:32:33	ga_ls7e_ard_3-2-1_094075_2021-11-22_final
2021-11-23 08:32:57	ga_ls7e_ard_3-2-1_094076_2021-11-22_final
2021-11-30 08:36:53	ga_ls7e_ard_3-2-1_095072_2021-11-29_final
2021-12-11 08:20:06	ga_ls7e_ard_3-2-1_092079_2021-12-10_final
2021-12-11 08:20:30	ga_ls7e_ard_3-2-1_092080_2021-12-10_final
2021-12-11 08:20:54	ga_ls7e_ard_3-2-1_092081_2021-12-10_final
2021-12-11 08:21:18	ga_ls7e_ard_3-2-1_092082_2021-12-10_final
2021-12-11 08:21:42	ga_ls7e_ard_3-2-1_092083_2021-12-10_final
2021-12-11 08:22:06	ga_ls7e_ard_3-2-1_092084_2021-12-10_final
2021-12-11 08:22:30	ga_ls7e_ard_3-2-1_092085_2021-12-10_final
2021-12-13 08:11:08	ga_ls7e_ard_3-2-1_090088_2021-12-12_final
2021-12-13 08:11:32	ga_ls7e_ard_3-2-1_090089_2021-12-12_final
2021-12-13 08:11:56	ga_ls7e_ard_3-2-1_090090_2021-12-12_final
2021-12-18 08:24:01	ga_ls7e_ard_3-2-1_093075_2021-12-17_final
2021-12-18 08:24:25	ga_ls7e_ard_3-2-1_093076_2021-12-17_final
2021-12-18 08:24:48	ga_ls7e_ard_3-2-1_093077_2021-12-17_final
2021-12-18 08:25:12	ga_ls7e_ard_3-2-1_093078_2021-12-17_final
2021-12-18 08:25:36	ga_ls7e_ard_3-2-1_093079_2021-12-17_final
2021-12-18 08:26:00	ga_ls7e_ard_3-2-1_093080_2021-12-17_final
2021-12-18 08:26:24	ga_ls7e_ard_3-2-1_093081_2021-12-17_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

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