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 08:55:23	ga_ls7e_ard_3-2-0_096086_2021-09-17_final
2021-09-20 10:17:44	ga_ls7e_ard_3-2-0_110076_2021-09-20_final
2021-09-20 10:20:31	ga_ls7e_ard_3-2-0_110083_2021-09-20_final
2021-09-25 08:54:57	ga_ls7e_ard_3-2-0_097071_2021-09-24_final
2021-09-25 10:39:01	ga_ls7e_ard_3-2-0_113084_2021-09-25_final
2021-09-27 08:44:48	ga_ls7e_ard_3-2-0_095077_2021-09-26_final
2021-09-28 09:24:46	ga_ls7e_ard_3-2-0_102069_2021-09-27_final
2021-09-29 10:08:44	ga_ls7e_ard_3-2-0_109071_2021-09-29_final
2021-10-03 08:09:35	ga_ls7e_ard_3-2-0_089083_2021-10-02_final
2021-10-03 09:43:41	ga_ls7e_ard_3-2-0_105071_2021-10-03_final
2021-10-08 08:25:18	ga_ls7e_ard_3-2-0_092077_2021-10-07_final
2021-10-08 10:02:58	ga_ls7e_ard_3-2-0_108074_2021-10-08_final
2021-10-09 09:06:28	ga_ls7e_ard_3-2-0_099072_2021-10-08_final
2021-10-13 08:45:47	ga_ls7e_ard_3-2-0_095083_2021-10-12_final
2021-10-22 10:14:05	ga_ls7e_ard_3-2-0_110074_2021-10-22_final
2021-10-23 09:18:46	ga_ls7e_ard_3-2-0_101075_2021-10-22_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-10-27 08:55:41	ga_ls7e_ard_3-2-0_097080_2021-10-26_final
2021-10-30 09:21:31	ga_ls7e_ard_3-2-0_102068_2021-10-29_final
2021-10-31 08:30:35	ga_ls7e_ard_3-2-0_093080_2021-10-30_final
2021-10-31 10:09:52	ga_ls7e_ard_3-2-0_109081_2021-10-31_final
2021-11-01 09:13:21	ga_ls7e_ard_3-2-0_100079_2021-10-31_final
2021-11-02 08:18:50	ga_ls7e_ard_3-2-0_091082_2021-11-01_final
2021-11-02 09:54:08	ga_ls7e_ard_3-2-0_107073_2021-11-02_final
2021-11-03 10:38:29	ga_ls7e_ard_3-2-0_114076_2021-11-03_final
2021-11-05 08:45:52	ga_ls7e_ard_3-2-0_096073_2021-11-04_final
2021-11-07 10:15:23	ga_ls7e_ard_3-2-0_110081_2021-11-07_final
2021-11-14 10:20:05	ga_ls7e_ard_3-2-1_111079_2021-11-14_final
2021-11-15 09:24:46	ga_ls7e_ard_3-2-1_102080_2021-11-14_final
2021-11-16 08:30:39	ga_ls7e_ard_3-2-1_093084_2021-11-15_final
2021-11-19 08:55:40	ga_ls7e_ard_3-2-1_098070_2021-11-18_final
2021-11-20 09:38:50	ga_ls7e_ard_3-2-1_105070_2021-11-20_final
2021-11-22 09:28:16	ga_ls7e_ard_3-2-1_103075_2021-11-21_final
2021-11-26 09:03:10	ga_ls7e_ard_3-2-1_099075_2021-11-25_final
2021-12-03 09:07:54	ga_ls7e_ard_3-2-1_100073_2021-12-02_final
2021-12-04 08:14:35	ga_ls7e_ard_3-2-1_091079_2021-12-03_final
2021-12-09 08:33:27	ga_ls7e_ard_3-2-1_094081_2021-12-08_final
2021-12-14 08:49:07	ga_ls7e_ard_3-2-1_097075_2021-12-13_final
2021-12-14 08:52:18	ga_ls7e_ard_3-2-1_097083_2021-12-13_final
2021-12-18 08:26:48	ga_ls7e_ard_3-2-1_093082_2021-12-17_final
2021-12-18 10:04:29	ga_ls7e_ard_3-2-1_109079_2021-12-18_final
2021-12-19 09:09:58	ga_ls7e_ard_3-2-1_100082_2021-12-18_final
2021-12-23 08:40:04	ga_ls7e_ard_3-2-1_096070_2021-12-22_final
2021-12-23 08:43:15	ga_ls7e_ard_3-2-1_096078_2021-12-22_final
2021-12-23 08:43:39	ga_ls7e_ard_3-2-1_096079_2021-12-22_final
2021-12-24 09:24:01	ga_ls7e_ard_3-2-1_103072_2021-12-23_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2021-12-30 10:27:13	ga_ls7e_ard_3-2-1_113077_2021-12-30_final
2022-01-01 08:38:10	ga_ls7e_ard_3-2-1_095083_2021-12-31_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-04 09:08:45	ga_ls7e_ard_3-2-1_100083_2022-01-03_final
2022-01-08 08:41:40	ga_ls7e_ard_3-2-1_096078_2022-01-07_final
2022-01-08 10:20:09	ga_ls7e_ard_3-2-1_112077_2022-01-08_final
2022-01-09 09:25:14	ga_ls7e_ard_3-2-1_103079_2022-01-08_final
2022-01-09 09:25:38	ga_ls7e_ard_3-2-1_103080_2022-01-08_final
2022-01-14 08:08:01	ga_ls7e_ard_3-2-1_090088_2022-01-13_final
2022-01-17 08:35:26	ga_ls7e_ard_3-2-1_095080_2022-01-16_final
2022-01-18 09:15:01	ga_ls7e_ard_3-2-1_102071_2022-01-17_final
2022-01-18 09:15:25	ga_ls7e_ard_3-2-1_102072_2022-01-17_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-24 10:19:25	ga_ls7e_ard_3-2-1_112079_2022-01-24_final
2022-02-04 08:20:55	ga_ls7e_ard_3-2-1_093079_2022-02-03_final
2022-02-04 08:21:19	ga_ls7e_ard_3-2-1_093080_2022-02-03_final
2022-02-04 08:22:06	ga_ls7e_ard_3-2-1_093082_2022-02-03_final
2022-02-07 08:52:18	ga_ls7e_ard_3-2-1_098081_2022-02-06_final
2022-02-10 09:22:29	ga_ls7e_ard_3-2-1_103080_2022-02-09_final
2022-02-11 08:25:58	ga_ls7e_ard_3-2-1_094078_2022-02-10_final
2022-02-11 08:28:46	ga_ls7e_ard_3-2-1_094085_2022-02-10_final
2022-02-15 09:39:18	ga_ls7e_ard_3-2-1_106077_2022-02-15_final
2022-02-16 10:21:16	ga_ls7e_ard_3-2-1_113074_2022-02-16_final
2022-02-16 10:22:04	ga_ls7e_ard_3-2-1_113076_2022-02-16_final
2022-02-19 09:13:24	ga_ls7e_ard_3-2-1_102075_2022-02-18_final
2022-02-20 08:20:29	ga_ls7e_ard_3-2-1_093082_2022-02-19_final
2022-02-20 09:57:46	ga_ls7e_ard_3-2-1_109078_2022-02-20_final
2022-02-25 08:36:57	ga_ls7e_ard_3-2-1_096078_2022-02-24_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-25 08:38:33	ga_ls7e_ard_3-2-1_096082_2022-02-24_final
2022-02-27 08:24:00	ga_ls7e_ard_3-2-1_094077_2022-02-26_final
2022-02-27 08:24:24	ga_ls7e_ard_3-2-1_094078_2022-02-26_final
2022-03-03 08:00:54	ga_ls7e_ard_3-2-1_090082_2022-03-02_final
2022-03-08 08:19:20	ga_ls7e_ard_3-2-1_093083_2022-03-07_final
2022-03-08 09:56:13	ga_ls7e_ard_3-2-1_109078_2022-03-08_final
2022-03-08 09:56:37	ga_ls7e_ard_3-2-1_109079_2022-03-08_final
2022-03-10 08:05:11	ga_ls7e_ard_3-2-1_091079_2022-03-09_final
2022-03-10 08:05:35	ga_ls7e_ard_3-2-1_091080_2022-03-09_final
2022-03-10 08:07:11	ga_ls7e_ard_3-2-1_091084_2022-03-09_final
2022-03-10 09:45:39	ga_ls7e_ard_3-2-1_107083_2022-03-10_final
2022-03-15 09:59:42	ga_ls7e_ard_3-2-1_110073_2022-03-15_final
2022-03-17 09:48:44	ga_ls7e_ard_3-2-1_108077_2022-03-17_final
2022-03-17 09:49:07	ga_ls7e_ard_3-2-1_108078_2022-03-17_final
2022-03-19 09:32:59	ga_ls7e_ard_3-2-1_106069_2022-03-19_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-24 09:55:51	ga_ls7e_ard_3-2-1_109081_2022-03-24_final
2022-03-26 08:06:49	ga_ls7e_ard_3-2-1_091087_2022-03-25_final
2022-03-27 08:43:36	ga_ls7e_ard_3-2-1_098071_2022-03-26_final
2022-03-28 09:29:33	ga_ls7e_ard_3-2-1_105078_2022-03-27_final
2022-03-31 08:20:53	ga_ls7e_ard_3-2-1_094077_2022-03-30_final
2022-03-31 09:59:46	ga_ls7e_ard_3-2-1_110077_2022-03-31_final
2022-04-02 08:09:56	ga_ls7e_ard_3-2-1_092081_2022-04-01_final
2022-04-06 09:19:18	ga_ls7e_ard_3-2-1_104070_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years