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
2021-09-24 09:53:03	ga_ls7e_ard_3-2-0_106077_2021-09-24_final
2021-09-25 08:58:56	ga_ls7e_ard_3-2-0_097081_2021-09-24_final
2021-09-27 08:42:48	ga_ls7e_ard_3-2-0_095072_2021-09-26_final
2021-09-27 08:43:36	ga_ls7e_ard_3-2-0_095074_2021-09-26_final
2021-09-30 09:13:26	ga_ls7e_ard_3-2-0_100072_2021-09-29_final
2021-10-08 10:05:22	ga_ls7e_ard_3-2-0_108080_2021-10-08_final
2021-10-14 09:25:46	ga_ls7e_ard_3-2-0_102075_2021-10-13_final
2021-10-17 08:19:55	ga_ls7e_ard_3-2-0_091081_2021-10-16_final
2021-10-18 08:58:17	ga_ls7e_ard_3-2-0_098069_2021-10-17_final
2021-10-18 09:03:29	ga_ls7e_ard_3-2-0_098082_2021-10-17_final
2021-10-19 08:08:10	ga_ls7e_ard_3-2-0_089083_2021-10-18_final
2021-10-20 08:47:21	ga_ls7e_ard_3-2-0_096073_2021-10-19_final
2021-10-20 08:48:33	ga_ls7e_ard_3-2-0_096076_2021-10-19_final
2021-10-20 10:28:13	ga_ls7e_ard_3-2-0_112078_2021-10-20_final
2021-10-20 10:29:01	ga_ls7e_ard_3-2-0_112080_2021-10-20_final
2021-10-22 08:34:48	ga_ls7e_ard_3-2-0_094073_2021-10-21_final
2021-10-22 10:16:52	ga_ls7e_ard_3-2-0_110081_2021-10-22_final
2021-10-24 08:23:52	ga_ls7e_ard_3-2-0_092077_2021-10-23_final
2021-10-24 09:59:57	ga_ls7e_ard_3-2-0_108070_2021-10-24_final
2021-10-24 10:01:08	ga_ls7e_ard_3-2-0_108073_2021-10-24_final
2021-10-24 10:02:20	ga_ls7e_ard_3-2-0_108076_2021-10-24_final
2021-10-24 10:03:32	ga_ls7e_ard_3-2-0_108079_2021-10-24_final
2021-10-27 10:35:21	ga_ls7e_ard_3-2-0_113082_2021-10-27_final
2021-10-30 09:21:55	ga_ls7e_ard_3-2-0_102069_2021-10-29_final
2021-11-01 09:12:10	ga_ls7e_ard_3-2-0_100076_2021-10-31_final
2021-11-02 09:53:20	ga_ls7e_ard_3-2-0_107071_2021-11-02_final
2021-11-02 09:53:44	ga_ls7e_ard_3-2-0_107072_2021-11-02_final
2021-11-04 09:40:23	ga_ls7e_ard_3-2-0_105070_2021-11-04_final
2021-11-05 08:45:04	ga_ls7e_ard_3-2-0_096071_2021-11-04_final
2021-11-05 08:47:04	ga_ls7e_ard_3-2-0_096076_2021-11-04_final
2021-11-05 08:48:40	ga_ls7e_ard_3-2-0_096080_2021-11-04_final
2021-11-06 09:28:14	ga_ls7e_ard_3-2-0_103071_2021-11-05_final
2021-11-06 09:28:38	ga_ls7e_ard_3-2-0_103072_2021-11-05_final
2021-11-09 08:25:57	ga_ls7e_ard_3-2-0_092086_2021-11-08_final
2021-11-14 08:40:49	ga_ls7e_ard_3-2-1_095078_2021-11-13_final
2021-11-16 08:29:03	ga_ls7e_ard_3-2-1_093080_2021-11-15_final
2021-11-17 09:09:49	ga_ls7e_ard_3-2-1_100074_2021-11-16_final
2021-11-17 09:13:01	ga_ls7e_ard_3-2-1_100082_2021-11-16_final
2021-11-23 10:13:01	ga_ls7e_ard_3-2-1_110079_2021-11-23_final
2021-11-25 10:01:16	ga_ls7e_ard_3-2-1_108081_2021-11-25_final
2021-11-28 08:54:13	ga_ls7e_ard_3-2-1_097084_2021-11-27_final
2021-11-29 09:32:12	ga_ls7e_ard_3-2-1_104071_2021-11-29_final
2021-12-02 08:27:32	ga_ls7e_ard_3-2-1_093080_2021-12-01_final
2021-12-02 10:04:49	ga_ls7e_ard_3-2-1_109076_2021-12-02_final
2021-12-02 10:06:48	ga_ls7e_ard_3-2-1_109081_2021-12-02_final
2021-12-03 09:10:42	ga_ls7e_ard_3-2-1_100080_2021-12-02_final
2021-12-09 08:31:03	ga_ls7e_ard_3-2-1_094075_2021-12-08_final
2021-12-09 08:33:03	ga_ls7e_ard_3-2-1_094080_2021-12-08_final
2021-12-11 08:20:54	ga_ls7e_ard_3-2-1_092081_2021-12-10_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-18 10:05:17	ga_ls7e_ard_3-2-1_109081_2021-12-18_final
2021-12-20 08:13:27	ga_ls7e_ard_3-2-1_091080_2021-12-19_final
2021-12-22 09:37:47	ga_ls7e_ard_3-2-1_105075_2021-12-22_final
2021-12-23 08:44:27	ga_ls7e_ard_3-2-1_096081_2021-12-22_final
2021-12-25 10:09:58	ga_ls7e_ard_3-2-1_110079_2021-12-25_final
2022-01-03 10:02:29	ga_ls7e_ard_3-2-1_109078_2022-01-03_final
2022-01-05 08:13:26	ga_ls7e_ard_3-2-1_091084_2022-01-04_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-17 08:35:50	ga_ls7e_ard_3-2-1_095081_2022-01-16_final
2022-01-18 09:17:00	ga_ls7e_ard_3-2-1_102076_2022-01-17_final
2022-01-19 08:20:54	ga_ls7e_ard_3-2-1_093075_2022-01-18_final
2022-01-19 10:02:10	ga_ls7e_ard_3-2-1_109081_2022-01-19_final
2022-01-23 09:32:40	ga_ls7e_ard_3-2-1_105070_2022-01-23_final
2022-01-26 10:06:52	ga_ls7e_ard_3-2-1_110079_2022-01-26_final
2022-01-29 09:00:11	ga_ls7e_ard_3-2-1_099083_2022-01-28_final
2022-02-02 08:35:28	ga_ls7e_ard_3-2-1_095084_2022-02-01_final
2022-02-04 08:20:07	ga_ls7e_ard_3-2-1_093077_2022-02-03_final
2022-02-04 10:00:59	ga_ls7e_ard_3-2-1_109082_2022-02-04_final
2022-02-06 08:09:57	ga_ls7e_ard_3-2-1_091083_2022-02-05_final
2022-02-11 08:29:34	ga_ls7e_ard_3-2-1_094087_2022-02-10_final
2022-02-13 09:52:17	ga_ls7e_ard_3-2-1_108078_2022-02-13_final
2022-02-13 09:54:40	ga_ls7e_ard_3-2-1_108084_2022-02-13_final
2022-02-15 08:02:01	ga_ls7e_ard_3-2-1_090081_2022-02-14_final
2022-02-20 08:20:05	ga_ls7e_ard_3-2-1_093081_2022-02-19_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-22 09:42:26	ga_ls7e_ard_3-2-1_107071_2022-02-22_final
2022-02-25 08:37:21	ga_ls7e_ard_3-2-1_096079_2022-02-24_final
2022-02-26 09:18:31	ga_ls7e_ard_3-2-1_103074_2022-02-25_final
2022-03-01 08:11:27	ga_ls7e_ard_3-2-1_092077_2022-02-28_final
2022-03-01 09:50:44	ga_ls7e_ard_3-2-1_108078_2022-03-01_final
2022-03-02 08:56:37	ga_ls7e_ard_3-2-1_099082_2022-03-01_final
2022-03-03 08:00:30	ga_ls7e_ard_3-2-1_090081_2022-03-02_final
2022-03-03 08:03:17	ga_ls7e_ard_3-2-1_090088_2022-03-02_final
2022-03-12 09:31:06	ga_ls7e_ard_3-2-1_105078_2022-03-12_final
2022-03-13 08:35:23	ga_ls7e_ard_3-2-1_096078_2022-03-12_final
2022-03-13 08:38:10	ga_ls7e_ard_3-2-1_096085_2022-03-12_final
2022-03-13 10:12:40	ga_ls7e_ard_3-2-1_112074_2022-03-13_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_final
2022-03-13 10:16:15	ga_ls7e_ard_3-2-1_112083_2022-03-13_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-15 10:00:30	ga_ls7e_ard_3-2-1_110075_2022-03-15_final
2022-03-19 07:58:30	ga_ls7e_ard_3-2-1_090080_2022-03-18_final
2022-03-20 08:38:04	ga_ls7e_ard_3-2-1_097071_2022-03-19_final
2022-03-20 08:42:27	ga_ls7e_ard_3-2-1_097082_2022-03-19_final
2022-03-23 09:10:17	ga_ls7e_ard_3-2-1_102075_2022-03-22_final
2022-03-24 08:18:34	ga_ls7e_ard_3-2-1_093085_2022-03-23_final
2022-03-24 09:55:03	ga_ls7e_ard_3-2-1_109079_2022-03-24_final
2022-03-28 09:28:45	ga_ls7e_ard_3-2-1_105076_2022-03-27_final
2022-03-29 08:36:14	ga_ls7e_ard_3-2-1_096084_2022-03-28_final
2022-03-31 08:22:29	ga_ls7e_ard_3-2-1_094081_2022-03-30_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