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 08:51:23	ga_ls7e_ard_3-2-0_096076_2021-09-17_final
2021-09-18 10:29:52	ga_ls7e_ard_3-2-0_112075_2021-09-18_final
2021-09-20 08:40:27	ga_ls7e_ard_3-2-0_094080_2021-09-19_final
2021-11-12 10:31:03	ga_ls7e_ard_3-2-1_113075_2021-11-12_final
2021-11-14 10:22:05	ga_ls7e_ard_3-2-1_111084_2021-11-14_final
2021-11-15 09:23:10	ga_ls7e_ard_3-2-1_102076_2021-11-14_final
2021-11-15 09:23:34	ga_ls7e_ard_3-2-1_102077_2021-11-14_final
2021-11-15 09:23:58	ga_ls7e_ard_3-2-1_102078_2021-11-14_final
2021-11-19 10:38:56	ga_ls7e_ard_3-2-1_114081_2021-11-19_final
2021-11-26 10:43:14	ga_ls7e_ard_3-2-1_115078_2021-11-26_final
2021-11-29 09:35:23	ga_ls7e_ard_3-2-1_104079_2021-11-29_final
2021-12-06 09:40:31	ga_ls7e_ard_3-2-1_105078_2021-12-06_final
2021-12-07 08:46:48	ga_ls7e_ard_3-2-1_096083_2021-12-06_final
2021-12-09 08:31:03	ga_ls7e_ard_3-2-1_094075_2021-12-08_final
2021-12-09 08:32:15	ga_ls7e_ard_3-2-1_094078_2021-12-08_final
2021-12-10 09:17:24	ga_ls7e_ard_3-2-1_101083_2021-12-09_final
2021-12-12 09:02:52	ga_ls7e_ard_3-2-1_099078_2021-12-11_final
2021-12-12 09:04:04	ga_ls7e_ard_3-2-1_099081_2021-12-11_final
2021-12-13 09:43:14	ga_ls7e_ard_3-2-1_106071_2021-12-13_final
2021-12-18 10:04:53	ga_ls7e_ard_3-2-1_109080_2021-12-18_final
2021-12-23 08:42:28	ga_ls7e_ard_3-2-1_096076_2021-12-22_final
2021-12-23 08:42:51	ga_ls7e_ard_3-2-1_096077_2021-12-22_final
2021-12-23 10:22:08	ga_ls7e_ard_3-2-1_112078_2021-12-23_final
2021-12-30 10:27:37	ga_ls7e_ard_3-2-1_113078_2021-12-30_final
2022-01-02 09:16:56	ga_ls7e_ard_3-2-1_102072_2022-01-01_final
2022-01-03 08:26:48	ga_ls7e_ard_3-2-1_093086_2022-01-02_final
2022-01-04 09:08:21	ga_ls7e_ard_3-2-1_100082_2022-01-03_final
2022-01-08 08:40:28	ga_ls7e_ard_3-2-1_096075_2022-01-07_final
2022-01-08 10:20:56	ga_ls7e_ard_3-2-1_112079_2022-01-08_final
2022-01-10 08:28:19	ga_ls7e_ard_3-2-1_094076_2022-01-09_final
2022-01-10 08:30:19	ga_ls7e_ard_3-2-1_094081_2022-01-09_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-11 09:11:29	ga_ls7e_ard_3-2-1_101076_2022-01-10_final
2022-01-14 09:39:19	ga_ls7e_ard_3-2-1_106069_2022-01-14_final
2022-01-15 08:48:47	ga_ls7e_ard_3-2-1_097082_2022-01-14_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-17 08:37:50	ga_ls7e_ard_3-2-1_095086_2022-01-16_final
2022-01-19 09:58:34	ga_ls7e_ard_3-2-1_109072_2022-01-19_final
2022-01-26 10:07:16	ga_ls7e_ard_3-2-1_110080_2022-01-26_final
2022-01-27 09:09:57	ga_ls7e_ard_3-2-1_101076_2022-01-26_final
2022-01-29 08:59:47	ga_ls7e_ard_3-2-1_099082_2022-01-28_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-30 08:06:52	ga_ls7e_ard_3-2-1_090089_2022-01-29_final
2022-02-02 08:36:40	ga_ls7e_ard_3-2-1_095087_2022-02-01_final
2022-02-04 08:20:55	ga_ls7e_ard_3-2-1_093079_2022-02-03_final
2022-02-06 09:48:49	ga_ls7e_ard_3-2-1_107083_2022-02-06_final
2022-02-10 09:20:30	ga_ls7e_ard_3-2-1_103075_2022-02-09_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-12 09:06:44	ga_ls7e_ard_3-2-1_101072_2022-02-11_final
2022-02-12 09:10:19	ga_ls7e_ard_3-2-1_101081_2022-02-11_final
2022-02-13 09:52:17	ga_ls7e_ard_3-2-1_108078_2022-02-13_final
2022-02-14 08:54:09	ga_ls7e_ard_3-2-1_099072_2022-02-13_final
2022-02-14 08:56:57	ga_ls7e_ard_3-2-1_099079_2022-02-13_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-18 08:31:02	ga_ls7e_ard_3-2-1_095077_2022-02-17_final
2022-02-18 08:31:50	ga_ls7e_ard_3-2-1_095079_2022-02-17_final
2022-02-19 09:12:13	ga_ls7e_ard_3-2-1_102072_2022-02-18_final
2022-02-19 09:14:36	ga_ls7e_ard_3-2-1_102078_2022-02-18_final
2022-02-20 08:18:53	ga_ls7e_ard_3-2-1_093078_2022-02-19_final
2022-02-20 08:21:17	ga_ls7e_ard_3-2-1_093084_2022-02-19_final
2022-02-21 09:01:15	ga_ls7e_ard_3-2-1_100076_2022-02-20_final
2022-02-21 09:02:27	ga_ls7e_ard_3-2-1_100079_2022-02-20_final
2022-02-22 09:45:13	ga_ls7e_ard_3-2-1_107078_2022-02-22_final
2022-02-24 09:33:28	ga_ls7e_ard_3-2-1_105080_2022-02-24_final
2022-02-25 08:36:33	ga_ls7e_ard_3-2-1_096077_2022-02-24_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-25 08:40:09	ga_ls7e_ard_3-2-1_096086_2022-02-24_final
2022-02-27 10:04:53	ga_ls7e_ard_3-2-1_110082_2022-02-27_final
2022-03-02 08:56:37	ga_ls7e_ard_3-2-1_099082_2022-03-01_final
2022-03-05 09:22:02	ga_ls7e_ard_3-2-1_104069_2022-03-04_final
2022-03-08 09:57:01	ga_ls7e_ard_3-2-1_109080_2022-03-08_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-11 08:49:08	ga_ls7e_ard_3-2-1_098081_2022-03-10_final
2022-03-12 07:53:25	ga_ls7e_ard_3-2-1_089081_2022-03-11_final
2022-03-12 09:30:42	ga_ls7e_ard_3-2-1_105077_2022-03-12_final
2022-03-12 09:31:54	ga_ls7e_ard_3-2-1_105080_2022-03-12_final
2022-03-15 08:22:01	ga_ls7e_ard_3-2-1_094076_2022-03-14_final
2022-03-15 10:01:42	ga_ls7e_ard_3-2-1_110078_2022-03-15_final
2022-03-17 08:10:39	ga_ls7e_ard_3-2-1_092079_2022-03-16_final
2022-03-17 09:48:44	ga_ls7e_ard_3-2-1_108077_2022-03-17_final
2022-03-18 08:51:25	ga_ls7e_ard_3-2-1_099073_2022-03-17_final
2022-03-18 08:52:36	ga_ls7e_ard_3-2-1_099076_2022-03-17_final
2022-03-20 08:40:52	ga_ls7e_ard_3-2-1_097078_2022-03-19_final
2022-03-21 09:20:50	ga_ls7e_ard_3-2-1_104070_2022-03-20_final
2022-03-21 09:24:02	ga_ls7e_ard_3-2-1_104078_2022-03-20_final
2022-03-21 09:25:13	ga_ls7e_ard_3-2-1_104081_2022-03-20_final
2022-03-23 09:11:29	ga_ls7e_ard_3-2-1_102078_2022-03-22_final
2022-03-24 08:16:34	ga_ls7e_ard_3-2-1_093080_2022-03-23_final
2022-03-24 09:55:03	ga_ls7e_ard_3-2-1_109079_2022-03-24_final
2022-03-25 08:57:44	ga_ls7e_ard_3-2-1_100075_2022-03-24_final
2022-03-29 08:31:51	ga_ls7e_ard_3-2-1_096073_2022-03-28_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_final
2022-03-30 09:15:00	ga_ls7e_ard_3-2-1_103073_2022-03-29_final
2022-03-30 09:15:24	ga_ls7e_ard_3-2-1_103074_2022-03-29_final
2022-03-31 08:20:05	ga_ls7e_ard_3-2-1_094075_2022-03-30_final
2022-04-01 09:05:15	ga_ls7e_ard_3-2-1_101080_2022-03-31_final
2022-04-02 08:10:20	ga_ls7e_ard_3-2-1_092082_2022-04-01_final
2022-04-03 08:50:41	ga_ls7e_ard_3-2-1_099075_2022-04-02_final
2022-04-05 08:40:08	ga_ls7e_ard_3-2-1_097080_2022-04-04_final
2022-04-05 10:17:24	ga_ls7e_ard_3-2-1_113076_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