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
2021-03-25 10:04:27	ga_ls7e_ard_3-2-0_105082_2021-03-25_final
2021-09-18 08:52:11	ga_ls7e_ard_3-2-0_096078_2021-09-17_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-10-25 09:05:26	ga_ls7e_ard_3-2-0_099073_2021-10-24_final
2021-10-26 08:16:06	ga_ls7e_ard_3-2-0_090089_2021-10-25_final
2021-10-26 09:50:12	ga_ls7e_ard_3-2-0_106077_2021-10-26_final
2021-10-26 09:51:23	ga_ls7e_ard_3-2-0_106080_2021-10-26_final
2021-12-18 10:04:53	ga_ls7e_ard_3-2-1_109080_2021-12-18_final
2021-12-19 09:09:10	ga_ls7e_ard_3-2-1_100080_2021-12-18_final
2021-12-23 10:20:32	ga_ls7e_ard_3-2-1_112074_2021-12-23_final
2021-12-27 09:58:13	ga_ls7e_ard_3-2-1_108081_2021-12-27_final
2022-01-01 08:34:10	ga_ls7e_ard_3-2-1_095073_2021-12-31_final
2022-01-01 08:36:58	ga_ls7e_ard_3-2-1_095080_2021-12-31_final
2022-01-01 10:17:03	ga_ls7e_ard_3-2-1_111083_2022-01-01_final
2022-01-03 08:25:12	ga_ls7e_ard_3-2-1_093082_2022-01-02_final
2022-01-03 08:26:00	ga_ls7e_ard_3-2-1_093084_2022-01-02_final
2022-01-03 08:26:24	ga_ls7e_ard_3-2-1_093085_2022-01-02_final
2022-01-03 08:26:48	ga_ls7e_ard_3-2-1_093086_2022-01-02_final
2022-01-04 09:05:34	ga_ls7e_ard_3-2-1_100075_2022-01-03_final
2022-01-06 10:31:53	ga_ls7e_ard_3-2-1_114075_2022-01-06_final
2022-01-08 08:43:16	ga_ls7e_ard_3-2-1_096082_2022-01-07_final
2022-01-09 09:21:14	ga_ls7e_ard_3-2-1_103069_2022-01-08_final
2022-01-09 09:22:26	ga_ls7e_ard_3-2-1_103072_2022-01-08_final
2022-01-10 08:29:55	ga_ls7e_ard_3-2-1_094080_2022-01-09_final
2022-01-10 08:31:55	ga_ls7e_ard_3-2-1_094085_2022-01-09_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-11 09:10:41	ga_ls7e_ard_3-2-1_101074_2022-01-10_final
2022-01-12 08:18:58	ga_ls7e_ard_3-2-1_092084_2022-01-11_final
2022-01-13 09:01:44	ga_ls7e_ard_3-2-1_099083_2022-01-12_final
2022-01-14 09:42:30	ga_ls7e_ard_3-2-1_106077_2022-01-14_final
2022-01-14 09:43:18	ga_ls7e_ard_3-2-1_106079_2022-01-14_final
2022-01-14 09:43:42	ga_ls7e_ard_3-2-1_106080_2022-01-14_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-18 09:17:48	ga_ls7e_ard_3-2-1_102078_2022-01-17_final
2022-01-19 09:58:58	ga_ls7e_ard_3-2-1_109073_2022-01-19_final
2022-01-21 08:10:20	ga_ls7e_ard_3-2-1_091080_2022-01-20_final
2022-01-21 08:11:56	ga_ls7e_ard_3-2-1_091084_2022-01-20_final
2022-01-22 08:48:43	ga_ls7e_ard_3-2-1_098068_2022-01-21_final
2022-01-22 08:49:54	ga_ls7e_ard_3-2-1_098071_2022-01-21_final
2022-01-22 10:30:23	ga_ls7e_ard_3-2-1_114075_2022-01-22_final
2022-01-23 07:56:59	ga_ls7e_ard_3-2-1_089078_2022-01-22_final
2022-01-24 08:37:21	ga_ls7e_ard_3-2-1_096071_2022-01-23_final
2022-01-26 08:31:11	ga_ls7e_ard_3-2-1_094087_2022-01-25_final
2022-01-29 08:57:00	ga_ls7e_ard_3-2-1_099075_2022-01-28_final
2022-01-31 08:45:38	ga_ls7e_ard_3-2-1_097078_2022-01-30_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-01-31 10:23:43	ga_ls7e_ard_3-2-1_113076_2022-01-31_final
2022-02-01 09:24:48	ga_ls7e_ard_3-2-1_104068_2022-01-31_final
2022-02-06 08:11:56	ga_ls7e_ard_3-2-1_091088_2022-02-05_final
2022-02-11 08:27:58	ga_ls7e_ard_3-2-1_094083_2022-02-10_final
2022-02-11 08:28:46	ga_ls7e_ard_3-2-1_094085_2022-02-10_final
2022-02-13 09:49:29	ga_ls7e_ard_3-2-1_108071_2022-02-13_final
2022-02-15 08:00:50	ga_ls7e_ard_3-2-1_090078_2022-02-14_final
2022-02-15 09:36:31	ga_ls7e_ard_3-2-1_106070_2022-02-15_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-18 08:30:14	ga_ls7e_ard_3-2-1_095075_2022-02-17_final
2022-02-18 08:32:14	ga_ls7e_ard_3-2-1_095080_2022-02-17_final
2022-02-18 10:11:31	ga_ls7e_ard_3-2-1_111081_2022-02-18_final
2022-02-18 10:11:55	ga_ls7e_ard_3-2-1_111082_2022-02-18_final
2022-02-19 09:13:00	ga_ls7e_ard_3-2-1_102074_2022-02-18_final
2022-02-20 08:20:53	ga_ls7e_ard_3-2-1_093083_2022-02-19_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-22 08:07:56	ga_ls7e_ard_3-2-1_091082_2022-02-21_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-22 09:47:37	ga_ls7e_ard_3-2-1_107084_2022-02-22_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-02-25 08:38:09	ga_ls7e_ard_3-2-1_096081_2022-02-24_final
2022-02-25 08:38:33	ga_ls7e_ard_3-2-1_096082_2022-02-24_final
2022-02-26 09:20:31	ga_ls7e_ard_3-2-1_103079_2022-02-25_final
2022-02-27 10:04:05	ga_ls7e_ard_3-2-1_110080_2022-02-27_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-02-28 09:08:22	ga_ls7e_ard_3-2-1_101080_2022-02-27_final
2022-03-03 09:37:47	ga_ls7e_ard_3-2-1_106077_2022-03-03_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-07 09:10:16	ga_ls7e_ard_3-2-1_102071_2022-03-06_final
2022-03-08 08:19:20	ga_ls7e_ard_3-2-1_093083_2022-03-07_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-10 09:42:04	ga_ls7e_ard_3-2-1_107074_2022-03-10_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-12 09:29:54	ga_ls7e_ard_3-2-1_105075_2022-03-11_final
2022-03-14 09:18:08	ga_ls7e_ard_3-2-1_103077_2022-03-13_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-20 10:20:32	ga_ls7e_ard_3-2-1_113080_2022-03-20_final
2022-03-23 09:08:41	ga_ls7e_ard_3-2-1_102071_2022-03-22_final
2022-03-23 09:10:41	ga_ls7e_ard_3-2-1_102076_2022-03-22_final
2022-03-24 08:14:10	ga_ls7e_ard_3-2-1_093074_2022-03-23_final
2022-03-24 08:14:58	ga_ls7e_ard_3-2-1_093076_2022-03-23_final
2022-03-25 08:57:20	ga_ls7e_ard_3-2-1_100074_2022-03-24_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-27 10:26:28	ga_ls7e_ard_3-2-1_114081_2022-03-27_final
2022-03-30 09:14:12	ga_ls7e_ard_3-2-1_103071_2022-03-29_final
2022-03-31 08:20:05	ga_ls7e_ard_3-2-1_094075_2022-03-30_final
2022-04-01 09:03:15	ga_ls7e_ard_3-2-1_101075_2022-03-31_final
2022-04-01 09:03:39	ga_ls7e_ard_3-2-1_101076_2022-03-31_final
2022-04-01 09:06:27	ga_ls7e_ard_3-2-1_101083_2022-03-31_final
2022-04-02 09:46:25	ga_ls7e_ard_3-2-1_108075_2022-04-02_final
2022-04-04 07:58:58	ga_ls7e_ard_3-2-1_090085_2022-04-03_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