Search ga_ls8c_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
2019-07-12 09:47:32	ga_ls8c_ard_3-1-0_095075_2019-07-12_final
2020-02-21 09:47:37	ga_ls8c_ard_3-1-0_095075_2020-02-21_final
2022-03-30 09:46:08	ga_ls8c_ard_3-2-1_095072_2022-03-30_final
2022-03-31 10:32:12	ga_ls8c_ard_3-2-1_102079_2022-03-31_final
2022-04-01 11:12:40	ga_ls8c_ard_3-2-1_109072_2022-04-01_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-03 10:59:54	ga_ls8c_ard_3-2-1_107071_2022-04-03_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-06 11:31:38	ga_ls8c_ard_3-2-1_112073_2022-04-06_final
2022-04-07 10:34:02	ga_ls8c_ard_3-2-1_103068_2022-04-07_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-09 10:24:53	ga_ls8c_ard_3-2-1_101076_2022-04-09_final
2022-04-09 10:27:17	ga_ls8c_ard_3-2-1_101082_2022-04-09_final
2022-04-12 10:52:37	ga_ls8c_ard_3-2-1_106068_2022-04-12_final
2022-04-13 10:01:23	ga_ls8c_ard_3-2-1_097079_2022-04-13_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-15 09:47:50	ga_ls8c_ard_3-2-1_095076_2022-04-15_final
2022-04-16 10:29:06	ga_ls8c_ard_3-2-1_102071_2022-04-16_final
2022-04-16 10:31:54	ga_ls8c_ard_3-2-1_102078_2022-04-16_final
2022-04-16 10:32:18	ga_ls8c_ard_3-2-1_102079_2022-04-16_final
2022-04-16 10:33:30	ga_ls8c_ard_3-2-1_102082_2022-04-16_final
2022-04-17 09:39:04	ga_ls8c_ard_3-2-1_093085_2022-04-17_final
2022-04-17 11:14:21	ga_ls8c_ard_3-2-1_109076_2022-04-17_final
2022-04-17 11:16:45	ga_ls8c_ard_3-2-1_109082_2022-04-17_final
2022-04-18 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-04-18_final
2022-04-18 10:20:44	ga_ls8c_ard_3-2-1_100081_2022-04-18_final
2022-04-19 09:23:54	ga_ls8c_ard_3-2-1_091078_2022-04-18_final
2022-04-19 09:24:18	ga_ls8c_ard_3-2-1_091079_2022-04-18_final
2022-04-19 11:01:11	ga_ls8c_ard_3-2-1_107074_2022-04-19_final
2022-04-21 09:11:32	ga_ls8c_ard_3-2-1_089078_2022-04-20_final
2022-04-22 11:34:52	ga_ls8c_ard_3-2-1_112081_2022-04-22_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-27 10:14:53	ga_ls8c_ard_3-2-1_099082_2022-04-27_final
2022-04-28 09:18:27	ga_ls8c_ard_3-2-1_090080_2022-04-27_final
2022-04-28 09:19:15	ga_ls8c_ard_3-2-1_090082_2022-04-27_final
2022-04-28 10:54:56	ga_ls8c_ard_3-2-1_106074_2022-04-28_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-04-30 10:41:48	ga_ls8c_ard_3-2-1_104072_2022-04-30_final
2022-05-01 09:47:47	ga_ls8c_ard_3-2-1_095076_2022-05-01_final
2022-05-01 09:50:35	ga_ls8c_ard_3-2-1_095083_2022-05-01_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-02 10:28:16	ga_ls8c_ard_3-2-1_102069_2022-05-02_final
2022-05-02 10:29:04	ga_ls8c_ard_3-2-1_102071_2022-05-02_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-03 11:13:56	ga_ls8c_ard_3-2-1_109075_2022-05-03_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-05 09:25:31	ga_ls8c_ard_3-2-1_091082_2022-05-04_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-05 11:02:00	ga_ls8c_ard_3-2-1_107076_2022-05-05_final
2022-05-06 10:09:59	ga_ls8c_ard_3-2-1_098085_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2022-05-07 10:46:28	ga_ls8c_ard_3-2-1_105068_2022-05-07_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-08 09:53:39	ga_ls8c_ard_3-2-1_096075_2022-05-08_final
2022-05-08 09:56:51	ga_ls8c_ard_3-2-1_096083_2022-05-08_final
2022-05-09 10:35:20	ga_ls8c_ard_3-2-1_103071_2022-05-09_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-14 10:54:18	ga_ls8c_ard_3-2-1_106072_2022-05-14_final
2022-05-15 11:38:46	ga_ls8c_ard_3-2-1_113075_2022-05-15_final
2022-05-15 11:39:58	ga_ls8c_ard_3-2-1_113078_2022-05-15_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-16 10:41:10	ga_ls8c_ard_3-2-1_104070_2022-05-16_final
2022-05-16 10:41:34	ga_ls8c_ard_3-2-1_104071_2022-05-16_final
2022-05-17 09:50:44	ga_ls8c_ard_3-2-1_095083_2022-05-17_final
2022-05-18 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-05-18_final
2022-05-19 09:37:35	ga_ls8c_ard_3-2-1_093081_2022-05-19_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-19 09:39:58	ga_ls8c_ard_3-2-1_093087_2022-05-19_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-21 11:04:30	ga_ls8c_ard_3-2-1_107082_2022-05-21_final
2022-05-24 09:58:06	ga_ls8c_ard_3-2-1_096086_2022-05-24_final
2022-05-24 11:32:12	ga_ls8c_ard_3-2-1_112074_2022-05-24_final
2022-05-25 10:34:35	ga_ls8c_ard_3-2-1_103069_2022-05-25_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-05-25 10:35:23	ga_ls8c_ard_3-2-1_103071_2022-05-25_final
2022-05-25 10:36:11	ga_ls8c_ard_3-2-1_103073_2022-05-25_final
2022-05-30 10:57:56	ga_ls8c_ard_3-2-1_106081_2022-05-30_final
2022-06-01 10:41:13	ga_ls8c_ard_3-2-1_104070_2022-06-01_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-02 11:24:54	ga_ls8c_ard_3-2-1_111071_2022-06-02_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-04 11:16:57	ga_ls8c_ard_3-2-1_109082_2022-06-04_final
2022-06-05 10:17:45	ga_ls8c_ard_3-2-1_100073_2022-06-05_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-08 10:46:18	ga_ls8c_ard_3-2-1_105067_2022-06-08_final
2022-06-13 09:30:00	ga_ls8c_ard_3-2-1_092077_2022-06-13_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-16 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-06-16_final
2022-06-18 09:50:59	ga_ls8c_ard_3-2-1_095083_2022-06-18_final
2022-06-21 10:18:43	ga_ls8c_ard_3-2-1_100075_2022-06-21_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years