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
2022-07-19 10:43:53	ga_ls8c_ard_3-2-1_104076_2022-07-19_final
2022-07-19 10:44:41	ga_ls8c_ard_3-2-1_104078_2022-07-19_final
2022-07-19 10:45:29	ga_ls8c_ard_3-2-1_104080_2022-07-19_final
2022-07-20 09:50:41	ga_ls8c_ard_3-2-1_095082_2022-07-20_final
2022-07-20 09:51:05	ga_ls8c_ard_3-2-1_095083_2022-07-20_final
2022-07-20 11:23:58	ga_ls8c_ard_3-2-1_111068_2022-07-20_final
2022-07-20 11:25:10	ga_ls8c_ard_3-2-1_111071_2022-07-20_final
2022-07-20 11:29:34	ga_ls8c_ard_3-2-1_111082_2022-07-20_final
2022-07-20 11:30:22	ga_ls8c_ard_3-2-1_111084_2022-07-20_final
2022-07-21 10:29:58	ga_ls8c_ard_3-2-1_102072_2022-07-21_final
2022-07-21 10:30:22	ga_ls8c_ard_3-2-1_102073_2022-07-21_final
2022-07-21 10:30:46	ga_ls8c_ard_3-2-1_102074_2022-07-21_final
2022-07-21 10:31:10	ga_ls8c_ard_3-2-1_102075_2022-07-21_final
2022-07-22 09:33:57	ga_ls8c_ard_3-2-1_093071_2022-07-22_final
2022-07-22 09:34:21	ga_ls8c_ard_3-2-1_093072_2022-07-22_final
2022-07-22 09:36:45	ga_ls8c_ard_3-2-1_093078_2022-07-22_final
2022-07-22 11:14:02	ga_ls8c_ard_3-2-1_109074_2022-07-22_final
2022-07-22 11:14:26	ga_ls8c_ard_3-2-1_109075_2022-07-22_final
2022-07-22 11:14:50	ga_ls8c_ard_3-2-1_109076_2022-07-22_final
2022-07-22 11:16:26	ga_ls8c_ard_3-2-1_109080_2022-07-22_final
2022-07-22 11:16:50	ga_ls8c_ard_3-2-1_109081_2022-07-22_final
2022-07-22 11:17:38	ga_ls8c_ard_3-2-1_109083_2022-07-22_final
2022-07-23 10:20:49	ga_ls8c_ard_3-2-1_100080_2022-07-23_final
2022-07-23 10:21:13	ga_ls8c_ard_3-2-1_100081_2022-07-23_final
2022-07-23 10:21:37	ga_ls8c_ard_3-2-1_100082_2022-07-23_final
2022-07-23 11:58:07	ga_ls8c_ard_3-2-1_116076_2022-07-23_final
2022-07-23 11:58:31	ga_ls8c_ard_3-2-1_116077_2022-07-23_final
2022-07-24 09:26:24	ga_ls8c_ard_3-2-1_091083_2022-07-23_final
2022-07-24 09:28:48	ga_ls8c_ard_3-2-1_091089_2022-07-23_final
2022-07-24 11:00:06	ga_ls8c_ard_3-2-1_107070_2022-07-24_final
2022-07-24 11:01:42	ga_ls8c_ard_3-2-1_107074_2022-07-24_final
2022-07-24 11:05:18	ga_ls8c_ard_3-2-1_107083_2022-07-24_final
2022-07-25 10:04:30	ga_ls8c_ard_3-2-1_098070_2022-07-25_final
2022-07-25 10:07:17	ga_ls8c_ard_3-2-1_098077_2022-07-25_final
2022-07-25 10:07:41	ga_ls8c_ard_3-2-1_098078_2022-07-25_final
2022-07-25 10:08:05	ga_ls8c_ard_3-2-1_098079_2022-07-25_final
2022-07-25 10:10:05	ga_ls8c_ard_3-2-1_098084_2022-07-25_final
2022-07-25 10:10:29	ga_ls8c_ard_3-2-1_098085_2022-07-25_final
2022-07-25 11:47:46	ga_ls8c_ard_3-2-1_114081_2022-07-25_final
2022-07-26 09:13:40	ga_ls8c_ard_3-2-1_089082_2022-07-25_final
2022-07-26 09:14:28	ga_ls8c_ard_3-2-1_089084_2022-07-25_final
2022-07-26 09:15:16	ga_ls8c_ard_3-2-1_089086_2022-07-25_final
2022-08-01 10:14:44	ga_ls8c_ard_3-2-1_099080_2022-08-01_final
2022-08-02 09:19:08	ga_ls8c_ard_3-2-1_090080_2022-08-01_final
2022-08-02 10:56:25	ga_ls8c_ard_3-2-1_106076_2022-08-02_final
2022-08-03 10:00:48	ga_ls8c_ard_3-2-1_097076_2022-08-03_final
2022-08-03 11:40:29	ga_ls8c_ard_3-2-1_113078_2022-08-03_final
2022-08-04 09:07:35	ga_ls8c_ard_3-2-1_088082_2022-08-03_final
2022-08-05 09:47:16	ga_ls8c_ard_3-2-1_095073_2022-08-05_final
2022-08-05 11:26:09	ga_ls8c_ard_3-2-1_111073_2022-08-05_final
2022-08-05 11:27:45	ga_ls8c_ard_3-2-1_111077_2022-08-05_final
2022-08-07 09:37:43	ga_ls8c_ard_3-2-1_093080_2022-08-07_final
2022-08-08 10:20:59	ga_ls8c_ard_3-2-1_100080_2022-08-08_final
2022-08-08 10:22:35	ga_ls8c_ard_3-2-1_100084_2022-08-08_final
2022-08-08 11:58:40	ga_ls8c_ard_3-2-1_116077_2022-08-08_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-08-09 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-08-08_final
2022-08-10 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-08-10_final
2022-08-10 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-08-10_final
2022-08-10 10:09:26	ga_ls8c_ard_3-2-1_098082_2022-08-10_final
2022-08-11 09:13:49	ga_ls8c_ard_3-2-1_089082_2022-08-10_final
2022-08-11 10:49:54	ga_ls8c_ard_3-2-1_105075_2022-08-11_final
2022-08-12 11:33:34	ga_ls8c_ard_3-2-1_112076_2022-08-12_final
2022-08-13 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-08-13_final
2022-08-13 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-08-13_final
2022-08-13 10:36:45	ga_ls8c_ard_3-2-1_103073_2022-08-13_final
2022-08-13 10:37:09	ga_ls8c_ard_3-2-1_103074_2022-08-13_final
2022-08-13 10:39:09	ga_ls8c_ard_3-2-1_103079_2022-08-13_final
2022-08-14 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-08-14_final
2022-08-14 09:40:44	ga_ls8c_ard_3-2-1_094072_2022-08-14_final
2022-08-14 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-08-14_final
2022-08-14 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-08-14_final
2022-08-14 11:18:26	ga_ls8c_ard_3-2-1_110069_2022-08-14_final
2022-08-14 11:19:14	ga_ls8c_ard_3-2-1_110071_2022-08-14_final
2022-08-15 10:23:36	ga_ls8c_ard_3-2-1_101071_2022-08-15_final
2022-08-15 10:24:48	ga_ls8c_ard_3-2-1_101074_2022-08-15_final
2022-08-15 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-15_final
2022-08-16 09:28:23	ga_ls8c_ard_3-2-1_092072_2022-08-15_final
2022-08-16 09:28:47	ga_ls8c_ard_3-2-1_092073_2022-08-15_final
2022-08-16 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-08-16_final
2022-08-16 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-08-16_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-08-16 11:06:28	ga_ls8c_ard_3-2-1_108070_2022-08-16_final
2022-08-16 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-08-16_final
2022-08-16 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-08-16_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-16 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-08-16_final
2022-08-16 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-08-16_final
2022-08-17 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-08-17_final
2022-08-17 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-08-17_final
2022-08-17 10:15:15	ga_ls8c_ard_3-2-1_099081_2022-08-17_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-18 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-08-18_final
2022-08-18 10:58:30	ga_ls8c_ard_3-2-1_106081_2022-08-18_final
2022-08-18 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-08-18_final
2022-08-19 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-08-19_final
2022-08-19 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-08-19_final
2022-08-19 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-08-19_final
2022-08-19 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-08-19_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