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
2019-04-07 09:46:43	ga_ls8c_ard_3-1-0_095074_2019-04-07_final
2019-04-07 09:49:54	ga_ls8c_ard_3-1-0_095082_2019-04-07_final
2019-06-14 09:24:42	ga_ls8c_ard_3-1-0_091080_2019-06-13_final
2019-06-26 09:52:16	ga_ls8c_ard_3-1-0_095087_2019-06-26_final
2019-08-17 09:23:49	ga_ls8c_ard_3-1-0_091077_2019-08-16_final
2019-09-02 09:23:29	ga_ls8c_ard_3-1-0_091076_2019-09-01_final
2019-09-30 09:47:09	ga_ls8c_ard_3-1-0_095073_2019-09-30_final
2019-09-30 09:47:33	ga_ls8c_ard_3-1-0_095074_2019-09-30_final
2019-10-16 09:47:12	ga_ls8c_ard_3-1-0_095073_2019-10-16_final
2019-10-16 09:52:23	ga_ls8c_ard_3-1-0_095086_2019-10-16_final
2019-10-20 09:25:16	ga_ls8c_ard_3-1-0_091080_2019-10-19_final
2019-11-01 09:51:11	ga_ls8c_ard_3-1-0_095083_2019-11-01_final
2019-11-17 09:50:44	ga_ls8c_ard_3-1-0_095082_2019-11-17_final
2019-12-03 09:46:43	ga_ls8c_ard_3-1-0_095072_2019-12-03_final
2019-12-03 09:50:43	ga_ls8c_ard_3-1-0_095082_2019-12-03_final
2020-02-05 09:48:04	ga_ls8c_ard_3-1-0_095076_2020-02-05_final
2020-02-21 09:52:00	ga_ls8c_ard_3-1-0_095086_2020-02-21_final
2022-03-29 10:41:22	ga_ls8c_ard_3-2-1_104071_2022-03-29_final
2022-03-30 09:46:56	ga_ls8c_ard_3-2-1_095074_2022-03-30_final
2022-03-30 09:47:20	ga_ls8c_ard_3-2-1_095075_2022-03-30_final
2022-03-30 11:25:49	ga_ls8c_ard_3-2-1_111074_2022-03-30_final
2022-03-31 10:28:36	ga_ls8c_ard_3-2-1_102070_2022-03-31_final
2022-03-31 10:29:24	ga_ls8c_ard_3-2-1_102072_2022-03-31_final
2022-04-01 09:35:22	ga_ls8c_ard_3-2-1_093076_2022-04-01_final
2022-04-03 09:25:00	ga_ls8c_ard_3-2-1_091081_2022-04-02_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-04 10:05:05	ga_ls8c_ard_3-2-1_098073_2022-04-04_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-04 10:09:53	ga_ls8c_ard_3-2-1_098085_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-08 11:23:41	ga_ls8c_ard_3-2-1_110084_2022-04-08_final
2022-04-09 10:24:05	ga_ls8c_ard_3-2-1_101074_2022-04-09_final
2022-04-09 10:25:41	ga_ls8c_ard_3-2-1_101078_2022-04-09_final
2022-04-10 09:29:16	ga_ls8c_ard_3-2-1_092076_2022-04-09_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-12 10:57:48	ga_ls8c_ard_3-2-1_106081_2022-04-12_final
2022-04-13 11:39:28	ga_ls8c_ard_3-2-1_113077_2022-04-13_final
2022-04-14 10:41:04	ga_ls8c_ard_3-2-1_104070_2022-04-14_final
2022-04-15 11:23:56	ga_ls8c_ard_3-2-1_111069_2022-04-15_final
2022-04-15 11:29:07	ga_ls8c_ard_3-2-1_111082_2022-04-15_final
2022-04-17 11:12:46	ga_ls8c_ard_3-2-1_109072_2022-04-17_final
2022-04-18 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-04-18_final
2022-04-19 09:25:54	ga_ls8c_ard_3-2-1_091083_2022-04-18_final
2022-04-19 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-04-19_final
2022-04-19 11:01:11	ga_ls8c_ard_3-2-1_107074_2022-04-19_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-21 10:47:37	ga_ls8c_ard_3-2-1_105071_2022-04-21_final
2022-04-22 09:57:11	ga_ls8c_ard_3-2-1_096084_2022-04-22_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-26 11:06:08	ga_ls8c_ard_3-2-1_108071_2022-04-26_final
2022-04-28 10:53:45	ga_ls8c_ard_3-2-1_106071_2022-04-28_final
2022-04-29 09:58:55	ga_ls8c_ard_3-2-1_097073_2022-04-29_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-05-01 09:47:23	ga_ls8c_ard_3-2-1_095075_2022-05-01_final
2022-05-01 09:49:23	ga_ls8c_ard_3-2-1_095080_2022-05-01_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-01 11:24:40	ga_ls8c_ard_3-2-1_111071_2022-05-01_final
2022-05-03 11:13:08	ga_ls8c_ard_3-2-1_109073_2022-05-03_final
2022-05-03 11:17:08	ga_ls8c_ard_3-2-1_109083_2022-05-03_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-06 11:46:52	ga_ls8c_ard_3-2-1_114080_2022-05-06_final
2022-05-09 10:39:19	ga_ls8c_ard_3-2-1_103081_2022-05-09_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-18 10:29:12	ga_ls8c_ard_3-2-1_102071_2022-05-18_final
2022-05-19 09:35:59	ga_ls8c_ard_3-2-1_093077_2022-05-19_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-20 10:21:14	ga_ls8c_ard_3-2-1_100082_2022-05-20_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-05-23 09:14:03	ga_ls8c_ard_3-2-1_089084_2022-05-22_final
2022-05-24 09:52:55	ga_ls8c_ard_3-2-1_096073_2022-05-24_final
2022-05-24 09:56:55	ga_ls8c_ard_3-2-1_096083_2022-05-24_final
2022-05-26 09:41:45	ga_ls8c_ard_3-2-1_094076_2022-05-26_final
2022-05-26 09:43:21	ga_ls8c_ard_3-2-1_094080_2022-05-26_final
2022-05-26 11:18:14	ga_ls8c_ard_3-2-1_110070_2022-05-26_final
2022-05-30 10:57:32	ga_ls8c_ard_3-2-1_106080_2022-05-30_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-05-31 09:59:08	ga_ls8c_ard_3-2-1_097073_2022-05-31_final
2022-05-31 11:40:25	ga_ls8c_ard_3-2-1_113079_2022-05-31_final
2022-05-31 11:40:49	ga_ls8c_ard_3-2-1_113080_2022-05-31_final
2022-06-02 11:26:30	ga_ls8c_ard_3-2-1_111075_2022-06-02_final
2022-06-04 11:12:58	ga_ls8c_ard_3-2-1_109072_2022-06-04_final
2022-06-04 11:17:21	ga_ls8c_ard_3-2-1_109083_2022-06-04_final
2022-06-05 10:17:45	ga_ls8c_ard_3-2-1_100073_2022-06-05_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-07 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-06-07_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-15 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-06-15_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_final
2022-06-17 10:46:12	ga_ls8c_ard_3-2-1_104082_2022-06-17_final
2022-06-19 10:28:40	ga_ls8c_ard_3-2-1_102069_2022-06-19_final
2022-06-20 11:17:08	ga_ls8c_ard_3-2-1_109082_2022-06-20_final
2022-06-22 09:26:17	ga_ls8c_ard_3-2-1_091083_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