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
2019-06-26 09:49:05	ga_ls8c_ard_3-1-0_095079_2019-06-26_final
2019-06-26 09:50:17	ga_ls8c_ard_3-1-0_095082_2019-06-26_final
2019-08-13 09:46:55	ga_ls8c_ard_3-1-0_095073_2019-08-13_final
2019-08-13 09:48:07	ga_ls8c_ard_3-1-0_095076_2019-08-13_final
2019-09-30 09:48:21	ga_ls8c_ard_3-1-0_095076_2019-09-30_final
2019-11-01 09:48:23	ga_ls8c_ard_3-1-0_095076_2019-11-01_final
2020-01-20 09:48:57	ga_ls8c_ard_3-1-0_095078_2020-01-20_final
2020-02-21 09:48:48	ga_ls8c_ard_3-1-0_095078_2020-02-21_final
2020-03-24 09:47:47	ga_ls8c_ard_3-1-0_095076_2020-03-24_final
2020-04-09 09:50:02	ga_ls8c_ard_3-1-0_095082_2020-04-09_final
2022-03-30 09:46:08	ga_ls8c_ard_3-2-1_095072_2022-03-30_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-03-31 10:30:12	ga_ls8c_ard_3-2-1_102074_2022-03-31_final
2022-04-01 09:34:35	ga_ls8c_ard_3-2-1_093074_2022-04-01_final
2022-04-01 09:34:58	ga_ls8c_ard_3-2-1_093075_2022-04-01_final
2022-04-01 11:11:28	ga_ls8c_ard_3-2-1_109069_2022-04-01_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-05 10:47:34	ga_ls8c_ard_3-2-1_105071_2022-04-05_final
2022-04-06 09:52:45	ga_ls8c_ard_3-2-1_096073_2022-04-06_final
2022-04-06 09:53:57	ga_ls8c_ard_3-2-1_096076_2022-04-06_final
2022-04-06 09:54:45	ga_ls8c_ard_3-2-1_096078_2022-04-06_final
2022-04-06 11:33:14	ga_ls8c_ard_3-2-1_112077_2022-04-06_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-09 10:26:53	ga_ls8c_ard_3-2-1_101081_2022-04-09_final
2022-04-10 09:32:28	ga_ls8c_ard_3-2-1_092084_2022-04-10_final
2022-04-10 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-04-10_final
2022-04-11 10:10:57	ga_ls8c_ard_3-2-1_099072_2022-04-11_final
2022-04-12 09:20:55	ga_ls8c_ard_3-2-1_090086_2022-04-11_final
2022-04-13 09:59:48	ga_ls8c_ard_3-2-1_097075_2022-04-13_final
2022-04-13 10:00:11	ga_ls8c_ard_3-2-1_097076_2022-04-13_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-18 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-04-18_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-20 10:07:10	ga_ls8c_ard_3-2-1_098078_2022-04-20_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-21 09:16:19	ga_ls8c_ard_3-2-1_089090_2022-04-20_final
2022-04-22 09:57:35	ga_ls8c_ard_3-2-1_096085_2022-04-22_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-23 10:39:14	ga_ls8c_ard_3-2-1_103081_2022-04-23_final
2022-04-27 10:11:41	ga_ls8c_ard_3-2-1_099074_2022-04-27_final
2022-04-27 10:14:53	ga_ls8c_ard_3-2-1_099082_2022-04-27_final
2022-04-27 10:15:17	ga_ls8c_ard_3-2-1_099083_2022-04-27_final
2022-04-30 10:44:59	ga_ls8c_ard_3-2-1_104080_2022-04-30_final
2022-05-01 09:47:47	ga_ls8c_ard_3-2-1_095076_2022-05-01_final
2022-05-01 09:50:11	ga_ls8c_ard_3-2-1_095082_2022-05-01_final
2022-05-01 09:50:35	ga_ls8c_ard_3-2-1_095083_2022-05-01_final
2022-05-02 10:32:39	ga_ls8c_ard_3-2-1_102080_2022-05-02_final
2022-05-03 09:37:51	ga_ls8c_ard_3-2-1_093082_2022-05-03_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-04 10:19:55	ga_ls8c_ard_3-2-1_100079_2022-05-04_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-05 10:59:36	ga_ls8c_ard_3-2-1_107070_2022-05-05_final
2022-05-05 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-05-05_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2022-05-07 10:51:15	ga_ls8c_ard_3-2-1_105080_2022-05-07_final
2022-05-08 11:32:56	ga_ls8c_ard_3-2-1_112076_2022-05-08_final
2022-05-08 11:33:20	ga_ls8c_ard_3-2-1_112077_2022-05-08_final
2022-05-09 10:35:44	ga_ls8c_ard_3-2-1_103072_2022-05-09_final
2022-05-09 10:39:43	ga_ls8c_ard_3-2-1_103082_2022-05-09_final
2022-05-11 10:24:11	ga_ls8c_ard_3-2-1_101074_2022-05-11_final
2022-05-12 11:07:51	ga_ls8c_ard_3-2-1_108075_2022-05-12_final
2022-05-13 10:13:50	ga_ls8c_ard_3-2-1_099079_2022-05-13_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-13 11:52:19	ga_ls8c_ard_3-2-1_115078_2022-05-13_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-05-16 10:43:09	ga_ls8c_ard_3-2-1_104075_2022-05-16_final
2022-05-17 09:49:08	ga_ls8c_ard_3-2-1_095079_2022-05-17_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-20 10:18:27	ga_ls8c_ard_3-2-1_100075_2022-05-20_final
2022-05-24 09:54:07	ga_ls8c_ard_3-2-1_096076_2022-05-24_final
2022-05-24 11:33:24	ga_ls8c_ard_3-2-1_112077_2022-05-24_final
2022-05-25 10:39:46	ga_ls8c_ard_3-2-1_103082_2022-05-25_final
2022-05-26 09:39:45	ga_ls8c_ard_3-2-1_094071_2022-05-26_final
2022-05-26 09:42:57	ga_ls8c_ard_3-2-1_094079_2022-05-26_final
2022-05-26 11:21:50	ga_ls8c_ard_3-2-1_110079_2022-05-26_final
2022-05-31 11:40:01	ga_ls8c_ard_3-2-1_113078_2022-05-31_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-05 11:58:14	ga_ls8c_ard_3-2-1_116077_2022-06-05_final
2022-06-06 11:00:38	ga_ls8c_ard_3-2-1_107072_2022-06-06_final
2022-06-07 10:04:37	ga_ls8c_ard_3-2-1_098071_2022-06-07_final
2022-06-07 10:06:13	ga_ls8c_ard_3-2-1_098075_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-08 09:16:36	ga_ls8c_ard_3-2-1_089090_2022-06-07_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-13 09:31:12	ga_ls8c_ard_3-2-1_092080_2022-06-13_final
2022-06-13 11:07:42	ga_ls8c_ard_3-2-1_108074_2022-06-13_final
2022-06-15 10:53:46	ga_ls8c_ard_3-2-1_106070_2022-06-15_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-16 11:40:37	ga_ls8c_ard_3-2-1_113079_2022-06-16_final
2022-06-17 10:43:25	ga_ls8c_ard_3-2-1_104075_2022-06-17_final
2022-06-18 09:52:11	ga_ls8c_ard_3-2-1_095086_2022-06-18_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_final
2022-06-20 09:38:14	ga_ls8c_ard_3-2-1_093082_2022-06-20_final
2022-06-20 11:16:20	ga_ls8c_ard_3-2-1_109080_2022-06-20_final
2022-06-20 11:16:44	ga_ls8c_ard_3-2-1_109081_2022-06-20_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