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
2022-01-14 10:09:10	ga_ls8c_ard_3-2-1_098082_2022-01-14_final
2022-10-19 11:12:06	ga_ls8c_ard_3-2-1_108084_2022-10-19_final
2022-10-23 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-23_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-10-29 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-10-29_final
2022-11-06 10:57:01	ga_ls8c_ard_3-2-1_106077_2022-11-06_final
2022-11-07 10:01:23	ga_ls8c_ard_3-2-1_097077_2022-11-07_final
2022-11-07 11:39:52	ga_ls8c_ard_3-2-1_113076_2022-11-07_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-10 10:31:28	ga_ls8c_ard_3-2-1_102075_2022-11-10_final
2022-11-15 10:51:57	ga_ls8c_ard_3-2-1_105080_2022-11-15_final
2022-11-18 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-11-18_final
2022-11-20 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-11-19_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-27 11:15:29	ga_ls8c_ard_3-2-1_109077_2022-11-27_final
2022-11-29 11:05:07	ga_ls8c_ard_3-2-1_107082_2022-11-29_final
2022-12-02 11:35:37	ga_ls8c_ard_3-2-1_112081_2022-12-02_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-03 10:38:00	ga_ls8c_ard_3-2-1_103076_2022-12-03_final
2022-12-05 10:27:38	ga_ls8c_ard_3-2-1_101081_2022-12-05_final
2022-12-07 10:12:52	ga_ls8c_ard_3-2-1_099075_2022-12-07_final
2022-12-09 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-12-09_final
2022-12-10 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-12-10_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-14 10:20:36	ga_ls8c_ard_3-2-1_100079_2022-12-14_final
2022-12-17 10:49:04	ga_ls8c_ard_3-2-1_105073_2022-12-17_final
2022-12-18 09:57:01	ga_ls8c_ard_3-2-1_096082_2022-12-18_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-22 09:30:38	ga_ls8c_ard_3-2-1_092078_2022-12-22_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-24 09:20:16	ga_ls8c_ard_3-2-1_090083_2022-12-23_final
2022-12-25 10:01:33	ga_ls8c_ard_3-2-1_097078_2022-12-25_final
2022-12-29 09:37:39	ga_ls8c_ard_3-2-1_093080_2022-12-29_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2023-01-01 10:09:21	ga_ls8c_ard_3-2-1_098082_2023-01-01_final
2023-01-05 11:23:07	ga_ls8c_ard_3-2-1_110081_2023-01-05_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-10 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-10_final
2023-01-12 09:51:57	ga_ls8c_ard_3-2-1_095085_2023-01-12_final
2023-01-15 10:20:25	ga_ls8c_ard_3-2-1_100079_2023-01-15_final
2023-01-16 11:04:51	ga_ls8c_ard_3-2-1_107082_2023-01-16_final
2023-01-18 10:51:16	ga_ls8c_ard_3-2-1_105079_2023-01-18_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-26 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-26_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-10 10:56:43	ga_ls8c_ard_3-2-1_106077_2023-02-10_final
2023-02-11 10:01:05	ga_ls8c_ard_3-2-1_097077_2023-02-11_final
2023-02-11 11:40:22	ga_ls8c_ard_3-2-1_113078_2023-02-11_final
2023-02-13 09:51:29	ga_ls8c_ard_3-2-1_095084_2023-02-13_final
2023-02-14 10:31:32	ga_ls8c_ard_3-2-1_102076_2023-02-14_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-17 09:24:43	ga_ls8c_ard_3-2-1_091079_2023-02-16_final
2023-02-21 10:37:12	ga_ls8c_ard_3-2-1_103075_2023-02-21_final
2023-02-23 10:27:11	ga_ls8c_ard_3-2-1_101081_2023-02-23_final
2023-02-27 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-02-27_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_final
2023-03-08 11:35:02	ga_ls8c_ard_3-2-1_112081_2023-03-08_final
2023-03-12 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-03-12_final
2023-03-14 10:57:09	ga_ls8c_ard_3-2-1_106079_2023-03-14_final
2023-03-16 10:41:59	ga_ls8c_ard_3-2-1_104072_2023-03-16_final
2023-03-23 10:48:03	ga_ls8c_ard_3-2-1_105072_2023-03-23_final
2023-03-23 10:51:38	ga_ls8c_ard_3-2-1_105081_2023-03-23_final
2023-03-26 09:45:38	ga_ls8c_ard_3-2-1_094086_2023-03-26_final
2023-03-26 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-03-26_final
2023-03-28 11:06:34	ga_ls8c_ard_3-2-1_108072_2023-03-28_final
2023-03-29 10:11:44	ga_ls8c_ard_3-2-1_099074_2023-03-29_final
2023-03-29 10:12:08	ga_ls8c_ard_3-2-1_099075_2023-03-29_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-03-31 10:02:57	ga_ls8c_ard_3-2-1_097083_2023-03-31_final
2023-04-06 11:00:15	ga_ls8c_ard_3-2-1_107072_2023-04-06_final
2023-04-07 10:06:12	ga_ls8c_ard_3-2-1_098076_2023-04-07_final
2023-04-07 11:45:05	ga_ls8c_ard_3-2-1_114076_2023-04-07_final
2023-04-10 10:35:49	ga_ls8c_ard_3-2-1_103073_2023-04-10_final
2023-04-10 10:36:13	ga_ls8c_ard_3-2-1_103074_2023-04-10_final
2023-04-13 11:09:30	ga_ls8c_ard_3-2-1_108080_2023-04-13_final
2023-04-19 10:31:10	ga_ls8c_ard_3-2-1_102077_2023-04-19_final
2023-04-20 11:11:14	ga_ls8c_ard_3-2-1_109069_2023-04-20_final
2023-04-20 11:14:50	ga_ls8c_ard_3-2-1_109078_2023-04-20_final
2023-04-26 10:35:45	ga_ls8c_ard_3-2-1_103073_2023-04-26_final
2023-04-27 11:22:12	ga_ls8c_ard_3-2-1_110081_2023-04-27_final
2023-04-29 11:07:50	ga_ls8c_ard_3-2-1_108076_2023-04-29_final
2023-04-30 10:11:00	ga_ls8c_ard_3-2-1_099073_2023-04-30_final
2023-05-01 10:56:15	ga_ls8c_ard_3-2-1_106078_2023-05-01_final
2023-05-03 10:41:05	ga_ls8c_ard_3-2-1_104071_2023-05-03_final
2023-05-04 09:50:14	ga_ls8c_ard_3-2-1_095083_2023-05-04_final
2023-05-04 11:28:43	ga_ls8c_ard_3-2-1_111082_2023-05-04_final
2023-05-06 09:35:03	ga_ls8c_ard_3-2-1_093076_2023-05-06_final
2023-05-07 10:17:54	ga_ls8c_ard_3-2-1_100075_2023-05-07_final
2023-05-09 11:44:23	ga_ls8c_ard_3-2-1_114075_2023-05-09_final
2023-05-11 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-11_final
2023-05-13 11:20:24	ga_ls8c_ard_3-2-1_110077_2023-05-13_final
2023-05-15 11:06:01	ga_ls8c_ard_3-2-1_108072_2023-05-15_final
2023-05-15 11:10:01	ga_ls8c_ard_3-2-1_108082_2023-05-15_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