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
2022-11-01 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-11-01_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-04 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-11-04_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-04 11:07:23	ga_ls8c_ard_3-2-1_108072_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-07 10:01:23	ga_ls8c_ard_3-2-1_097077_2022-11-07_final
2022-11-07 10:02:59	ga_ls8c_ard_3-2-1_097081_2022-11-07_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-15 10:48:21	ga_ls8c_ard_3-2-1_105071_2022-11-15_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-17 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-11-17_final
2022-11-18 09:41:56	ga_ls8c_ard_3-2-1_094075_2022-11-18_final
2022-11-18 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-11-18_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-23 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-11-23_final
2022-11-23 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-11-23_final
2022-11-29 09:24:38	ga_ls8c_ard_3-2-1_091078_2022-11-28_final
2022-12-03 10:36:00	ga_ls8c_ard_3-2-1_103071_2022-12-03_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-04 11:22:28	ga_ls8c_ard_3-2-1_110079_2022-12-04_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-06 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-12-06_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-09 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-12-09_final
2022-12-11 11:29:48	ga_ls8c_ard_3-2-1_111082_2022-12-11_final
2022-12-18 09:56:37	ga_ls8c_ard_3-2-1_096081_2022-12-18_final
2022-12-19 10:37:52	ga_ls8c_ard_3-2-1_103076_2022-12-19_final
2022-12-19 10:38:40	ga_ls8c_ard_3-2-1_103078_2022-12-19_final
2022-12-21 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-12-21_final
2022-12-22 11:11:55	ga_ls8c_ard_3-2-1_108084_2022-12-22_final
2022-12-23 10:15:05	ga_ls8c_ard_3-2-1_099081_2022-12-23_final
2022-12-27 09:51:36	ga_ls8c_ard_3-2-1_095084_2022-12-27_final
2022-12-29 09:38:03	ga_ls8c_ard_3-2-1_093081_2022-12-29_final
2022-12-31 09:24:53	ga_ls8c_ard_3-2-1_091079_2022-12-30_final
2022-12-31 11:04:58	ga_ls8c_ard_3-2-1_107082_2022-12-31_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-05 11:22:43	ga_ls8c_ard_3-2-1_110080_2023-01-05_final
2023-01-05 11:23:07	ga_ls8c_ard_3-2-1_110081_2023-01-05_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-09 10:58:22	ga_ls8c_ard_3-2-1_106081_2023-01-09_final
2023-01-10 10:00:21	ga_ls8c_ard_3-2-1_097075_2023-01-10_final
2023-01-12 09:51:09	ga_ls8c_ard_3-2-1_095083_2023-01-12_final
2023-01-13 10:34:00	ga_ls8c_ard_3-2-1_102082_2023-01-13_final
2023-01-14 09:38:22	ga_ls8c_ard_3-2-1_093082_2023-01-14_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-14 09:40:22	ga_ls8c_ard_3-2-1_093087_2023-01-14_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-19 09:56:28	ga_ls8c_ard_3-2-1_096081_2023-01-19_final
2023-01-20 10:36:57	ga_ls8c_ard_3-2-1_103074_2023-01-20_final
2023-01-21 09:43:44	ga_ls8c_ard_3-2-1_094080_2023-01-21_final
2023-01-22 10:27:25	ga_ls8c_ard_3-2-1_101081_2023-01-22_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-23 11:10:17	ga_ls8c_ard_3-2-1_108080_2023-01-23_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-01-29 10:31:15	ga_ls8c_ard_3-2-1_102075_2023-01-29_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-01 09:26:03	ga_ls8c_ard_3-2-1_091082_2023-01-31_final
2023-02-06 09:46:11	ga_ls8c_ard_3-2-1_094086_2023-02-06_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-10 09:19:02	ga_ls8c_ard_3-2-1_090080_2023-02-09_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-11 10:01:05	ga_ls8c_ard_3-2-1_097077_2023-02-11_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-12 10:44:19	ga_ls8c_ard_3-2-1_104077_2023-02-12_final
2023-02-14 10:32:20	ga_ls8c_ard_3-2-1_102078_2023-02-14_final
2023-02-15 09:39:06	ga_ls8c_ard_3-2-1_093084_2023-02-15_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-17 09:25:55	ga_ls8c_ard_3-2-1_091082_2023-02-16_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_final
2023-02-22 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-02-22_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-02-26 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-02-25_final
2023-02-26 10:56:50	ga_ls8c_ard_3-2-1_106078_2023-02-26_final
2023-03-01 11:26:32	ga_ls8c_ard_3-2-1_111075_2023-03-01_final
2023-03-01 11:26:56	ga_ls8c_ard_3-2-1_111076_2023-03-01_final
2023-03-01 11:28:32	ga_ls8c_ard_3-2-1_111080_2023-03-01_final
2023-03-03 09:38:05	ga_ls8c_ard_3-2-1_093082_2023-03-03_final
2023-03-03 09:38:29	ga_ls8c_ard_3-2-1_093083_2023-03-03_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-09 10:36:37	ga_ls8c_ard_3-2-1_103074_2023-03-09_final
2023-03-10 11:22:17	ga_ls8c_ard_3-2-1_110080_2023-03-10_final
2023-03-10 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-03-10_final
2023-03-12 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-03-12_final
2023-03-13 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-03-13_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-16 10:42:47	ga_ls8c_ard_3-2-1_104074_2023-03-16_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