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

52 results

Time (local)	Label
2023-12-14 09:47:23	ga_ls8c_ard_3-2-1_095074_2023-12-14_final
2023-12-14 11:29:03	ga_ls8c_ard_3-2-1_111081_2023-12-14_final
2023-12-15 10:31:51	ga_ls8c_ard_3-2-1_102077_2023-12-15_final
2023-12-16 09:36:38	ga_ls8c_ard_3-2-1_093078_2023-12-16_final
2023-12-16 09:37:26	ga_ls8c_ard_3-2-1_093080_2023-12-16_final
2023-12-16 09:39:02	ga_ls8c_ard_3-2-1_093084_2023-12-16_final
2023-12-16 09:39:26	ga_ls8c_ard_3-2-1_093085_2023-12-16_final
2023-12-16 11:12:43	ga_ls8c_ard_3-2-1_109071_2023-12-16_final
2023-12-16 11:13:31	ga_ls8c_ard_3-2-1_109073_2023-12-16_final
2023-12-16 11:14:43	ga_ls8c_ard_3-2-1_109076_2023-12-16_final
2023-12-16 11:16:19	ga_ls8c_ard_3-2-1_109080_2023-12-16_final
2023-12-17 10:17:07	ga_ls8c_ard_3-2-1_100071_2023-12-17_final
2023-12-17 10:17:30	ga_ls8c_ard_3-2-1_100072_2023-12-17_final
2023-12-17 10:19:30	ga_ls8c_ard_3-2-1_100077_2023-12-17_final
2023-12-17 10:21:30	ga_ls8c_ard_3-2-1_100082_2023-12-17_final
2023-12-18 09:25:29	ga_ls8c_ard_3-2-1_091081_2023-12-17_final
2023-12-18 09:26:41	ga_ls8c_ard_3-2-1_091084_2023-12-17_final
2023-12-18 09:27:53	ga_ls8c_ard_3-2-1_091087_2023-12-17_final
2023-12-18 11:01:34	ga_ls8c_ard_3-2-1_107074_2023-12-18_final
2023-12-18 11:02:22	ga_ls8c_ard_3-2-1_107076_2023-12-18_final
2023-12-18 11:03:10	ga_ls8c_ard_3-2-1_107078_2023-12-18_final
2023-12-19 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-12-19_final
2023-12-19 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-12-19_final
2023-12-19 10:04:46	ga_ls8c_ard_3-2-1_098071_2023-12-19_final
2023-12-19 10:05:33	ga_ls8c_ard_3-2-1_098073_2023-12-19_final
2023-12-19 10:06:45	ga_ls8c_ard_3-2-1_098076_2023-12-19_final
2023-12-19 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-12-19_final
2023-12-19 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-12-19_final
2023-12-19 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-12-19_final
2023-12-20 09:11:32	ga_ls8c_ard_3-2-1_089077_2023-12-19_final
2023-12-20 09:15:08	ga_ls8c_ard_3-2-1_089086_2023-12-19_final
2023-12-20 10:50:01	ga_ls8c_ard_3-2-1_105076_2023-12-20_final
2023-12-20 10:51:37	ga_ls8c_ard_3-2-1_105080_2023-12-20_final
2023-12-20 10:52:01	ga_ls8c_ard_3-2-1_105081_2023-12-20_final
2023-12-21 09:55:12	ga_ls8c_ard_3-2-1_096078_2023-12-21_final
2023-12-21 09:56:24	ga_ls8c_ard_3-2-1_096081_2023-12-21_final
2023-12-21 11:36:29	ga_ls8c_ard_3-2-1_112084_2023-12-21_final
2023-12-22 10:36:52	ga_ls8c_ard_3-2-1_103074_2023-12-22_final
2023-12-22 10:37:40	ga_ls8c_ard_3-2-1_103076_2023-12-22_final
2023-12-23 09:40:26	ga_ls8c_ard_3-2-1_094072_2023-12-23_final
2023-12-23 09:40:50	ga_ls8c_ard_3-2-1_094073_2023-12-23_final
2023-12-23 09:41:14	ga_ls8c_ard_3-2-1_094074_2023-12-23_final
2023-12-23 09:43:38	ga_ls8c_ard_3-2-1_094080_2023-12-23_final
2023-12-23 11:18:08	ga_ls8c_ard_3-2-1_110069_2023-12-23_final
2023-12-23 11:22:07	ga_ls8c_ard_3-2-1_110079_2023-12-23_final
2023-12-23 11:22:31	ga_ls8c_ard_3-2-1_110080_2023-12-23_final
2023-12-23 11:23:43	ga_ls8c_ard_3-2-1_110083_2023-12-23_final
2023-12-24 10:24:06	ga_ls8c_ard_3-2-1_101073_2023-12-24_final
2023-12-24 10:26:53	ga_ls8c_ard_3-2-1_101080_2023-12-24_final
2023-12-24 10:27:17	ga_ls8c_ard_3-2-1_101081_2023-12-24_final
2023-12-25 09:27:40	ga_ls8c_ard_3-2-1_092071_2023-12-24_final
2023-12-25 09:29:16	ga_ls8c_ard_3-2-1_092075_2023-12-24_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years