petrel.grid: A dataset of grids for producing spatial predictions of...
In spm: Spatial Predictive Modeling
petrel.grid R Documentation
A dataset of grids for producing spatial predictions of seabed sediment content in the Petrel sub-basin in Australia Exclusive Economic Zone
Description
This dataset contains 248675 rows of 6 variables including
longitude (long), latitude (lat), bathymetry (bathy), disttance to coast (dist), seabe relief (relief),
seabed slope (slope).
Usage
data("petrel")
Format
A data frame with 248675 observations on the following 6 variables.
longa numeric vector, decimal degree
lata numeric vector, decimal degree
bathya numeric vector, meter bellow sea level
dista numeric vector, degree
reliefa numeric vector, meter
slopea numeric vector, no unit
Details
For details, please check the reference.
Source
Li, J., 2013. Predicting the spatial distribution of seabed gravel content using random forest, spatial interpolation methods and their hybrid methods, The International Congress on Modelling and Simulation (MODSIM) 2013: Adelaide, pp. 394-400.
spm documentation built on May 6, 2022, 9:06 a.m.
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| petrel.grid | R Documentation |
A dataset of grids for producing spatial predictions of seabed sediment content in the Petrel sub-basin in Australia Exclusive Economic Zone
Description
This dataset contains 248675 rows of 6 variables including longitude (long), latitude (lat), bathymetry (bathy), disttance to coast (dist), seabe relief (relief), seabed slope (slope).
Usage
data("petrel")
Format
A data frame with 248675 observations on the following 6 variables.
longa numeric vector, decimal degree
lata numeric vector, decimal degree
bathya numeric vector, meter bellow sea level
dista numeric vector, degree
reliefa numeric vector, meter
slopea numeric vector, no unit
Details
For details, please check the reference.
Source
Li, J., 2013. Predicting the spatial distribution of seabed gravel content using random forest, spatial interpolation methods and their hybrid methods, The International Congress on Modelling and Simulation (MODSIM) 2013: Adelaide, pp. 394-400.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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