Ultrahigh Dimensional Variable Selection for Interpolation of Point Referenced Spatial Data: A Digital Soil Mapping Case Study
نویسندگان
چکیده
Modern soil mapping is characterised by the need to interpolate point referenced (geostatistical) observations and the availability of large numbers of environmental characteristics for consideration as covariates to aid this interpolation. Modelling tasks of this nature also occur in other fields such as biogeography and environmental science. This analysis employs the Least Angle Regression (LAR) algorithm for fitting Least Absolute Shrinkage and Selection Operator (LASSO) penalized Multiple Linear Regressions models. This analysis demonstrates the efficiency of the LAR algorithm at selecting covariates to aid the interpolation of geostatistical soil carbon observations. Where an exhaustive search of the models that could be constructed from 800 potential covariate terms and 60 observations would be prohibitively demanding, LASSO variable selection is accomplished with trivial computational investment.
منابع مشابه
Evaluating optimized digital elevation precipitation model using IDW method (Case study: Jam & Riz Watershed of Assaloyeh, Iran)
A watershed management program is usually based on the results of watershed modeling. Accurate modeling results are decided by the appropriate parameters and input data. Precipitation is the most important input for watershed modeling. Precipitation characteristics usually exhibit significant spatial variation, even within small watersheds. Therefore, properly describing the spatial variation o...
متن کاملMapping Spatial Variability of Soil Salinity Using Remote Sensing Data and Geostatistical Analysis: A Case of Shadegan, Khuzestan
Extended abstract 1- Introduction Soil salinity is one of the most important desertification parameters in many parts of the world. Thus, preparing soil salinity maps in macro scales is necessary. Water and soil salinity as one of the contributing parameters in desertification, cause soil and vegetation degradation. Soil salinization represents many negative effects on the earth systems such ...
متن کاملZoning hydraulic conductivity using different geostatistical methods (Case study Shavoor)
In studies of irrigation and drainage projects for drainage, it is necessary to extend the data from the sampling point to the network. Therefore, based on available data from observational wells, estimating the state of hydraulic conductivity (K) in the surrounding area. The estimation process values for locations where there is no information for them based on viewing areas called wells spati...
متن کاملAssessment of geostatistical and interpolation methods for mapping forest dieback intensity in Zagros forests
During recent years, oak decline has been widely spread across Brant’s oak (Quercus Brantii Lindl.) stands in the Zagros Mountains, Western Iran, which caused large-area forest dieback in several sites. Mapping the intensity and spatial distribution of forest dieback is essential for developing management and control strategies. This study evaluated a range of geostatistical and interpolation m...
متن کاملMapping spatial variability of soil salinity in a coastal area located in an arid environment using geostatistical and correlation methods based on the satellite data
Saline lakes can increase the soil and water salinity of the coastal areas. The main aim of this study is to distinguish the characteristics of the spectral reflectance of saline soil, analyze the statistical relationship between soil EC and characteristics of the spectral reflectance of saline soil, and to map soil salinity east of the Maharloo Lake. The correlation between field measurements ...
متن کامل