You have an existing collection of sample data from a given spatial domain. You want to collect some new samples from this spatial domain, but want to do so in consideration of your existing samples rather than just treating it as a clean slate. Read on to find out about a few approaches on how you might do this.

Journal Paper Digests 2019 #5

  • Evaluation of Parametric and Nonparametric Machine-Learning Techniques for Prediction of Saturated and Near-Saturated Hydraulic Conductivity
  • Delineating Site-Specific Management Zones and Evaluating Soil Water Temporal Dynamics in a Farmer’s Field in Kentucky
  • Evidences of soil geochemistry and mineralogy changes caused by eucalyptus rhizosphere

Journal Paper Digests 2019 #4

  • Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data-Poor Regions
  • A High-Resolution Global Map of Soil Hydraulic Properties Produced by a Hierarchical Parameterization of a Physically Based Water Retention Model
  • How far can the uncertainty on a Digital Soil Map be known?: A numerical experiment using pseudo values of clay content obtained from Vis-SWIR hyperspectral imagery
  • National soil organic carbon estimates can improve global estimates
  • Merging country, continental and global predictions of soil texture: Lessons from ensemble modelling in France
  • Use of portable XRF: Effect of thickness and antecedent moisture of soils on measured concentration of trace elements
  • Mapping future soil carbon change and its uncertainty in croplands using simple surrogates of a complex farming system model
  • Soil fertility assessment by Vis-NIR spectroscopy: Predicting soil functioning rather than availability indices
  • Pre-treatment of soil X-ray powder diffraction data for cluster analysis
  • The Role of Urban Agriculture in a Secure, Healthy, and Sustainable Food System
  • Poetry as a Creative Practice to Enhance Engagement and Learning in Conservation Science

Journal Paper Digests 2019 #4

  • Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data-Poor Regions
  • A High-Resolution Global Map of Soil Hydraulic Properties Produced by a Hierarchical Parameterization of a Physically Based Water Retention Model
  • How far can the uncertainty on a Digital Soil Map be known?: A numerical experiment using pseudo values of clay content obtained from Vis-SWIR hyperspectral imagery
  • National soil organic carbon estimates can improve global estimates
  • Merging country, continental and global predictions of soil texture: Lessons from ensemble modelling in France
  • Use of portable XRF: Effect of thickness and antecedent moisture of soils on measured concentration of trace elements
  • Mapping future soil carbon change and its uncertainty in croplands using simple surrogates of a complex farming system model
  • Soil fertility assessment by Vis-NIR spectroscopy: Predicting soil functioning rather than availability indices
  • Pre-treatment of soil X-ray powder diffraction data for cluster analysis

Journal Paper Digests 2019 #3

  • The minimum level for soil allocation using topsoil reflectance spectra: Genus or species?
  • Deconstructing aeolian landscapes
  • Combination of fractional order derivative and memory-based learning algorithm to improve the estimation accuracy of soil organic matter by visible and near-infrared spectroscopy
  • Agricultural landscape evolution and structural connectivity to the river for matter flux, a multi-agents simulation approach
  • Forecasting dryland vegetation condition months in advance through satellite data assimilation
  • Connectivity as an emergent property of geomorphic systems
  • Topographic variation in soil erosion and accumulation determined with meteoric Be-10
  • A mechanical-dielectric-high frequency acoustic sensor fusion for soil physical characterization
  • A new method to analyse the soil movement during tillage operations using a novel digital image processing algorithm
  • Managing for soil carbon sequestration: Let’s get realistic