Eric Ariel L. Salas The scientific community hides me behind the initials EAL Salas

We Won the Best Paper Award 2022

By EAL Salas on October 20, 2022October 20, 2022

The International Journal of Image and Data Fusion (IJIDF) has presented my colleagues and I the Best Paper Award 2022 for our paper “Mapping crop types in fragmented arable landscapesContinue readingWe Won the Best Paper Award 2022

R Code for Mapping Dissolved Oxygen Using Random Forest (RF) and Support Vector Machine (SVM)

By EAL Salas on May 6, 2022May 6, 2022

First, I will give credit to the Soil Organic Carbon Mapping Cookbook for making the original R code available for use to the public. In this paper, I did aContinue readingR Code for Mapping Dissolved Oxygen Using Random Forest (RF) and Support Vector Machine (SVM)

Potential of mapping dissolved oxygen in the Little Miami River using Sentinel-2 images and machine learning algorithms

By EAL Salas on May 2, 2022May 2, 2022

Abstract: Dissolved oxygen (DO) is one of the most significant indicators of water quality in the inland water systems. Maintaining DO monitoring systems is time and money consuming since inContinue readingPotential of mapping dissolved oxygen in the Little Miami River using Sentinel-2 images and machine learning algorithms

Modelling Land Use and Land Cover in the Transboundary Mono River Catchment of Togo and Benin Using Markov Chain and Stakeholder’s Perspectives

By EAL Salas on March 31, 2022March 31, 2022

Abstract Integrating both modeling approach and stakeholders’ perspectives to derive past and future trends of land use land cover (LULC) is a key to creating more realistic results on LULCContinue readingModelling Land Use and Land Cover in the Transboundary Mono River Catchment of Togo and Benin Using Markov Chain and Stakeholder’s Perspectives

Conditional Latin Hypercube Sampling (cLHS) R-Code to Sample Points From Raster Images

By EAL Salas on November 11, 2021May 1, 2025

The conditional Latin Hypercube Sampling (cLHS) is a prominent model-based sampling method that employs a stratified random technique to optimize sample selection using continuous and/or categorical covariates as input. TheContinue readingConditional Latin Hypercube Sampling (cLHS) R-Code to Sample Points From Raster Images

Eric Ariel L. Salas

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