List of works - Emma Izquierdo-Verdiguier

A Cloud-Based Multi-Temporal Ensemble Classifier to Map Smallholder Farming Systems

scientific article published on 9 May 2018

A Multiscale Random Forest Kernel for Land Cover Classification

scientific article published in 2020

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing

scientific article published in June 2020

An interactive analysis of users, use and usability of phenological information

scientific article published on 23 March 2020

Area and Feature Guided Regularised Random Forest: a novel method for predictive modelling of binary phenomena. The case of illegal landfill in Canary Island

scientific article published on 9 June 2022

CGC: a Scalable Python Package for Co- and Tri-Clustering of Geodata Cubes

scientific article published on 10 April 2022

CGC: an open-source Python module for geospatial data clustering

scientific article published on 27 March 2022

CLUSTERING-BASED APPROACHES TO THE EXPLORATION OF SPATIO-TEMPORAL DATA

scientific article published on 14 September 2017

CLUSTERING-BASED APPROACHES TO THE EXPLORATION OF SPATIO-TEMPORAL DATA

Clustering Geodata Cubes (CGC) and Its Application to Phenological Datasets

scientific article published on 15 May 2023

Correction: Zafari, A.; Zurita-Milla, R.; Izquierdo-Verdiguier, E. Evaluating the Performance of a Random Forest Kernel for Land Cover Classification. Remote Sensing 2019, 11, 575

scientific article published on 24 June 2019

Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets

scientific article published on 26 January 2019

Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

scientific article published in January 2018

Evaluating the Performance of a Random Forest Kernel for Land Cover Classification

scientific article published on 8 March 2019

Exploring Spring Onset at Continental Scales: Mapping Phenoregions and Correlating Temperature and Satellite-Based Phenometrics

scientific article published in September 2020

False Spring over Europe: risk and uncertainties

scientific article published on 4 March 2021

Gross Primary Production and False Spring: a spatio-temporal analysis

scientific article published on 23 March 2020

Influence of source and scale of gridded temperature data on modelled spring onset patterns in the conterminous United States

scientific article published on 24 September 2018

Integrating support vector machines and random forests to classify crops in time series of Worldview-2 images

scientific article published on 4 October 2017

Introducing co-clustering for hyperspectral image analysis

scientific article published in July 2015

Land Cover Classification Using Extremely Randomized Trees: A Kernel Perspective

scientific article published in October 2020

Optimized Kernel Entropy Components

scientific article

List of works by Emma Izquierdo-Verdiguier

A Cloud-Based Multi-Temporal Ensemble Classifier to Map Smallholder Farming Systems

A Multiscale Random Forest Kernel for Land Cover Classification

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing

An interactive analysis of users, use and usability of phenological information

Area and Feature Guided Regularised Random Forest: a novel method for predictive modelling of binary phenomena. The case of illegal landfill in Canary Island

CGC: a Scalable Python Package for Co- and Tri-Clustering of Geodata Cubes

CGC: an open-source Python module for geospatial data clustering

CLUSTERING-BASED APPROACHES TO THE EXPLORATION OF SPATIO-TEMPORAL DATA

CLUSTERING-BASED APPROACHES TO THE EXPLORATION OF SPATIO-TEMPORAL DATA

Clustering Geodata Cubes (CGC) and Its Application to Phenological Datasets

Correction: Zafari, A.; Zurita-Milla, R.; Izquierdo-Verdiguier, E. Evaluating the Performance of a Random Forest Kernel for Land Cover Classification. Remote Sensing 2019, 11, 575

Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets

Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

Evaluating the Performance of a Random Forest Kernel for Land Cover Classification

Exploring Spring Onset at Continental Scales: Mapping Phenoregions and Correlating Temperature and Satellite-Based Phenometrics

False Spring over Europe: risk and uncertainties

Gross Primary Production and False Spring: a spatio-temporal analysis

Influence of source and scale of gridded temperature data on modelled spring onset patterns in the conterminous United States

Integrating support vector machines and random forests to classify crops in time series of Worldview-2 images

Introducing co-clustering for hyperspectral image analysis

Land Cover Classification Using Extremely Randomized Trees: A Kernel Perspective

Optimized Kernel Entropy Components

Semisupervised nonlinear feature extraction for image classification

Triclustering Georeferenced Time Series for Analyzing Patterns of Intra-Annual Variability in Temperature