Publicaciones (52) Publicaciones de EMMA IZQUIERDO VERDIGUIER

2024

  1. Learning vs. understanding: When does artificial intelligence outperform process-based modeling in soil organic carbon prediction?

    New Biotechnology, Vol. 81, pp. 20-31

  2. Within-season crop monitoring at continental scale utilizing new gap-filled Landsat temporal series

    International Journal of Digital Earth, Vol. 17, Núm. 1

2022

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

    International Journal of Geographical Information Science, Vol. 36, Núm. 12, pp. 2473-2495

  2. Satellite Analyses Unravel the Multi-Decadal Impact of Dam Management on Tropical Floodplain Vegetation

    Frontiers in Environmental Science, Vol. 10

2021

  1. GLOBAL UPSCALING OF THE MODIS LAND COVER WITH GOOGLE EARTH ENGINE AND LANDSAT DATA

    International Geoscience and Remote Sensing Symposium (IGARSS)

  2. Remote sensing applications in sugarcane cultivation: A review

    Remote Sensing, Vol. 13, Núm. 20

2020

  1. A Multiscale Random Forest Kernel for Land Cover Classification

    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 13, pp. 2842-2852

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

    International Journal of Applied Earth Observation and Geoinformation, Vol. 88

  3. Comparison of harmonic analysis of time series (HANTS) and multi-singular spectrum analysis (M-SSA) in reconstruction of long-gap missing data in NDVI time series

    Remote Sensing, Vol. 12, Núm. 17, pp. 1-22

  4. Down-Scaling Modis Vegetation Products with Landsat GAP Filled Surface Reflectance in Google Earth Engine

    International Geoscience and Remote Sensing Symposium (IGARSS)

  5. Exploring differences in spatial patterns and temporal trends of phenological models at continental scale using gridded temperature time-series

    International Journal of Biometeorology, Vol. 64, Núm. 3, pp. 409-421

  6. Land Cover Classification Using Extremely Randomized Trees: A Kernel Perspective

    IEEE Geoscience and Remote Sensing Letters, Vol. 17, Núm. 10, pp. 1702-1706

  7. Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources

    Information Fusion, Vol. 63, pp. 256-272

  8. Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud

    Remote Sensing of Environment, Vol. 247

  9. Understanding deep learning in land use classification based on Sentinel-2 time series

    Scientific Reports, Vol. 10, Núm. 1

2019

  1. Correction: Evaluating the performance of a random forest kernel for land cover classification [Remote Sensing, 11, (2019) (575)] DOI:10.3390/rs11050575

    Remote Sensing

  2. Dataset reduction techniques to speed up SVD analyses on big geo-datasets

    ISPRS International Journal of Geo-Information, Vol. 8, Núm. 2

  3. Evaluating the performance of a Random Forest Kernel for land cover classification

    Remote Sensing, Vol. 11, Núm. 5

  4. Growing stock volume from multi-temporal landsat imagery through google earth engine

    International Journal of Applied Earth Observation and Geoinformation, Vol. 83

2018

  1. A cloud-based multi-temporal ensemble classifier to map smallholder farming systems

    Remote Sensing, Vol. 10, Núm. 5