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

International journal of climatology, 2018-11, Vol.38 (14), p.5430-5440

2018

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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 (Basel, Switzerland), 2020-09, Vol.12 (17), p.2747

2020

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

International journal of applied earth observation and geoinformation, 2020-06, Vol.88, p.102051, Article 102051

2020

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

Scientific reports, 2020-10, Vol.10 (1), p.17188, Article 17188

2020

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Remote Sensing Applications in Sugarcane Cultivation: A Review

Remote sensing (Basel, Switzerland), 2021-10, Vol.13 (20), p.4040

2021

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

Remote sensing (Basel, Switzerland), 2019-03, Vol.11 (5), p.575

2019

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A multi-decadal 1 km gridded database of continental-scale spring onset products

Scientific data, 2024-08, Vol.11 (1), p.905-11

2024

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

Remote sensing (Basel, Switzerland), 2018-05, Vol.10 (5), p.729

2018

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

International journal of applied earth observation and geoinformation, 2019-11, Vol.83, p.101913, Article 101913

2019

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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

Remote sensing (Basel, Switzerland), 2019-06, Vol.11 (12), p.1489

2019

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

Annals of the American Association of Geographers, 2018-01, Vol.108 (1), p.71-87

2018

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European Union crop map 2022: Earth observation’s 10-meter dive into Europe’s crop tapestry

Scientific data, 2024-09, Vol.11 (1), p.1048-23, Article 1048

2024

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

ISPRS international journal of geo-information, 2019-01, Vol.8 (2), p.55

2019

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

Frontiers in environmental science, 2022-05, Vol.10

2022

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

Remote sensing of environment, 2020-09, Vol.247, p.111901-111901, Article 111901

2020

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

International archives of the photogrammetry, remote sensing and spatial information sciences., 2017-09, Vol.XLII-2/W7, p.1387-1391

2017

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Development and analysis of spring plant phenology products: 36 years of 1-km grids over the conterminous US

Agricultural and forest meteorology, 2018-11, Vol.262, p.34-41

2018

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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 : IJGIS, 2022-12, Vol.36 (12), p.2473-2495

2022

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

New biotechnology, 2024-07, Vol.81, p.20-31

2024

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

International journal of biometeorology, 2020-03, Vol.64 (3), p.409-421

2020

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Spectral clustering with the probabilistic cluster kernel

Neurocomputing (Amsterdam), 2015-02, Vol.149, p.1299-1304

2015

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

Journal of open source software, 2022-04, Vol.7 (72), p.4032

2022

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

IEEE transactions on big data, 2020-09, Vol.6 (3), p.583-593

2020

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HyperLabelMe : A Web Platform for Benchmarking Remote-Sensing Image Classifiers

IEEE geoscience and remote sensing magazine, 2017-12, Vol.5 (4), p.79-85

2017

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Using a Deployable Analysis Environment to Study Continental-Scale Phenology at High-Spatial Resolution

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2024, p.996-999

2024

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

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

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

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

Remote Sensing Applications in Sugarcane Cultivation: A Review

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

A multi-decadal 1 km gridded database of continental-scale spring onset products

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

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

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

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

European Union crop map 2022: Earth observation’s 10-meter dive into Europe’s crop tapestry

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

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

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

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

Development and analysis of spring plant phenology products: 36 years of 1-km grids over the conterminous US

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

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

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

Spectral clustering with the probabilistic cluster kernel

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

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

HyperLabelMe : A Web Platform for Benchmarking Remote-Sensing Image Classifiers

Using a Deployable Analysis Environment to Study Continental-Scale Phenology at High-Spatial Resolution

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