Annamaria Castrignano

Professor

Italy

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Professor Annamaria Castrignano is a faculty member at the University G. D'Annunzio of Chieti-Pescara, Italy. Her research focuses on various aspects of geostatistics, including groundwater salinity and quality modeling, soil spatial variability, and the integration of remote sensing data for precision agriculture. Recent publications highlight her work on assessing soil functions and addressing environmental challenges using advanced statistical approaches.

Articles (11)

Year:

2025

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Collaborators (7)

Diego Di Curzio

Delft University of Technology

NETHERLANDS

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Federico Valerio MORESI

Adjunct Professor

University of Tuscia

ITALY

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Belmonte Antonella

Istituto per il Rilevamento Elettromagnetico dell'Ambiente Consiglio Nazionale delle Ricerche

ITALY

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Giuseppe Scarascia Mugnozza

University of Tuscia

ITALY

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Franco Nigro

Full Professor

University of Bari Aldo Moro

ITALY

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Sergio Rusi

Prof

University "G. d'Annunzio"

ITALY

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Nunzio Romano

Full Professor

Università degli Studi di Napoli Federico II

ITALY

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Annamaria Castrignano

Research Interests

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About

Articles (11)

An Integrated Statistical, Geostatistical and Hydrogeological Approach for Assessing and Modelling Groundwater Salinity and Quality in Nile Delta Aquifer

Improving the Spatial Prediction of Sand Content in Forest Soils Using a Multivariate Geostatistical Analysis of LiDAR and Hyperspectral Data

Scale-Dependent Field Partition Based on Water Retention Functional Data

Regional-scale assessment of soil functions and resilience indicators: Accounting for change of support to estimate primary soil properties and their uncertainty

Use of Geostatistics for Multi-Scale Spatial Modeling of Xylella fastidiosa subsp. pauca (Xfp) Infection with Unmanned Aerial Vehicle Image

A multivariate non-parametric approach for estimating probability of exceeding the local natural background level of arsenic in the aquifers of Calabria region (Southern Italy)

Geostatistical Modelling of Soil Spatial Variability by Fusing Drone-Based Multispectral Data, Ground-Based Hyperspectral and Sample Data with Change of Support

Potential of GPR data fusion with hyperspectral data for precision agriculture of the future

A combined geostatistical approach of data fusion and stochastic simulation for probabilistic assessment of shallow water table depth risk

A geostatistical fusion approach using UAV data for probabilistic estimation of Xylella fastidiosa subsp. pauca infection in olive trees

Assessment of the hyperspectral data analysis as a tool to diagnose xylella fastidiosa in the asymptomatic leaves of olive plants

Collaborators (7)

Diego Di Curzio

Federico Valerio MORESI

Belmonte Antonella

Giuseppe Scarascia Mugnozza

Franco Nigro

Sergio Rusi

Nunzio Romano

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