Fabio Oriani

Fabio Oriani
Agroscope · Agroecology and Environment

PhD
Geostatistical analysis and modelling, remote sensing, hydroclimatology, vegetation distribution

About

25
Publications
8,660
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
355
Citations
Introduction
My main research topic is the geostatistical analysis and modelling of climate and remote sensing data. I am also interested in stochastic hydrology, vegetation distrubution, and paleoclimate.
Additional affiliations
October 2013 - January 2014
UNSW Sydney
Position
  • Fellow
September 2017 - present
University of Lausanne
Position
  • PostDoc Position
Description
  • Stochastic hydrology, geostatistics, remote sensing.
March 2016 - August 2017
Geological Survey of Denmark and Greenland
Position
  • PostDoc Position
Description
  • Stochastic hydrology, multiple point geostatistics

Publications

Publications (25)
Article
Full-text available
Very high-resolution satellite imagery from the latest generation commercial platforms provides an unprecedented capacity for imaging the Earth with very high spatial detail. However, these data are generally expensive, particularly if large areas or temporal sequences are required. In recent years, lower quality imagery has been enabled through th...
Article
Missing rainfall data are a major limitation for distributed hydrological modeling and climate studies. Practitioners need reliable approaches that can be employed on a daily basis, often with too limited data in space to feed complex predictive models. In this study we compare different automatic approaches for missing data imputation including ge...
Preprint
Full-text available
Accurate precipitation estimation with high temporal resolution is crucial to monitor and predict natural hazards in mountainous regions. While rain gauges are the reliable source of precipitation data, they lack continuous fine resolution at desired locations, such as avalanche and landslide sites. In this context, temporal disaggregation approach...
Article
Full-text available
Modern and fossil pollen data are widely used in paleoenvironmental research to characterize past environmental changes in a given location. However, their discrete and discontinuous nature can limit the inferences that can be made from them. Deriving continuous spatial maps of the pollen presence from point-based datasets would enable more robust...
Preprint
Full-text available
Modern and fossil pollen data are widely used in paleoenvironmental research to characterise past environmental changes in a given location. However, their discrete and discontinuous nature can limit the inferences that can be made from them. In contrasts, deriving continuous spatial maps of the pollen presence from point-based datasets would enabl...
Preprint
Full-text available
Modern and fossil pollen data are widely used in paleoenvironmental research to characterise past environmental changes in a given location. However, their discrete and discontinuous nature can limit the inferences that can be made from them. In contrasts, deriving continuous spatial maps of the pollen presence from point-based datasets would enabl...
Poster
Full-text available
We present here a novel image analysis approach to detect and count laminae in geoscientific imagery, called WlCount.
Article
Full-text available
The manual identification and count of laminae in layered textures is a common practice in the study of geological records, which can be time consuming and carry large uncertainty for dense or disturbed lamina textures. We present here a novel image analysis approach to detect and count laminae in geoscientific imagery, called WlCount. Based on Dyn...
Article
Variation of sulphur in annually laminated stalagmites can be used to infer the impact of past volcanic activities, anthropogenic pollution, and climate change due to increased bushfire activity. The synchrotron radiation micro-X-Ray fluorescence (SR-XRF) microprobe is a powerful tool to analyse and image sulphur recorded in stalagmites with microm...
Preprint
Full-text available
The manual identification and count of laminae in layered textures is a common practice in the study of geological records, which can be time consuming and carry large uncertainty for dense or disturbed lamina textures. We present here a novel image analysis approach to detect and count laminae in geoscientific imagery, called WlCount. Based on Dyn...
Article
Full-text available
In this paper, we compare the performance of two data-driven algorithms to deal with an automatic classification problem in geomorphology: Direct Sampling (DS) and Random Forest (RF). The main goal is to provide a semi-automated procedure for the geomorphological mapping of alpine environments, using a manually mapped zone as training dataset and p...
Article
Quantifying rainfall recharge thresholds, including their spatial and temporal heterogeneity, is of fundamental importance to better understand recharge processes and improving estimation of recharge rates. Caves provide a unique observatory into the percolation of water from the surface to the water table at the timescale of individual rainfall re...
Article
Complete hydrological time series are necessary for water resources management and modeling. This can be challenging in data scarce environments where data gaps are ubiquitous. In many applications, repetitive gaps can have unfortunate consequences including ineffective model calibration, unreliable timing of peak flows, and biased statistics. Here...
Code
DS_pytools is apython package to control the DeeSse software for MultiplePoint Statistics (MPS) simulation (http://www.randlab.org/). It contains functions to write and read .gslib files used by DS to read the training image and results.
Article
Full-text available
Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for...
Code
A basic implementation of the Genetic Algorithm for optimization of mixed-integer problems. Set up the algorithm in the "OPTIMIZATION PARAMETERS" section. For usage instruction see the help in the optimize.py and the usage examples in optim_test.py.
Article
The quantification of spatial rainfall is critical for distributed hydrological modeling. Rainfall spatial patterns generated by similar weather conditions can be extremely diverse. This variability can have a significant impact on hydrological processes. Stochastic simulation allows generating multiple realizations of spatial rainfall or filling m...
Article
The direct sampling (DS) multiple-point statistical technique is proposed as a non-parametric missing data simulator for hydrological flow rate time-series. The algorithm makes use of the patterns contained inside a training data set to reproduce the complexity of the missing data. The proposed setup is tested in the reconstruction of a flow rate t...
Poster
Full-text available
Rainfall amount is one of the most sensitive inputs to distributed hydrological models. Its spatial representation is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the 10-km-grid rainfall product provided by the Danish Meteorological Instit...
Article
Full-text available
The direct sampling technique, belonging to the family of multiple-point statistics, is proposed as a nonparametric alternative to the classical autoregressive and Markov-chain-based models for daily rainfall time-series simulation. The algorithm makes use of the patterns contained inside the training image (the past rainfall record) to reproduce t...
Article
Full-text available
The direct sampling technique, belonging to the family of multiple-point statistics, is proposed as a nonparametric alternative to the classical autoregressive and Markov-chain-based models for daily rainfall time-series simulation. The algorithm makes use of the patterns contained inside the training image (the past rainfall record) to reproduce t...
Code
Matlab code to compute the Autocorrelation and Partial Autocorrelation function on time-series containing missing data (nans).
Article
Sand lenses at various spatial scales are recognized to add heterogeneity to glacial sediments. They have high hydraulic conductivities relative to the surrounding till matrix and may affect the advective transport of water and contaminants in clayey till settings. Sand lenses were investigated on till outcrops producing binary images of geological...

Questions

Questions (2)
Question
I am looking for a free software, possibly linux compatible, for orthorectification of satellite images using both DEM and sensor data. Any suggestions?
I am currently using OTB but I am not getting good results.
Best,
Fabio
Question
The title is self-explanatory, please enlighten me!

Network

Cited By