Project

Using Big Data and Machine learning in agricultural and forest applications

Publisher

Supervisor

Location

Greater Copenhagen area

The information from large remote sensing time series can be exploited in a Big Data framework to improve forecasting models of eco-hydrological variables at regional scales, understand vulnerability of ecosystems to climatic extremes (droughts, temperature), quantify the effects of land use changes on the hydrological cycle and forecast agricultural products including prices.

In the project, machine learning algorithms (e.g. tensor decomposition, random forest) can be used with MODIS, Sentinel, OCO-2 (plant fluorescence) or GRACE satellite datasets together with climatic products (ECMWF).

Different applications can be considered depending on students’ interest, such as gap filling of time series due to cloud cover, estimate risk of fires, forecasting of prices of wine and olive oil from high value regions, or short term forecasting of crop yields or water use.

 The project is part of the FORWARD European project. Collaboration with companies  is possible (DHI-Gras).

In collaboration with

DHI Gras

Requirements

programming in Python, Matlab

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Contact

Company / Organization

DTU Miljø

Name

Monica Garcia

Position

Lektor

Mail

mgarc@env.dtu.dk

Supervisor info

Artificial Intelligence and Data

Supervisor

Monica Garcia

Co-supervisors

Andreas Baum

ECTS credits

25 - 35

Type

BSc project, MSc thesis

BSc in Earth and Space Physics and Engineering

Supervisor

Monica Garcia

Co-supervisors

Andreas Baum

ECTS credits

25 - 35

Type

BSc project, MSc thesis

BSc in Environmental Engineering

Supervisor

Monica Garcia

Co-supervisors

Andreas Baum

ECTS credits

25 - 35

Type

BSc project, MSc thesis

MSc in Computer Science and Engineering

Supervisor

Monica Garcia

Co-supervisors

Andreas Baum

ECTS credits

25 - 35

Type

BSc project, MSc thesis

Msc in Earth and Space Physics and Engineering

Supervisor

Monica Garcia

Co-supervisors

Andreas Baum

ECTS credits

25 - 35

Type

BSc project, MSc thesis

MSc in Environmental Engineering

Supervisor

Monica Garcia

Co-supervisors

Andreas Baum

ECTS credits

25 - 35

Type

BSc project, MSc thesis

Technical University of Denmark

For almost two centuries DTU, Technical University of Denmark, has been dedicated to fulfilling the vision of H.C. Ørsted – the father of electromagnetism – who founded the university in 1829 to develop and create value using the natural sciences and the technical sciences to benefit society.


Today, DTU is ranked as one of the foremost technical universities in Europe, continues to set new records in the number of publications, and persistently increases and develops our partnerships with industry, and assignments accomplished by DTU’s public sector consultancy.

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Anker Engelunds Vej 1
Bygning 101A
2800 Kgs. Lyngby

Denmark



Tlf. (+45) 45 25 25 25

CVR-nr. 30 06 09 46

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