[Defended thesis] Urcel Kalenga Tshingomba

[Defended thesis] Urcel Kalenga Tshingomba : Definition, Design and Evaluation of a decision support system for pastoralism

Urcel defended his PhD on 28 March 2023 @ Maison de la télédétection (Salle Saltus, 500 rue Jean François Breton, Montpellier)

Definition, Design and Evaluation of a decision support system for pastoralism

Hello, my name is Urcel Kalenga Tshingomba, doctoral student at AgroParisTech in Montpellier. I am an agricultural engineer by training (University of Lubumbashi, DR Congo), and have a degree in Geomatics (AgroParisTech).
I've always had a passion for all aspects of agriculture, particularly animal production. My thesis focuses on heterogeneous data processing applied to Mediterranean pastoralism. I'm working on the implementation of an information system to offer an operational service to breeders and technicians for their decision-making.

  • Starting date: Decembrer 2019
  • University : MUSE Montpellier Université d’Excellence / L'Institut Agro
  • PhD school:  GAIA, Montpellier
  • Scientific field: Geomatics
  • Thesis management: Magali Jouven (L'Institut Agro, Selmet), Maguelonne Teisseire (Inrae, Tetis)
  • Thesis supervisors: Lucile Sautot (AgroParisTech, Tetis)
  • Funding: #DigitAg – AgroParisTech
  • #DigitAg : Cofunded PhD – Axes 4 & 5 , Challenge 4

Keywords: Pastoralism, Heterogeneous data, Data warehouse

Abstract: Pastoral systems are widely recognized for their social, environmental and cultural value. They also represent a type of livestock farming system consistent with agroecology. Their sustainability depends on their ability to cope with wide spatio-temporal variations in the availability of pastoral resources. Thus, both animals and farmers need to constantly adapt their strategies to the changing context. Decision making and diagnosis in pastoral systems rely on the analysis of heterogeneous data from various sources (local and scientific knowledge, direct observations and technical references, embarked sensors such as GPS). Such heterogeneous data is more or less available to the farmer or technical advisor, and its comprehensive analysis is carried out on an informal basis and with varying success. The digital age offers the opportunity to link data that could not be previously correlated. What are the methodological solutions in Computer Science to manipulate and link such data? How to evaluate and measure the interest and the impact of this information for farmers and technical advisors? The proposed work aims at addressing these issues by (1) defining a data warehouse model allowing the analysis and cross-referencing of heterogeneous data (digital platform offering new services to farmers according to spatial dimensions, temporal and thematic); and (2) carrying out an analysis of the contribution of these new types of information in terms of lever for innovation for pastoral livestock farming systems, at several levels and with a suitable multicriteria analysis

Jury compound:

François PINET, Directeur de recherche, INRAE                                                   Rapporteur

Gilles BRUNSCHWIG, Professeur, VetAgroSup                                                     Rapporteur

Elvira SALES-BAPTISTA, Professeure, Université d'Evora                                    Examinatrice

Carmen GERVET, Professeure, Université de Montpellier                                  Examinatrice

Eliel GONZALEZ-GARCIA, Chargé de recherche, INRAE                                       Examinateur

Pierre-Yves VION, ICPEF, AgroParisTech                                                                 Invité

See also

Upload the thesis manuscript

Papers in international journals

Urcel Kalenga, Bassira Djibo, Lucile Sautot, Maguelonne Teisseire, Magali Jouven. A spatialised information system to support decisions regarding grazing management in mountainous and Mediterranean rangelands. Computers and Electronics in Agriculture, Elsevier, In press, 198 (issue C), pp.107100. ⟨10.1016/j.compag.2022.107100⟩⟨hal-03656295⟩

Modification date: 16 May 2024 | Publication date: 19 August 2022 | By: ZM