Maud Loireau

Linking Spatialized Indicators of Desertification Risks with Observed Land Use/Land Cover Change: An Operational Monitoring System of Desertification

The need of useful information for decision-makers to fight against desertification in Tunisian dry zones leads to conceive assessing and monitoring systems that can supply synthetic indicators. These latter should integrate socioeconomic and environmental dimensions with their spatial and temporal diversity at the local scale. This paper proposes an example of information system entitled SIELO (information system for operational desertification monitoring at the local scale). This system attempts to create the link between i) spatialized indicators of desertification risks, built in connection with the systematic complexity of desertification and ii) observed Land Use/ Land Cover (LU/LC) Change. The first type of data arises from pre-existing environmental model: LEIS model (Local Environmental Information System). The second type of data is extracted from satellite images acquired according to regular time steps. The proposed approach is based also on the spatializing of knowledge, via the ‘‘landscape’’ tool in particular. We illustrate the feasibility and the operational effectiveness of a developed software prototype (SIELO v1.0) with an initial application in a Tunisian dry zone. This system showed that it has the capacity to feed an operational monitoring of desertification according to the state of LU/LC directly observed or measured in several dates. Then, it can be useful for the decision-makers in their programs of fighting against desertification, but also to manage uncertainties in southeastern Tunisia, especially climate variability and climate change.

Vulnerability of natural resources in Tunisian arid zones facing climate change and human pressure : toward better target actions to combat desertification

The main challenges of Tunisian arid areas is better understand desertification and better adapt decisions to uncertainties that arise in complex interactions between the socio-economic and biophysical dynamics at different spatial and temporal scales. This understanding is increasingly necessary to better target actions and improve coping strategies. The objective of this work is to assess the vulnerability of natural resources and the risk of desertification at the local scale, in a case study (Oum Zessar watershed) located in the south-east of Tunisia. The assessment is carried out through an analysis of different human and biophysical causes and driving forces, such as natural resources uses and climate change. It is based on geographical (landscape), integrated (socio-economy, biophysics) and multi-actors (research-decision) approaches, associated with reproducible methods and models to assess the risk of desertification, and to better target future combating actions. The work led to the development of desertification risk indexes (based on spatial integration of biophysical and socio-economic functioning through modeling), facing several scenarios of climate change and human pressure. It shows that the same level of risk in one place or another may have differentiated causes, which could help public policy in their fighting against desertification.

Conceptual Analysis of Climate Change in the Light of Society-Environment Relationships: Observatories Closer to Both Systems and Societies

This chapter focuses on climate change, including the acuity of both scientific and social issues, which questions the future of humanity. We adopt a systemic reasoning that provides objectivity to the analysis. We represent society-environment relationships, and analyze climate global systemic functioning and its global scale connection to geographical imprints . In this conceptual systemic framework, we position an observatory , which observes, analyses, reports on facts, and enhances democratic processes by providing sound (scientific, accurate, unbiased) information to debate. We note the consistency of systemic and ethical approaches; thereby scientifically strengthening and justifying the latter if this was necessary. They converge on the proposal of a “System World” where humans as one whole would be conscious of the global systemics, responsible and fair players, and aware of the part they can play in climate regulation. The contribution of every single individual adds to the global effort, and acknowledging how they contribute to scaling climate regulation up and down would also promote greater equity and a better shared future.

A multilayer perceptron model for the correlation between satellite data and soil vulnerability in the Ferlo, Senegal

ABSTRACT Soil erosion processes which contribute to desertification and land degradation, constitute major environmental and social issues for the coming decades. This is particularly true in arid areas where rural populations mostly depend on soil ability to support crop production. Assessment of soil erosion across large and quite diverse areas is very difficult but crucial for planning and management of the natural resources. The purpose of this paper is to investigate a prediction model for soil vulnerability to erosion based on the use of the information contained in satellite images. Based on neural networks models, the used approach in this paper aims at checking a correlation between the digital content of satellite images and soil vulnerability factors: erosivity (R), the soil erodibility (K), and the slope length and steepness (LS); vulnerability (V) as described in the RUSLE model. Significant results have been obtained for R and K factors. This promising pilot study was conducted in South Ferlo, Senegal, a region with Sahelian environmental characteristics. Graphical Abstract

Observatoire scientifique en appui aux gestionnaires de territoire, entre abstraction OSAGE et réalité ROSELT/OSS

A partir de la description formelle des concepts «xa0OSAGExa0» (Observatoire Scientifique en Appui aux GEstionnaires de territoire) dans ses dimensions scientifique, technique et organisationnelle, nous analysons l’experience concrete et specifique de l’observatoire ROSELT/OSS (Reseau d’observatoires de surveillance ecologique a long terme/Observatoire du Sahara et du Sahel) menee depuis 1992 en matiere de lutte contre la desertification dans le circum-Sahara. Cette confrontation modele abstrait/modele concret (ou «xa0instancexa0») permet de tester la validite du modele abstrait (OSAGE), mesurer sa richesse et ses difficultes de mise en œuvre et l’enrichir, tout en offrant un cadre formel pour analyser ROSELT/OSS et mesurer son niveau de conformite au modele OSAGE.

SIEL : système intégré pour la modélisation et l’évaluation du risque de désertification

La lutte contre la desertification est une priorite, notamment dans les pays du Sud ou vivent 75% de l’humanite et ou les trois quarts de la population travaillent dans le secteur agricole. A partir d’une reflexion menee sur la caracterisation et spatialisation des pratiques (agricoles) et des ressources naturelles en interaction sur un espace donne, l’article decrit une chaine de traitements thematiques pour modeliser des unites de paysages ruraux et les causes et intensite du risque de desertification afferents, ainsi que la plateforme logicielle geomatique qui la met en œuvre. Via une interface utilisateur accompagnee d’une aide documentee, le logiciel SIEL permet le parametrage et l’execution de la chaine de traitements. Les resultats obtenus sur des exemples illustratifs dans plusieurs observatoires circum-sahariens sont presentes. Ils ouvrent la voie aux discussions sur les perspectives et potentialites du SIEL dans les observatoires en appui a l’aide a la decision pour la lutte contre la desertification.

Un système d’information pour le suivi opérationnel de la désertification à l’échelle locale (prototype SIELO)

Developper des modeles capables de fournir des indicateurs integrant des dimensions socio-economiques et environnementales dans leur diversite spatiale et temporelle, traitant de phenomenes a l’echelle locale, et mobilisables dans des systemes d’aide a la decision, reste un challenge d’actualite pour comprendre, spatialiser, suivre, evaluer et anticiper les dynamiques complexes de la desertification. Cet article presente la demarche modelisatrice imaginee, et la plateforme logicielle prototype intitulee « systeme d’information pour le suivi operationnel de la desertification a l’echelle locale » (SIELO) pour repondre a cet enjeu scientifique. Ce systeme tente de creer le lien entre : i) des indicateurs spatialises de risque de desertification prenant en compte la complexite systemique de la desertification ; et ii) le Land Cover Change observe. Le premier type de donnees est issu de modeles systemiques preexistants dans le SIEL. Le second type de donnees est extrait d’images satellites acquises selon des pas de temps reguliers. La demarche s’appuie sur des approches de spatialisation des connaissances, qui mobilise le « paysage » notamment. Dans cet article, nous mettons l’accent sur la description de la demarche proposee pour etablir ce lien, et sur les specificites qui la mettent en capacite d’alimenter un suivi operationnel de la desertification dans le cadre d’observatoires a l’echelle locale. Nous illustrons la faisabilite et l’operationnalite de sa mise en œuvre avec une premiere application a une zone aride tunisienne via un logiciel prototype developpe.

Integrated Environmental and Socio-economic Modeling Using LEIS for Desertification Monitoring and Assessment in Menzel Habib Observatory (South Tunisia)

In the framework of the implementation of the national action plan (NAP) as part of the UNCCD, a network of observatories for the assessment and monitoring of desertification has been established, covering the main agro-ecological zones of Tunisia. Menzel Habib represents one of the main observatories located in a typical arid zone threatened by desertification. This site is also part of the ROSELT3/OSS4 network and the arid zones observatory implemented by IRA within the framework of the national monitoring system of desertification coordinated by the national focal point of the UNCCD. It is in this framework that the GIS-based model LEIS (Local Environmental Information System) (in French known as SIEL) developed by the ROSELT team in Montpellier (Roselt/OSS, DS3, 2004) was applied to this observatory. The data used were issued from achieved and on-going multidisciplinary monitoring of the observatory covering the biophysical (soil, water, climate, vegetation) and the agro-socio-economic (population, agricul ture and pasture practices, land uses, etc.) aspects. Three types of information were used: remotely sensed data (satellite images), field measurements (vegetation bio-mass, yields, GPS, etc.), and socio-economic surveys (households, income, activi ties, etc.). Multiple scenarios have been conducted to assess the impact of changing one or many parameters (population, livestock, etc.). In fact, the final objective of the model is to place at the disposal of the various actors of development, research ers and technicians, a Spatial Decision Support System (SDSS) for planning and monitoring in plans to combat desertification and natural resources management in the dry areas.