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Hindi Research Article
Linking Spatialized Indicators of Desertification Risks with Observed Land Use/Land Cover Change: An Operational Monitoring System of Desertification
| Fetoui M1*, Loireau M2, Essifi B1, Chouikhi F1, Tarhouni M1, Sghaier M1, Laques AE2 and Dérioz P2 | |
| 1Institute of Arid Regions, Medinine, Tunisia | |
| 2Institute of Research and Development, UMR 228 SPACE-DEV, House of Remote Sensing IRD pole, 500, rue JF Breton, Montpellier cedex 05, France | |
| Corresponding Author : | Fetoui M Institute of Arid Regions Medinine, Tunisia Tel: (+216) 98 280 844 E-mail: mondher_ga@yahoo.fr |
| Received January 07, 2015; Accepted January 19, 2015; Published January 29, 2015 | |
| Citation: Fetoui M, Loireau M, Essifi B, Chouikhi F, Tarhouni M, et al. (2015) Linking Spatialized Indicators of Desertification Risks with Observed Land Use/ Land Cover Change: An Operational Monitoring System of Desertification. J Earth Sci Clim Change 6:252. doi: 10.4172/2157-7617.1000252 | |
| Copyright: © 2015 Fetoui M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
Abstract
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.
