Communicating a vision of the future with optimization models and virtual landscapes : An application to community management of the Jalapa watershed in Honduras
The demonstration presents the results of exploratory work on the communication of possible scenario outcomes to the population of a small watershed. This is done by combining optimization models with computer-generated images of future landscapes. Five scenarios (rapid population increase, sustainable forest management, an increase in agricultural productivity, a new credit programme and a payment for environmental services) were introduced into a linear proramming (LP) model which maximizes the total income of the watershed while finding the most profitable land use condition. The results of the model were fed into a virtual reality (VR) landscape rendering software that simulates the aspect of the watershed under given scenarios. The population were presented with realistic 'pictures' of the watershed based on the assumptions about the future. This included present and future roads, buildings, land use patterns and eroded hillsides. Animations were also generated which correspond to what an observer travelling through or flying over the landscape would see. Surprisingly, farmers have no problem grasping the profit maximization principle, and understand perfectly what would be the impact on the landscape. In fact, we found that VR helps to lower the level of abstraction typically associated with LP and GIS. VR animations reinforced the perceived realism of the simulated landscapes. This decision support tool will help communities forecast the impact of different collective actions such as new rules, new roads or adoption of new techniques on both their incomes and their landscapes.
| Main Authors: | , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
Ashgate Publishing
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| Subjects: | U10 - Informatique, mathématiques et statistiques, P01 - Conservation de la nature et ressources foncières, paysage, modèle mathématique, imagerie, impact sur l'environnement, technique de prévision, aide à la décision, population humaine, http://aims.fao.org/aos/agrovoc/c_4185, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_36760, http://aims.fao.org/aos/agrovoc/c_24420, http://aims.fao.org/aos/agrovoc/c_3041, http://aims.fao.org/aos/agrovoc/c_36897, http://aims.fao.org/aos/agrovoc/c_3683, http://aims.fao.org/aos/agrovoc/c_3651, |
| Online Access: | http://agritrop.cirad.fr/509395/ http://agritrop.cirad.fr/509395/1/ID509395.pdf |
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