0000000000329766

AUTHOR

Rami Saad

showing 3 related works from this author

Incorporating stand level risk management options into forest decision support systems

2018

Aim of study:  To examine methods of incorporating risk and uncertainty to stand level forest decisions. Area of study: A case study examines a small forest holding from Jonkoping, Sweden. Material and methods: We incorporate empirically estimated uncertainty into the simulation through a Monte Carlo approach when simulating the forest stands for the next 100 years. For the iterations of the Monte Carlo approach, errors were incorporated into the input data which was simulated according to the Heureka decision support system. Both the Value at Risk and the Conditional Value at Risk of the net present value are evaluated for each simulated stand. Main results: Visual representation of the er…

Decision support systemOperations researchComputer scienceForest management0211 other engineering and technologiesforest managementSoil Science02 engineering and technologyrisk preferencesvalue at riskconditional value at risklcsh:ForestryriskitEcology Evolution Behavior and SystematicsRisk management040101 forestry021103 operations researchForest inventoryPresent valuebusiness.industrymetsänkäsittelyEnvironmental resource managementInformation technologyForestryrisk preferences; forest management; inventory error; value at risk; conditional value at risk04 agricultural and veterinary sciencesExpected shortfalllcsh:SD1-669.50401 agriculture forestry and fisheriesmetsänhoitoriskianalyysibusinessinventory errorValue at riskForest Systems
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Potential of using data assimilation to support forest planning

2017

Uncertainty in forest information typically results in economic and ecological losses as a consequence of suboptimal management decisions. Several techniques have been proposed to handle such uncertainties. However, these techniques are often complex and costly. Data assimilation (DA) has recently been advocated as a tool that may reduce the uncertainty, thereby improving the quality of forest planning results. It offers an opportunity to make use of all new sources of information in a systematic way and thus provides more accurate and up-to-date information to forest planning. In this study, we refer to literature on handling uncertainties in forest planning, as well as related literature…

0106 biological sciencesForest planningGlobal and Planetary Change010504 meteorology & atmospheric sciencesEcologyOperations researchProcess (engineering)Computer sciencemedia_common.quotation_subjectForestry01 natural sciencesBayesian statisticsData assimilationStochastic optimizationQuality (business)010606 plant biology & botany0105 earth and related environmental sciencesmedia_commonCanadian Journal of Forest Research
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Potential of using data assimilation to support forest planning

2017

Uncertainty in forest information typically results in economic and ecological losses as a consequence of suboptimal management decisions. Several techniques have been proposed to handle such uncertainties. However, these techniques are often complex and costly. Data assimilation (DA) has recently been advocated as a tool that may reduce the uncertainty, thereby improving the quality of forest planning results. It offers an opportunity to make use of all new sources of information in a systematic way and thus provides more accurate and up-to-date information to forest planning. In this study, we refer to literature on handling uncertainties in forest planning, as well as related literature …

optimointibayesilainen menetelmäsuboptimal lossmetsäsuunnittelukaukokartoitusepävarmuus
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