The Use of Forest Decision Support Systems in Finland
Notice bibliographique
Résumé
Computer-based tools for supporting forest management. The experience and the expertise world-wide answers a call from both the research and the professional communities for a synthesis of current knowledge about the use of computerized tools in forest management planning. According to the aims of the Forest Management Decision Support Systems (FORSYS) (http://fp0804.emu.ee/) this synthesis is a critical success factor to develop a comprehensive quality reference for forest management decision support systems. The emphasis of the book is on identifying and assessing the support provided by computerized tools to enhance forest management planning in real-world contexts. The book thus identifies the management planning problems that prevail world-wide to discuss the architecture and the components of the tools used to address them. Of importance is the report of architecture approaches, models and methods, knowledge management and participatory planning techniques used to address specific management planning problems. We think that this synthesis may provide effective support to research and outreach activities that focus on the development of forest management decision support systems. It may contribute further to support forest managers when defining the requirements for a tool that best meets their needs. The first chapter of the book provides an introduction to the use of decision support systems in the forest sector and lays out the FORSYS framework for reporting the experience and expertise acquired in each country. Emphasis is on the FORSYS ontology to facilitate the sharing of experiences needed to characterize and evaluate the use of computerized tools when addressing forest management planning problems. The twenty six country reports share a structure designed to underline a problem-centric focus. Specifically, they all start with the identification of the management planning problems that are prevalent in the country and they move on to the characterization and assessment of the computerized tools used to address them. The reports were led by researchers with background and expertise in areas that range from ecological modeling to forest modeling, management planning and information and communication technology development. They benefited from the input provided by forest practitioners and by organizations that are responsible for developing and implementing forest management plans. A conclusions chapter highlights the success of bringing together such a wide range of disciplines and perspectives. This book benefited from voluntary contributions by 94 authors and from the involvement of several forest stakeholders from twenty six countries in Europe, North and South America, Africa and Asia over a three-year period. We, the chair of FORSYS and the editorial committee of the publication, acknowledge and thank for the valuable contributions from all authors, editors, stakeholders and FORSYS actors involved in this project.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».