WIS.2 – a sustainable forest management decision support system

Yazarlar

  • Christian Rosset Bern University of Applied Sciences, Swiss College of Agriculture, Switzerland
  • Jean-Philippe Schütz former ETH-Zürich, Brüggliäcker 37, 8050 Zürich, Switzerland
  • Mark Günter Bern University of Applied Sciences, Swiss College of Agriculture, Switzerland
  • Clotilde Gollut Bern University of Applied Sciences, Swiss College of Agriculture, Switzerland

Öz

WIS.2 is a DSS for monitoring and implementing the goal-oriented and sustainable management
of forest ecosystems, especially with regard to the integral management of signicant spatial and
temporal scales in forest ecosystems. WIS.2 considers multiple ecosystem goods and services in silvicultural
management and the implementation of silvicultural interventions, which are in accordance with the
Swiss silvicultural tradition. WIS.2 takes a top-down approach, starting with the entrepreneurial strategy,
and ending at short and mid-term interventions at stand level. WIS.2 structures the overall decision process
across multiple scales and provides decision support for each decision to be taken by organizing and
connecting available data and models.
WIS.2 is based on MS Access and ArcGIS View and is composed of dierent applications, each handling a
main aspect of the management of forest ecosystems. The tool is used at the level of higher education in
forest management in Switzerland. WIS.2, initially developed during 2001-2005 within the framework of a
PhD thesis at the ETH in Zurich (\Author" 2005a), has been successively improved through practical use
in more than 10 case studies in ve Swiss Cantons. The main challenge is now to advance from a prototype
to an easily available consolidated IT product.

Yayınlanmış

2014-09-30

Sayı

Bölüm

Special Section on Decision Support Tools for Sustainable Forest Management

Nasıl Atıf Yapılır

Rosset, C., Schütz, J.-P., Günter, M., & Gollut, C. (2014). WIS.2 – a sustainable forest management decision support system. Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 6(2), 89-100 (12). https://mcfns.com/index.php/Journal/article/view/6.10