Trend analyses and projections using national forest inventory data

Auteurs-es

  • Greg C Liknes USDA Forest Service
  • Randall S Morin USDA Forest Service
  • Charles D Canham Cary Institute of Ecosystem Studies image/svg+xml

Mots-clés :

forest inventory, forest monitoring, trends, projections, time series, FIA

Résumé

We present a collection of papers derived from the 2012 Forest Inventory and Analysis (FIA) Symposium held on December 4-6, 2012 in Baltimore, MD, USA. The symposium featured 128 oral presentations with nearly 200 attendees from the United States and other countries. A proceedings from the symposium included 75 papers as well as abstracts for all presentations and posters. The symposium theme, \textit{Moving from Status to Trends}, focused on the ability to perform trend or time series analysis using national forest inventory data. A wide range of topics were covered including forest products, social dimensions of forestry, landscape change, analytical tools, Landsat time series, forest carbon, and many others. Based on these presentations, we have assembled a selection of several papers that presented examples of trend analyses and projections using forest inventory data. This Special Issue contains four of these papers that passed the MCFNS double-blind peer-review by a minimum of three peers.

Biographies de l'auteur-e

  • Greg C Liknes, USDA Forest Service
    Research Physical Scientist, Forest Inentory and Analysis, Northern Research Station
  • Randall S Morin, USDA Forest Service
    Research Forester, Forest Inentory and Analysis, Northern Research Station
  • Charles D Canham, Cary Institute of Ecosystem Studies
    Forest Ecologist, Cary Institute of Ecosystem Studies

Publié

2013-09-30

Numéro

Rubrique

Sampling and Natural Resource Inventories

Comment citer

Trend analyses and projections using national forest inventory data. (2013). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 5(2), 112-114(3). https://mcfns.com/index.php/Journal/article/view/5.7

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