Next Article in Journal
Effects of Topographical and Edaphic Factors on Tree Community Structure and Diversity of Subtropical Mountain Forests in the Lower Lancang River Basin
Previous Article in Journal
Fire Regime in Marginal Jack Pine Populations at Their Southern Limit of Distribution, Riding Mountain National Park, Central Canada
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Forests 2016, 7(10), 220; doi:10.3390/f7100220

Using Spatial Optimization to Create Dynamic Harvest Blocks from LiDAR-Based Small Interpretation Units

1
School of Forest Sciences, University of Eastern Finland, P.O. Box 111, Joensuu 80101, Finland
2
Föra Forest Technologies, C/ Oreste Camarca, 4, Soria 42004, Spain
3
Department Producción Vegetaly Recursos Forestales, Universidad de Valladolid, Valladolid 34218, Spain
4
Department de Producció Vegetal i Ciència Forestal, Universitat de Lleida-Agrotecnio Center (UdL-Agrotecnio), Av. Rovira Roure, 191, Lleida 25198, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Peter N. Beets and Timothy A. Martin
Received: 12 August 2016 / Revised: 22 September 2016 / Accepted: 23 September 2016 / Published: 30 September 2016
View Full-Text   |   Download PDF [3411 KB, uploaded 30 September 2016]   |  

Abstract

Spatial and temporal differences in forest features occur on different scales as forest ecosystems evolve. Due to the increased capacity of remote sensing methods to detect these differences, forest planning may now consider forest compartments as transient units which may change in time and depend on the management objectives. This study presents a methodology for implementing these transient units, referred to as dynamic treatment units (DTU). LiDAR (Light Detecting and Ranging) data and field sample plots were used to estimate forest stand characteristics for 500-m2 pixels and compartments, and a set of models was developed to enable growth simulations. The DTUs were obtained by maximizing a utility function which aimed at maximizing the aggregation of harvest areas and the ending growing stock volume with even-flow cutting targets for three 10-year periods. Remote sensing techniques, modeling, simulation, and spatial optimization were combined with the aim of having an efficient methodology for assigning cutting treatments to forest stands and delineating compact harvest blocks. Pixel-based planning led to more accurate estimation of stand characteristics and more homogeneity inside the delineated harvest blocks while the compartment-based planning resulted in larger and higher area/perimeter ratio. View Full-Text
Keywords: forest planning; spatial optimization; precision forestry; remote sensing forest planning; spatial optimization; precision forestry; remote sensing
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Pascual, A.; Pukkala, T.; Rodríguez, F.; de-Miguel, S. Using Spatial Optimization to Create Dynamic Harvest Blocks from LiDAR-Based Small Interpretation Units. Forests 2016, 7, 220.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Forests EISSN 1999-4907 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top