Publications

Aim of the study: To introduce and describe ApkFor©, an Android Open-Source Project to generate basic mobile applications to transfer forest growth and yield models for even-aged stands. Material and methods: ApkFor© was developed in Android Studio using Java and XML languages integrating transition functions for dominant height and basal area, equations of tree and stand volume and structural models. The project was applied and validated for Pinus pinaster Ait. stands in Northeastern Portugal. Main results: ApkFor© is Open-Source and freely project available from the Source Force repository: https://sourceforge.net/projects/apkfor/, licensed under the GNU General Public License version 3.0 (GPLv3). Research highlights: This project has been designed and created to provide the code and promote its re-use and modification to develop simple growth and yield mobile applications in Android, and with it to transfer research results of forest modelling to forest managers. Moreover, an example of application of the compiled code is provided using the models of Pinus pinaster Ait. previously validated for the Northeastern Region of Portugal.

Costs and environmental impacts are key elements in forest logistics and they must part of decision-making. The evaluation of transportation fuel costs and carbon emissions depend on spatial and non-spatial data but in many cases the first type of data are difficult to obtain. On the other hand, the availability of software tools to evaluate with rigor transportation fuel quantities and costs and emissions of carbon dioxide is limited. We present a software tool that combines two empirical validated models of truck transportation using DEM and an open spatial data tool, specifically OpenStreetMap©. The tool provides outputs such as maps with distribution of transport performance (relation between beeline and real road distances), cost and CO2 emissions for four types of truck. These outputs can be successfully included in forest decision-making support systems. Finally, in this work we applied the tool in a particular case of forest logistics in northeaster Portugal.

Aim of study: To present the software utilities and explain how to use EucaTool®, a free cloud computing application developed to estimate the growth and production of seedling and clonal blue gum (Eucalyptus globulus Labill.) plantations in Galicia (NW Spain).

Area of study: Galicia (NW Spain).

Material and methods: EucaTool® implements a dynamic growth and production model that is valid for clonal and non-clonal blue gum plantations in the region. The model integrates transition functions for dominant height (site index curves), number of stems per hectare (mortality function) and basal area, as well as output functions for tree and stand volume, biomass and carbon content.

Main results: EucaTool® can be freely accessed from any device with an Internet connection, from http://app.eucatool.com. In addition, useful information about the application is published on a related website: http://www.eucatool.com.

Research highlights: The application has been designed to enable forest stakeholders to estimate volume, biomass and carbon content of forest plantations from individual trees, diameter classes or stand data, as well as to estimate growth and future production (indicating the optimal rotation age for maximum income) by measurement of only four stand variables: age, number of trees per hectare, dominant height and basal area.

We present an example of the application of the AHP decision-making approach to forest management, by use of MPC© 2.0 software. The example considered is that of a forest services company interested in buying a timber harvester. The company had preselected four different machines as possible alternatives, and established 11 different criteria involved in the decision, grouped into four categories (economic, environmental, social and technical). The decision-making process was undertaken using MPC© 2.0 software tools, which enable establishment of criteria on two levels, independent pairwise comparison of criteria (first phase) and of alternatives under each criterion (second phase), repetition of the decision-making process by the same or different users, graphical display of the results on the computer screen, and sensitivity analysis.