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Special Issue "Geographic Information Systems and Their Applications in Forests"

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Quantitative Methods and Remote Sensing".

Deadline for manuscript submissions: 15 October 2019

Special Issue Editor

Guest Editor
Dr. Francois Girard

Department of Geography, Université de Montréal, Montréal, QC, Canada.
Website | E-Mail
Interests: forest; tree regeneration; air photos; remote sensing; ecophysiology; photosynthesis; tree reproduction

Special Issue Information

Dear Colleagues,

Geographic Information Systems (or GIS) are now implemented in most research labs around the world. They allow to create, manage, analyze or map spatial data such as points, lines, polygons, air photos, satellite images or else. From the simple map in a journal article to very complex spatial analysis, researchers are now using and see GIS every day. Applications in forest research are extensive and varied. Historically, computer power had limited GIS analysis over large areas. Nowadays, machine learning can achieve a lot of processes simultaneously to provide researchers exceptional computer power for GIS analysis. Global understanding of forest dynamics, processes and, fluxes at the landscape level is now trending. Forest managers are quite interested in the big picture when planning sylviculture. Forest GIS datasets such as national inventories are based on field observations that can be interpolated in non-sampled areas. Thus, GIS analysis is non-expensive tool that forest managers use on a daily basis.

This Special Issue of Forests is focused on “Geographic Information Systems (GIS) and Their Applications in Forests”, and how the different GIS techniques can improve the global understanding of forest dynamics. Research articles may focus on any aspect GIS sciences, such as mapping, modelling, remote sensing or spatial statistics.

Dr. François Girard
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Geographic Information Systems
  • remote sensing
  • machine learning
  • forest management
  • landscape ecology

Published Papers (2 papers)

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Research

Open AccessArticle Global Assessment of Climate-Driven Susceptibility to South American Leaf Blight of Rubber Using Emerging Hot Spot Analysis and Gridded Historical Daily Data
Forests 2019, 10(3), 203; https://doi.org/10.3390/f10030203
Received: 24 January 2019 / Revised: 19 February 2019 / Accepted: 22 February 2019 / Published: 26 February 2019
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Abstract
South American leaf blight (SALB) of Para rubber trees (Hevea brasiliensis Muell. Arg.) is a serious fungal disease that hinders rubber production in the Americas and raises concerns over the future of rubber cultivation in Asia and Africa. The existing evidence of [...] Read more.
South American leaf blight (SALB) of Para rubber trees (Hevea brasiliensis Muell. Arg.) is a serious fungal disease that hinders rubber production in the Americas and raises concerns over the future of rubber cultivation in Asia and Africa. The existing evidence of the influence of weather conditions on SALB outbreaks in Brazil has motivated a number of assessment studies seeking to produce risk maps that illustrate this relationship. Subjects with dynamic and cyclical spatiotemporal features need to embody sufficiently fine spatial resolution and temporal granulation for both input data and outputs in order to be able to reveal the desired patterns. Here, we apply emerging hot spot analysis to three decades of gridded daily precipitation and surface relative humidity data to depict their temporal and geographical patterns in relation to the occurrence of weather conditions that may lead to the emergence of SALB. Inferential improvements through improved handling of the uncertainties and fine-scaled temporal breakdown of the analysis have been achieved in this study. We have overlaid maps of the potential distribution of rubber plantations with the resulting dynamic and static maps of the SALB hot spot analysis to highlight regions of distinctly high and low climatic susceptibility for the emergence of SALB. Our findings highlight the extent of low-risk areas that exist within the rubber growing areas outside of the 10° equatorial belt. Full article
(This article belongs to the Special Issue Geographic Information Systems and Their Applications in Forests)
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Open AccessArticle Predicting the Potential Distribution of Paeonia veitchii (Paeoniaceae) in China by Incorporating Climate Change into a Maxent Model
Forests 2019, 10(2), 190; https://doi.org/10.3390/f10020190
Received: 14 January 2019 / Revised: 14 February 2019 / Accepted: 19 February 2019 / Published: 20 February 2019
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Abstract
A detailed understanding of species distribution is usually a prerequisite for the rehabilitation and utilization of species in an ecosystem. Paeonia veitchii (Paeoniaceae), which is an endemic species of China, is an ornamental and medicinal plant that features high economic and ecological values. [...] Read more.
A detailed understanding of species distribution is usually a prerequisite for the rehabilitation and utilization of species in an ecosystem. Paeonia veitchii (Paeoniaceae), which is an endemic species of China, is an ornamental and medicinal plant that features high economic and ecological values. With the decrease of its population in recent decades, it has become a locally endangered species. In present study, we modeled the potential distribution of P. veitchii under current and future conditions, and evaluated the importance of the factors that shape its distribution. The results revealed a highly and moderately suitable habitat for P. veitchii that encompassed ca. 605,114 km2. The central area lies in northwest Sichuan Province. Elevation, temperature seasonality, annual mean precipitation, and precipitation seasonality were identified as the most important factors shaping the distribution of P. veitchii. Under the scenario with a low concentration of greenhouse gas emissions (RCP 2.6), we predicted an overall expansion of the potential distribution by 2050, followed by a slight contraction in 2070. However, with the scenario featuring intense greenhouse gas emissions (RCP 8.5), the range of suitable habitat should increase with the increasing intensity of global warming. The information that was obtained in the present study can provide background information related to the long-term conservation of this species. Full article
(This article belongs to the Special Issue Geographic Information Systems and Their Applications in Forests)
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