Spatial ecological complexity measures in GRASS GIS


Good estimates of ecosystem complexity are essential for a number of ecological tasks: from biodiversity estimation, to forest structure variable retrieval, to feature extraction by edge detection and generation of multifractal surface as neutral models for e.g. feature change assessment. Hence, measuring ecological complexity over space becomes crucial in macroecology and geography. Many geospatial tools have been advocated in spatial ecology to estimate ecosystem complexity and its changes over space and time. Among these tools, free and open source options especially offer opportunities to guarantee the robustness of algorithms and reproducibility. In this paper we will summarize the most straightforward measures of spatial complexity available in the Free and Open Source Software GRASS GIS, relating them to key ecological patterns and processes.

Publication DOI:
Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences > Sustainable environment research group
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Supplementary data availalbe on the journal website.
Uncontrolled Keywords: free and open source software,remote sensing,spatial complexity,spatial ecology,Information Systems,Computers in Earth Sciences
Publication ISSN: 1873-7803
Last Modified: 15 May 2024 07:11
Date Deposited: 25 May 2016 10:28
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2017-07
Published Online Date: 2016-05-18
Accepted Date: 2016-05-13
Submitted Date: 2015-11-12
Authors: Rocchini, Duccio
Petras, Vaclav
Petrasova, Anna
Chemin, Yann
Ricotta, Carlo
Frigeri, Alessandro
Landa, Martin
Marcantonio, Matteo
Bastin, Lucy (ORCID Profile 0000-0003-1321-0800)
Metz, Markus
Delucchi, Luca
Neteler, Markus

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