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ISPRS Int. J. Geo-Inf. 2018, 7(3), 127; https://doi.org/10.3390/ijgi7030127

Procedural Generation of Large-Scale Forests Using a Graph-Based Neutral Landscape Model

Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
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Received: 7 February 2018 / Revised: 15 March 2018 / Accepted: 17 March 2018 / Published: 20 March 2018
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Abstract

Specifying the positions and attributes of plants (e.g., species, size, and height) during the procedural generation of large-scale forests in virtual geographic environments is challenging, especially when reflecting the characteristics of vegetation distributions. To address this issue, a novel graph-based neutral landscape model (NLM) is proposed to generate forest landscapes with varying compositions and configurations. Our model integrates a set of class-level landscape metrics and generates more realistic and variable landscapes compared with existing NLMs controlled by limited global-level landscape metrics. To produce patches with particular sizes and shapes, a region adjacency graph is transformed from a cluster map that is generated based upon percolation theory; subsequently, optimal neighboring nodes in the graph are merged under restricted growth conditions from a source node. The locations of seeds are randomly placed and their species are classified according to the generated forest landscapes to obtain the final tree distributions. The results demonstrate that our method can generate realistic vegetation distributions representing different spatial patterns of species with a time efficiency that satisfies the requirements for constructing large-scale virtual forests. View Full-Text
Keywords: neutral landscape model; vegetation distribution; region adjacency graph; shape index neutral landscape model; vegetation distribution; region adjacency graph; shape index
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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).
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Li, J.; Gu, X.; Li, X.; Tan, J.; She, J. Procedural Generation of Large-Scale Forests Using a Graph-Based Neutral Landscape Model. ISPRS Int. J. Geo-Inf. 2018, 7, 127.

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