Sample-Based Vegetation Distribution Information Synthesis
Chanchan Xu, Gang Yang, Meng Yang
TL;DR
This paper introduces a method to simulate realistic forest scenes by synthesizing plant distributions based on sample patterns.
Contribution
A novel sample-based vector pattern synthesis method is proposed for efficient and realistic vegetation distribution generation.
Findings
The proposed method preserves the distribution features of sample patterns in synthesized forest scenes.
Experiments confirm the effectiveness of the histogram-matching neighborhood comparison technique.
The method is efficient and suitable for constructing large-scale virtual forests.
Abstract
In constructing and visualizing a virtual three-dimensional forest scene, we must first obtain the vegetation distribution, namely, the location of each plant in the forest. Because the forest contains a large number of plants, the distribution of each plant is difficult to obtain from actual measurement methods. Random approaches are used as common solutions to simulate a forest distribution but fail to reflect the specific biological arrangements among types of plants. Observations show that plants in the forest tend to generate particular distribution patterns due to growth competition and specific habitats. This pattern, which represents a local feature in the distribution and occurs repeatedly in the forest, is in line with the “locality” and “static” characteristics in the “texture data”, making it possible to use a sample-based texture synthesis strategy to build the…
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Taxonomy
TopicsRemote Sensing and Land Use · Remote Sensing in Agriculture · Remote Sensing and LiDAR Applications