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首页> 外文学位 >An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary.
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An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary.

机译：一种用于在受管理的南卡罗来纳州河口监测和预测常见芦苇（芦苇）定居的综合建模方法。

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Recently, research efforts have focused on the development and testing of geographic information processing (GIP) techniques to more effectively identify and monitor invasive plant species in coastal ecosystems. While these efforts are progressing, particularly with refinements in hyperspectral image processing, there remains a lack of practical, science-based tools for decision-making with respect to the monitoring and mitigation of invasive plant species. Therefore, a geographic information systems (GIS) model is proposed to quantify the probability of a future exotic plant invasion in a user-defined area of interest. The primary objective of this investigation is to present conceptual and technical descriptions of a proposed modeling approach for prediction of common reed (Phragmites australis) colonization in a managed coastal wetland environment. Successful validation and adoption of the model will promote continued discourse regarding the impact of invasive species in coastal ecosystems, while providing the management community with a valuable decision support tool. Three main chapters comprise this manuscript; Chapter 1 focuses on the evaluation of remote sensing data and techniques for directly identifying Phragmites australis in a coastal ecosystem; Chapter 2 describes proposed, GIS-based models for predicting Phragmites colonization and future growth projections; and Chapter 3 discusses the results of the compiled relative suitability index (RSI) compilation and growth models, and considers the key management implications of the investigation. In the absence of a universal eradication solution for the invasive species Phragmites australis, an integrated management approach that utilizes a suite of dynamic, geo-spatial techniques in concert with more traditional practices is ultimately recommended.; Keywords. Invasive species, estuary, NERRS, Phragmites, GIS-based models, remote sensing, coastal resource management, geographic information processing.
机译：最近，研究工作集中在地理信息处理（GIP）技术的开发和测试上，以更有效地识别和监视沿海生态系统中的入侵植物。尽管这些努力正在取得进展，特别是在高光谱图像处理方面的改进，但在监视和缓解入侵植物物种方面仍然缺乏实用，基于科学的决策工具。因此，提出了一种地理信息系统（GIS）模型来量化用户定义的关注区域中未来外来植物入侵的可能性。这项研究的主要目的是介绍在管理的沿海湿地环境中用于预测普通芦苇（芦苇）定殖的拟议建模方法的概念和技术描述。该模型的成功验证和采用将促进关于入侵物种对沿海生态系统影响的持续讨论，同时为管理界提供有价值的决策支持工具。该手稿包括三个主要章节；第1章着重评估遥感数据和直接识别沿海生态系统中的芦苇的技术；第2章介绍了建议的基于GIS的模型，用于预测芦苇的定居和未来的增长预测。第3章讨论了已编译的相对适合性指数（RSI）编译和增长模型的结果，并考虑了调查的关键管理意义。在缺乏针对入侵物种芦苇的通用根除解决方案的情况下，最终建议采用一种综合管理方法，该方法利用一套动态地理空间技术与更传统的做法相结合。关键字。外来入侵物种，河口，NERRS，芦苇，基于GIS的模型，遥感，沿海资源管理，地理信息处理。

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