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Comparing Pixel and Object-Based Approaches to Map an Understorey Invasive Shrub in Tropical Mixed Forests

机译：比较基于像素和对象的方法来绘制热带混交林下层入侵灌木

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The establishment of invasive alien species in varied habitats across the world is now recognized as a genuine threat to the preservation of biodiversity. Specifically, plant invasions in understory tropical forests are detrimental to the persistence of healthy ecosystems. Monitoring such invasions using Very High Resolution (VHR) satellite remote sensing has been shown to be valuable in designing management interventions for conservation of native habitats. Object-based classification methods are very helpful in identifying invasive plants in various habitats, by their inherent nature of imitating the ability of the human brain in pattern recognition. However, these methods have not been tested adequately in dense tropical mixed forests where invasion occurs in the understorey. This study compares a pixel-based and object-based classification method for mapping the understorey invasive shrub Lantana camara (Lantana) in a tropical mixed forest habitat in the Western Ghats biodiversity hotspot in India. Overall, a hierarchical approach of mapping top canopy at first, and then further processing for the understorey shrub, using measures such as texture and vegetation indices proved effective in separating out Lantana from other cover types. In the first method, we implement a simple parametric supervised classification for mapping cover types, and then process within these types for Lantana delineation. In the second method, we use an object-based segmentation algorithm to map cover types, and then perform further processing for separating Lantana. The improved ability of the object-based approach to delineate structurally distinct objects with characteristic spectral and spatial characteristics of their own, as well as with reference to their surroundings, allows for much flexibility in identifying invasive understorey shrubs among the complex vegetation of the tropical forest than that provided by the parametric classifier. Conservation practices in tropical mixed forests can benefit greatly by adopting methods which use high resolution remotely sensed data and advanced techniques to monitor the patterns and effective functioning of native ecosystems by periodically mapping disturbances such as invasion.
机译：现在，人们公认在世界各地不同的生境中建立外来入侵物种是对保护生物多样性的真正威胁。具体而言，林下热带森林中的植物入侵对健康生态系统的持久性有害。使用超高分辨率（VHR）卫星遥感监测此类入侵在设计保护自然栖息地的管理干预措施方面非常有价值。基于对象的分类方法具有模仿人脑在模式识别中的能力的内在本质，因此在识别各种生境中的入侵植物方面非常有帮助。但是，这些方法尚未在茂密的热带混交林中进行适当的测试，在这些混交林中，发生在下层。这项研究比较了基于像素和基于对象的分类方法，用于在印度西高止山脉生物多样性热点的热带混交林生境中绘制地下入侵灌木马樱丹（Lantana camara）（马樱丹）。总体而言，事实证明，采用分层方法首先绘制顶盖，然后使用质地和植被指数等措施对下层灌木进行进一步处理，可以有效地将马tana丹与其他覆盖类型区分开。在第一种方法中，我们实现了用于映射封面类型的简单参数监督分类，然后在这些类型中进行马Lan丹的描绘。在第二种方法中，我们使用基于对象的分割算法来映射封面类型，然后执行进一步的处理以分离马Lan丹。基于对象的方法具有更好的能力来描绘具有自身光谱特征和空间特征以及与周围环境相关的结构上不同的对象，从而在识别热带森林复杂植被中的侵入性灌木丛方面具有很大的灵活性。而不是参数分类器提供的参数。通过采用高分辨率遥感数据和先进技术，通过定期绘制干扰（例如入侵）图来监测本地生态系统的模式和有效功能，可以使热带混交林的保护实践受益匪浅。

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