Brian A. Tangen, Rebecca L. Esser, Benjamin A. Walker
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We also sought to compare the high-resolution imagery to widely available imagery (e.g., National Agriculture Imagery Program) to determine the efficacy of each for assessing vegetation communities and land-cover features in support of management activities. To accomplish these objectives, we obtained high-resolution imagery and visually scanned and assessed the imagery using standard geographic information system software. We were able to differentiate patches of crownvetch Securigera varia (L.) Lassen and wild parsnip Pastinaca sativa L., but not spotted knapweed Centaurea stoebe L. or leafy spurge Euphorbia esula L. The relative success in identifying these species was related to plant characteristics (e.g., flower color and morphology, height), time of year (phenology), patch size and density, and potentially site characteristics such density of the underlying vegetation (e.g., grasses), substrate color characteristics (i.e., color contrast with flowers), and physical disturbance. 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引用次数: 0
摘要
生物学家和其他保护人员利用来自各种收集平台(如卫星、有人驾驶和无人驾驶飞机)的遥感图像来支持从监测入侵物种到评估土地覆盖和植被特征等各种管理活动。虽然基于遥感的植被指数和模型已被开发并用于某些管理应用,但由现场人员对图像进行直接的目视判读可能是获取时间敏感性和空间相关信息以支持和指导当地管理活动的一种实用方法。我们的主要目标是定性评估我们根据对高分辨率航空图像的简单目视判读识别目标入侵植物物种斑块的能力。我们还试图将高分辨率图像与广泛使用的图像(如国家农业图像计划)进行比较,以确定每种图像在评估植被群落和土地覆盖物特征以支持管理活动方面的功效。为了实现这些目标,我们获得了高分辨率图像,并使用标准地理信息系统软件对图像进行了目视扫描和评估。我们能够分辨出皇冠草 Securigera varia (L.) Lassen 和野生欧洲防风草 Pastinaca sativa L.,但不能分辨出斑节草 Centaurea stoebe L. 或叶刺芹 Euphorbia esula L.、花的颜色和形态、高度)、一年中的时间(物候学)、斑块大小和密度,以及潜在的地点特征,如底层植被(如草)的密度、基质颜色特征(即与花的颜色对比)和物理干扰。我们直截了当的定性评估表明,对高分辨率图像(而非某些低分辨率图像)的视觉解读可能是支持当地入侵物种管理的高效工具,可用于监测已知斑块、识别未发现的侵扰、评估管理行动、指导实地工作或确定实地监测活动的优先次序等活动。
Visual interpretation of high-resolution aerial imagery: A tool for land managers
Remotely sensed imagery from various collection platforms (e.g., satellites, crewed and uncrewed aircraft) are used by biologists and other conservation personnel to support management activities ranging from monitoring invasive species to assessing land cover and vegetation characteristics. While remote sensing-based vegetation indices and models have been developed and used for some management applications, straightforward visual interpretation of imagery by on-the-ground personnel may be a pragmatic approach for obtaining time-sensitive and spatially relevant information to support and guide local management activities. Our primary objective was to qualitatively assess our ability to identify patches of target invasive plant species based on simple visual interpretation of high-resolution aerial imagery. We also sought to compare the high-resolution imagery to widely available imagery (e.g., National Agriculture Imagery Program) to determine the efficacy of each for assessing vegetation communities and land-cover features in support of management activities. To accomplish these objectives, we obtained high-resolution imagery and visually scanned and assessed the imagery using standard geographic information system software. We were able to differentiate patches of crownvetch Securigera varia (L.) Lassen and wild parsnip Pastinaca sativa L., but not spotted knapweed Centaurea stoebe L. or leafy spurge Euphorbia esula L. The relative success in identifying these species was related to plant characteristics (e.g., flower color and morphology, height), time of year (phenology), patch size and density, and potentially site characteristics such density of the underlying vegetation (e.g., grasses), substrate color characteristics (i.e., color contrast with flowers), and physical disturbance. Our straightforward, qualitative assessment suggests that visual interpretation of high-resolution imagery, but not some lower-resolution imagery, may be an efficient and effective tool for supporting local invasive species management through activities such as monitoring known patches, identifying undetected infestations, assessing management actions, guiding field work, or prioritizing on-the-ground monitoring activities.