Application of Remote Sensing Technologies for Assessing Planted Forests Damaged by Insect Pests and Fungal Pathogens: a Review
Application of Remote Sensing Technologies for Assessing Planted Forests Damaged by Insect Pests and Fungal Pathogens: a Review
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DOI：
10.1007/s40725-017-0056-1
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发表时间：
2017-03
影响因子：
9.5
通讯作者：
C. Stone;C. Mohammed
中科院分区：
文献类型：
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作者：
C. Stone;C. Mohammed
审查目的在本次审查中，我们重点介绍了遥感技术的最新发展和应用，这些发展和应用可以提高木材和纸浆生产管理种植园健康评估的准确性和及时性。检测和绘制由害虫和真菌病原体造成的损害范围和严重程度是管理种植园的林务人员的常见要求。这些调查的目标可以是早期发现有针对性的干预，也可以是预测林分敏感性或评估管理策略绩效的更具战略性的目标。最新发现遥感技术和大数据建模技术的最新发展现在可以为这些管理目标提供空间明确的定量解决方案，这些解决方案比手动现场评估树木损坏或机载视觉测绘更准确。过去的研究已经确定了大量的光谱、纹理和结构指标，这些指标已用于模型中对特定树冠损伤症状进行分类。这个过程需要详细了解特定破坏剂的牙冠症状的时间顺序以及对这些症状的光谱反应。遥感器空间和光谱分辨率的不断提高使得树冠级损伤分类成为可能。摘要将光谱信息与从单个或不同远程平台同时获取的三维（3D）数据融合的数据处理工作流程的发展促进了导出与树冠损伤相关的结构和生理树冠级属性的机会。同时采集光谱和 3D 点数据将使人工林林务人员能够获得多种空间产品，包括以经济高效的方式评估树木健康状况。
Purpose of ReviewIn this review, we highlight recent developments and applications in remote sensing that can improve the accuracy and timeliness of health assessments in plantations managed for timber and pulp production. The detection and mapping of damage extent and severity caused by insect pests and fungal pathogens is a common requirement of foresters managing plantations. The objectives of these surveys can range from early detection for targeted intervention to more strategic aims of predicting stand susceptibility or evaluating the performance of management strategies.Recent FindingsRecent developments in remote sensing technologies and big data modelling techniques can now provide spatially explicit, quantitative solutions for these management objectives that are more accurate than manual field-based assessments of tree damage or airborne visual mapping. Past studies have identified a large number of spectral, textural and structural metrics that have been used in models to classify specific tree crown damage symptoms. This process requires a detailed understanding of the chronology of crown symptoms for specific damaging agents and the spectral responses to these symptoms. Continuing increases in the spatial and spectral resolution of remote sensors enables crown-level damage classification.SummaryThe development of data processing workflows that fuse spectral information with three-dimensional (3D) data acquired simultaneously from single or different remote platforms promote the opportunities to derive both structural and physiological crown-level attributes that relate to crown damage. The simultaneous acquisition of spectral and 3D point data will enable plantation foresters to derive several spatial products, including the assessment of tree health in a cost-effective manner.