Lu Hui, Han Jian-guo, Zhang Lu-da
College of Animal Science and Technology, China Agricultural University, Beijing 100094, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2008 Dec;28(12):2808-11.
Grasshopper monitoring is of great significance in protecting environment and reducing economic loss. However, how to predict grasshoppers accurately and effectively is a difficult problem for a long time. In the present paper, the importance of forecasting grasshoppers and its habitat is expounded, and the development in monitoring grasshopper populations and the common arithmetic of spectral analysis technique are illustrated. Meanwhile, the traditional methods are compared with the spectral technology. Remote sensing has been applied in monitoring the living, growing and breeding habitats of grasshopper population, and can be used to develop a forecast model combined with GIS. The NDVI values can be analyzed throughout the remote sensing data and be used in grasshopper forecasting. Hyper-spectra remote sensing technique which can be used to monitor grasshoppers more exactly has advantages in measuring the damage degree and classifying damage areas of grasshoppers, so it can be adopted to monitor the spatial distribution dynamic of rangeland grasshopper population. Differentialsmoothing can be used to reflect the relations between the characteristic parameters of hyper-spectra and leaf area index (LAI), and indicate the intensity of grasshopper damage. The technology of near infrared reflectance spectroscopy has been employed in judging grasshopper species, examining species occurrences and monitoring hatching places by measuring humidity and nutrient of soil, and can be used to investigate and observe grasshoppers in sample research. According to this paper, it is concluded that the spectral analysis technique could be used as a quick and exact tool in monitoring and forecasting the infestation of grasshoppers, and will become an important means in such kind of research for their advantages in determining spatial orientation, information extracting and processing. With the rapid development of spectral analysis methodology, the goal of sustainable monitoring grasshoppers can be developed in the future. First, it is needed to find the relationship between the grasshopper and its environment. Second, the new spectral technology including thermal infrared, microwave, UV detection, and laser technique will be widely practiced in grasshopper monitoring. Finally, it is obvious that the integration of all methods will drive the research into a bright direction of synthetically monitoring grasshoppers. Such approaches will greatly decrease the likelihood of grasshopper outbreaks.
蝗虫监测对于保护环境和减少经济损失具有重要意义。然而，如何准确有效地预测蝗虫一直是一个长期存在的难题。本文阐述了预测蝗虫及其栖息地的重要性，说明了蝗虫种群监测的发展情况以及光谱分析技术的常用算法。同时，将传统方法与光谱技术进行了比较。遥感技术已应用于监测蝗虫种群的生存、生长和繁殖栖息地，并可与地理信息系统（GIS）结合用于开发预测模型。通过对遥感数据进行分析可得到归一化植被指数（NDVI）值，并将其用于蝗虫预测。高光谱遥感技术在测量蝗虫危害程度和划分危害区域方面具有优势，能够更准确地监测蝗虫，因此可用于监测草原蝗虫种群的空间分布动态。微分平滑可用于反映高光谱特征参数与叶面积指数（LAI）之间的关系，并指示蝗虫危害的强度。近红外反射光谱技术已用于通过测量土壤湿度和养分来判断蝗虫种类、检查物种出现情况以及监测孵化地点，并可用于样本研究中的蝗虫调查和观察。根据本文得出的结论，光谱分析技术可作为一种快速、准确的工具用于监测和预测蝗虫的侵害情况，并且由于其在确定空间方位、信息提取和处理方面的优势，将成为此类研究的重要手段。随着光谱分析方法的快速发展，未来有望实现蝗虫可持续监测的目标。首先，需要找到蝗虫与其环境之间的关系。其次，包括热红外、微波、紫外线检测和激光技术在内的新光谱技术将在蝗虫监测中得到广泛应用。最后，显然所有方法的整合将推动研究朝着综合监测蝗虫的光明方向发展。这些方法将大大降低蝗虫爆发的可能性。
