论文部分内容阅读
辽宁西部大面积的油松(Pinus tabulaeformis)人工林长期受到油松毛虫(Dendrolimus tabulaeformis)的危害,通过遥感技术,可以及时、高效、精准地对此大面积灾害进行监测,并获知地形、气象因子对其的影响。本文利用遥感和地理信息系统(GIS)技术,使用TM、ETM+数据,通过近红外与红光波段反射率的比值RVI,对油松的受灾程度进行了有效监测。前人的研究发现:油松毛虫易在干燥、温暖的环境爆发,本文将监测分类结果与地形、气象数据叠加后,分析发现结果亦与油松毛虫的生物学特性相吻合,由此逆向证明了监测结果的可靠性。通过对影像灰度直方图的分析,发现近红外波段对轻度的虫害敏感;红光波段对重度的虫害敏感。对影响因子的分析发现:油松毛虫在阳坡,坡度缓的地区危害更剧烈;在日照时数长、降雨少、积温低的地区,油松的受灾程度更重。此结论为预测虫害爆发的概率提供了依据。本研究表明:在森林灾害的遥感工作中,利用监测对象的生物生态学特性,可以在实地调查数据不足,难以直接对监测结果进行评价的情况下,判断结果的可靠性。利用此方法,一定程度上可以减少调查的工作量,降低外业的难度。
Large-scale Pinus tabulaeformis plantations in western Liaoning Province have been endangered by Dendrolimus tabulaeformis for a long time. Through remote sensing technology, large-scale disasters can be monitored timely, efficiently and accurately, and terrain, meteorological factors Impact on it. In this paper, TM and ETM + data are used to effectively monitor the degree of disaster of Pinus tabulaeformis by using remote sensing and geographic information system (GIS) technology and RVI ratio of near-infrared and red-band reflectance. Previous studies have found that the oil pine caterpillars can easily break out in a dry and warm environment. After superposition of the monitoring classification results and the topography and meteorological data, the results of the analysis also found that the results are consistent with the biological characteristics of the oil pine caterpillar, The reliability of the monitoring results. By analyzing the gray histogram of images, it is found that the near-infrared band is sensitive to mild pests and the red band is sensitive to severe pests. The analysis of the influencing factors showed that the pine caterpillars harmed even more in the sunny slopes and gently sloping areas, and the ones affected by the long hours of sunshine, less rainfall and low accumulated temperature. This conclusion provides the basis for predicting the probability of pest outbreak. This study shows that in the remote sensing of forest disasters, the bioecological characteristics of the monitoring object can be used to judge the reliability of the results when there is not enough field survey data and it is difficult to directly evaluate the monitoring results. Using this method, to a certain extent, reduce the workload of the survey and reduce the difficulty of the field.