基于Sentinel-1多时相InSAR影像的云南松切梢小蠹危害程度监测

Using Sentinel-1 multi-temporal InSAR data to monitor the damage degree of shoot beetle in Yunnan pine forest

森林病虫害是森林健康生长的重要威胁之一,开展其危害程度监测对森林保护具有重要意义。基于多时相Sentinel-1C波段雷达数据、云南松物候和地面高度2 m处的相对湿度资料,对SAR相干系数和后向散射系数的时变特征及与相对湿度的相关性进行了分析,提出一种利用合成孔径雷达干涉(interferometric synthetic apertrue Radar,InSAR)影像进行森林病虫害危害程度监测的方法;并以云南省祥云县为研究区,进行了云南松健康林与不同程度受害林的分类研究。结果表明:(1)后向散射系数和相干系数的时序变化均与云南松物候期相关;(2)相干系数与相对湿度的相关性很小,后向散射系数与相对湿度有一定的相关性,其中轻度受害林的相关性达到0. 78;(3)通过实测数据验证,用多时相相干系数进行分类,精度高于后向散射系数分类,其中降轨数据的精度最高,可达到83. 15%,表明多时相C波段SAR相干数据可有效识别健康林与不同程度的受害林;(4)该方法对多云雨地区的森林病虫害监测与分类有一定的优势,可以进一步提升遥感监测病虫害的能力。

Forest pests constitute one of the important threats to the healthy growth of forests,and the monitoring of its damage is of great significance to forest protection.In this paper,a method of monitoring the degree of forest pests by using interferometric synthetic aperture Radar(InSAR)is proposed.Xiangyun County of Yunnan Province was selected as the study area and the multi-temporal C-band Sentinel-1images were applied.Based on the information of Radar backscattering intensity,interference phase and coherence coefficient,the time-varying characteristics of coherence coefficient and backscattering coefficient were analyzed by combining the phenological phase of Yunnan pine and relative humidity in the height of2meters.Fusion of multi-temporal data was applied to the classification of health forest and different degrees of damaged forest.Some conclusions have been reached:①The temporal variation of the backscattering coefficientand thecoherencecoefficientarerelated to the phenological phenology of Yunnanpine.②The correlationbetweenthe relative humidityandbackscattering coefficient is higher than coherencecoefficient,which reaches0.78inthe mildlydamaged forest.③Field data validation shows that classificationaccuracy of the multi-temporalcoherencecoefficientis higher than the backscattering coefficient,and the descending image has the highest precision which reaches83.15%.The result shows that the coherence coefficient of C-band SAR time series can effectively identify the problem as to whether the forest is healthy or suffers different degrees of damage.④The method has certain advantages in monitoring and classification of forest pests in cloudy areas as well as in further enhancing the capability of remote sensing on monitoring pests.