无人机航高对落叶松毛虫虫害遥感监测精度的影响

杨乐; 黄晓君; 包玉海; 包刚; 佟斯琴; 苏都毕力格

doi:10.12302/j.issn.1000-2006.202204047

杨乐, 黄晓君, 包玉海, 包刚, 佟斯琴, 苏都毕力格

南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (4) : 13-22.

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南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (4) : 13-22. DOI: 10.12302/j.issn.1000-2006.202204047

专题报道：第三届中国林草计算机应用大会论文精选（Ⅱ）（执行主编李凤日）

无人机航高对落叶松毛虫虫害遥感监测精度的影响

杨乐 ¹ ,
黄晓君 ¹^,^* ,
包玉海 ¹ ,
包刚 ¹ ,
佟斯琴 ¹ ,
苏都毕力格 ²

作者信息 +

Effects of UAV flight altitude on the accuracy of monitoring Dendrolimus superans pests by remote sensing

YANG Le ¹ ,
HUANG Xiaojun ¹^,^* ,
BAO Yuhai ¹ ,
BAO Gang ¹ ,
TONG Siqin ¹ ,
Sudubilig ²

Author information +

文章历史 +

摘要

【目的】探究无人机航高对落叶松毛虫(Dendrolimus superans)虫害监测精度的影响机制,以期构建先进的森林虫害监测技术框架,为无人机近地面森林虫害遥感监测提供重要参考。【方法】以大兴安岭落叶松毛虫虫害频发区为试验区,以无人机不同航高下采集的多光谱遥感影像为基础数据,获得健康、轻度和重度虫害的386株落叶松树冠层光谱指数和纹理特征,通过方差分析法(ANOVA)及连续投影算法(SPA)提取对虫害严重程度敏感的光谱特征,结合随机森林(RF)和支持向量机(SVM)算法构建虫害严重程度监测模型,揭示航高对监测精度的影响。【结果】①光谱指数和纹理特征的总体(轻度+重度)监测精度均随航高上升呈下降趋势,而轻度和重度虫害的监测精度却有不同变化态势。②光谱指数(修正型三角植被指数2、绿光归一化差值植被指数2、绿光归一化差值植被指数、差值植被指数、简单比值指数1)+纹理特征(MEA 3)组合的虫害监测精度达到最优(总体精度和Kappa值分别为92.3%和0.891),但其总体和轻度的监测精度随航高上升呈下降趋势(下降速率分别为0.04%/m和0.03%/m),重度的监测精度有上升趋势(上升速率为0.03%/m)。【结论】航高对无人机近地虫害监测精度具有明显影响,并且轻度和重度监测精度随航高的变化速率和趋势有差异。与重度虫害相比,轻度的监测精度随航高的变化速率较快。无人机对虫害早期高精度遥感识别宜选择低航高,而适当提升航高亦能获得对虫害严重度评估监测的预期效果。

Abstract

【Objective】This study aims to explore the influence of unmanned aerial vehicles(UAV) flight altitude mechanism on the accuracy of monitoring larch caterpillar (Dendrolimus superans) insect pests, and provide an important reference for ground UAV remote sensing monitoring of forest pests.【Method】 The areas known for frequent occurrences of D. superans in Da Hinggan Mountains were selected and multispectral remote sensing images collected by UAV at different flight altitudes were used as the basic data. This study obtained the canopy spectral indexes and texture features of 386 healthy, mild, and severely damaged trees by D. superans. Analysis of variances and continuous projection algorithms were used to extract the spectral features sensitive to pest severity. The pest severity monitoring model was constructed using random forest and support vector machine algorithms, and expounded the influence of flight altitude on monitoring accuracy.【Result】(1) The accuracy of overall (mild + severe) monitoring of the spectral indexes and texture features decreased with an increase in flight altitudes. However, the accuracy of mild and severe monitoring of trees damaged by D. superans exhibited different trends. (2) The pest monitoring accuracy of the combination of spectral indices (MTVI 2, GNDVI 2, DVI, GMI 1 and GNDVI) + texture feature (MEA 3) was the best, and the overall accuracy and Kappa coefficient were 92.3% and 0.891, respectively. However, the overall and accuracy of mild monitoring decreased with an increase in flight altitudes, where the decline rate was 0.04%/m and 0.03%/m, respectively, and the accuracy of severe monitoring increased (the rise rate was 0.03%/m). 【Conclusion】 The flight altitudes significantly impacted the accuracy of UAV ground pest monitoring. There was a difference in the rate and trend between the accuracies of mild and severe monitoring. The rate of change in the accuracy of mild monitoring with flight altitude was faster than that of the accuracy of the severe monitoring. Thus, an early identification of pests using a high-precision UAV remote sensing, adaptable to various flight altitudes, is needed to monitor pest severity and improve the expected effects.

导出引用

杨乐, 黄晓君, 包玉海, 等. 无人机航高对落叶松毛虫虫害遥感监测精度的影响[J]. 南京林业大学学报（自然科学版）. 2023, 47(4): 13-22 https://doi.org/10.12302/j.issn.1000-2006.202204047

YANG Le, HUANG Xiaojun, BAO Yuhai, et al. Effects of UAV flight altitude on the accuracy of monitoring Dendrolimus superans pests by remote sensing[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2023, 47(4): 13-22 https://doi.org/10.12302/j.issn.1000-2006.202204047

中图分类号： S763.305

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