Please wait a minute...
 
国土资源遥感  2016, Vol. 28 Issue (2): 41-47    DOI: 10.6046/gtzyyg.2016.02.07
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
松毛虫危害下的马尾松林冠层光谱特征可辨性分析
许章华1, 刘健2,3,4, 陈崇成5, 余坤勇2,3, 黄旭影1, 王美雅1
1. 福州大学环境与资源学院, 福州 350116;
2. 福建农林大学3S技术应用研究所, 福州 350002;
3. 福建农林大学林学院, 福州 350002;
4. 三明学院, 三明 365000;
5. 福州大学地理空间 信息技术国家地方联合工程研究中心, 福州 350002
Canopy spectral characteristics distinguishability analysis of Pinus massoniana forests with Dendrolimus punctatus Walker damage
XU Zhanghua1, LIU Jian2,3,4, CHEN Chongcheng5, YU Kunyong2,3, HUANG Xuying1, WANG Meiya1
1. College of Environment and Resources, Fuzhou University, Fuzhou 350116, China;
2. Institute of Geomatics Application, Fujian Agriculture and Forestry University, Fuzhou 350002, China;
3. College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China;
4. Sanming University, Sanming 365000, China;
5. National Engineering Research Centre of Geospatial Information Technology, Fuzhou University, Fuzhou 350002, China
全文: PDF(1926 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 

深入挖掘寄主光谱响应机制是推进马尾松毛虫害遥感快速监测与预警的必要基础。将采集于福建省长汀县、南平市建阳区的46条马尾松林冠层光谱曲线数据设为规则组,利用单因素方差分析法实现不同危害等级可辨性波长的选择。研究表明,不同危害等级下的马尾松林冠层光谱数据呈现极显著差异(P<0.01),其中,中度—重度危害的马尾松林冠层光谱可辨性在516.51~598.99 nm和700.68~706.18 nm位置上有显著差异(P<0.05),在708.92~810.62 nm位置上有极显著差异(P<0.01)。为此,以519.20 nm,540.72 nm,758.40 nm和785.88 nm波段处光谱反射率为组合,以健康状态下的马尾松林冠层光谱数据为标准样本,基于空间距离法、相关系数法及光谱角制图法分别建立松毛虫危害等级的定量化判定规则,并利用将乐县、南平市延平区、华安县的34条验证组光谱曲线数据对此规则进行验证。结果显示,空间距离法的判定效果远优于相关系数法与光谱角制图法; 无松毛虫危害、轻度危害、中度危害以及重度危害的空间距离判定规则依次为: <0.355 3,[0.355 3,0.742 5),[0.742 5,0.963 1)及≥0.963 1,判定精度为88.24%,准确率达97.06%。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
李万伦
甘甫平
关键词 矿山环境高光谱遥感监测进展    
Abstract

The deep mining of host spectral response mechanism is the necessary foundation for Dendrolimus punctatus Walker damage remote sensing fast monitoring and early warning. 46 canopy spectral curve data of Pinus massoniana forests collected in Changting County of Jianyang District were set as the rule group, and the one-way ANOVA was used to realize the distinguished wavelengths selection with different pest levels, and the results showed that there were highly significant differences of pine forests canopy spectral data with different pest levels (P<0.01), in which there were significant differences at 516.51~598.99 nm and 700.68~706.18 nm of spectral distinguishability between moderate damage and severe damage (P<0.05), and highly significant differences at 708.92~810.62 nm (P<0.01). Thus, based on the combination of spectral reflectance of 519.2 nm, 540.72 nm, 758.4 nm, 785.88 nm and taking the healthy pine forests canopy spectral data as the standard sample, the authors constructed the quantitative determination rules of pest levels of Dendrolimus punctatus Walker, relying on the methods of spatial distance, correlation coefficient and spectral angle mapping respectively. The rules were verified with the test group of 34 spectral curve data collected in Jiangle County, Yanping District of Nanping City, and Huaan County, and the results showed that the determination effect of spatial distance method was by far better than that of the correlation coefficient method and spectral angle mapping method. The spatial distance determination rules of non-damage, mild damage, moderate damage and severe Dendrolimus punctatus Walker damages were as follows: <0.355 3, [0.355 3, 0.742 5), [0.742 5, 0.963 1) and ≥0.9631, with the determination accuracy being 88.24% and the accurate rate being 97.06%.

Key wordsmine environment    hyperspectral    monitoring through remote sensing    research progress
收稿日期: 2014-12-31      出版日期: 2016-04-14
:  TP79  
  P237  
基金资助:

国家自然科学基金青年科学基金项目(编号: 41501361)、福建省资源环境监测与可持续经营利用重点实验室开放基金项目(编号: ZD1403)和福州大学人才基金项目(编号: XRC-1345)共同资助。

通讯作者: 刘健(1963-),男,博士,教授,博士生导师,研究方向为森林经营管理与3S技术应用。Email: fjliujian@126.com。
作者简介: 许章华(1985-),男,博士,讲师,研究方向为资源环境遥感、城乡规划与GIS应用。Email: fafuxzh@163.com。
引用本文:   
许章华, 刘健, 陈崇成, 余坤勇, 黄旭影, 王美雅. 松毛虫危害下的马尾松林冠层光谱特征可辨性分析[J]. 国土资源遥感, 2016, 28(2): 41-47.
XU Zhanghua, LIU Jian, CHEN Chongcheng, YU Kunyong, HUANG Xuying, WANG Meiya. Canopy spectral characteristics distinguishability analysis of Pinus massoniana forests with Dendrolimus punctatus Walker damage. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 41-47.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2016.02.07      或      https://www.gtzyyg.com/CN/Y2016/V28/I2/41

[1] 陈高,代力民,姬兰柱,等.森林生态系统健康评估Ⅰ.模式、计算方法和指标体系[J].应用生态学报,2004,15(10):1743-1749. Chen G,Dai L M,Ji L Z,et al.Assessing forest ecosystem health I. Model,method and index system[J].Chinese Journal of Applied Ecology,2004,15(10):1743-1749.

[2] Abdel-Rahman E M,Mutanga O,Adam E,et al.Detecting Sirex noctilio grey-attacked and lightning-struck pine trees using airborne hyperspectral data,random forest and support vector machines classifiers[J].ISPRS Journal of Photogrammetry and Remote Sensing,2014,88:48-59.

[3] Dodds K J,Orwig D A.An invasive urban forest pest invades natural environments-Asian longhorned beetle in northeastern US Hardwood forests[J].Canadian Journal of Forest Research,2011,41(9):1729-1742.

[4] 郭志华,肖文发,蒋有绪.遥感在林冠动态监测研究中的应用[J].植物生态学报,2003,27(6):851-858. Guo Z H,Xiao W F,Jiang Y X.Applications of remote sensing to monitoring forest canopy dynamics[J].Acta Phytoecologica Sinica,2003,27(6):851-858.

[5] 亓兴兰,刘健,胡宗庆,等.基于纹理特征的SPOT-5影像马尾松毛虫害信息提取[J].西南林业大学学报,2012,32(1):46-50,111. Qi X L,Liu J,Hu Z Q,et al.SPOT-5 image texture analysis based Dendrolimus punctatus damage information collection[J].Journal of Southwest Forestry College,2012,32(1):46-50,111.

[6] Ahern F J,Erdle T,Maclean D A,et al.A quantitative relationship between forest growth rates and thematic mapper reflectance measurements[J].International Journal of Remote Sensing,1991,12(3):387-400.

[7] Bowers W.Forest structural damage assessment using image semi variance[J].Canadian Journal of Remote Sensing,199420:28-36.

[8] 武红敢,黄建文,乔彦友,等.松毛虫早期灾害点遥感监测研究初报[J].林业科学,1995,31(4):379-384. Wu H G,Huang J W,Qiao Y Y,et al.A preliminary study of remote sensing detection of damage by pine caterpillar[J].Scientia Silvae Sinicae,1995,31(4):379-384.

[9] 云丽丽,栾庆书,金若忠,等.辽西地区油松毛虫遥感监测的研究[J].防护林科技,2010(2):14-17. Yun L L,Luan Q S,Jin R Z,et al.Monitoring technique for Dendrolimus tabulaeformis Tsai et Liu by TM imagery in western Liaoning[J].Protection Forest Science and Technology,2010(2):14-17.

[10] Latifi H,Schumann B,Kautz M,et al.Spatial characterization of bark beetle infestations by a multidate synergy of SPOT and Landsat imagery[J].Environmental Monitoring and Assessment,2014,186(1):441-456.

[11] 倪健,吴继友,蒋本和.赤松林受虫害后生物学及光谱学特征的变化[J].植物生态学报,1994,18(4):322-327. Ni J,Wu J Y,Jiang B H.Changes of the biological and spectral characteristics of the pine caterpillar-damaged red pine forest in the spring[J].Acta Phytoecologica Sinica,1994,18(4):322-327.

[12] 吴继友,倪健.松毛虫危害的光谱特征与虫害早期探测模式[J].环境遥感,1995,10(4):250-258. Wu J Y,Ni J.Spectral characteristics of the pine leaves damaged by pine moth and a model for detecting the damage early[J].Remote Sensing of Environment China,1995,10(4):250-258.

[13] 许章华,刘健,余坤勇,等.松毛虫危害马尾松光谱特征分析与等级检测[J].光谱学与光谱分析,2013,33(2):428-433. Xu Z H,Liu J,Yu K Y,et al.Spectral features analysis of Pinus massoniana with pest of Dendrolimus punctatus Walker and levels detection[J].Spectroscopy and Spectral Analysis,2013,33(2):428-433.

[14] 杨俊泉,陈尚文,沈建中,等.马尾松毛虫危害区植被指数时序变化特征研究[J].国土资源遥感,1997,9(4):7-13.doi:10.6046/gtzyyg.1997.04.02. Yang J Q,Chen S W,Shen J Z,et al.Study for the character of NFVI time-series variation of pine caterpillar moth injury region by NOAA satellite image[J].Remote Sensing for Land and Resources,1997,9(4):7-13.doi:10.6046/gtzyyg.1997.04.02.

[15] 许章华,刘健,龚从宏,等.马尾松毛虫寄主有效叶面积指数遥感反演模型研究[J].中南林业科技大学学报,2012,32(10):72-78. Xu Z H,Liu J,Gong C H,et al.Effective leaf area index retrieving models for host of Dendrolimus punctatus Walker[J].Journal of Central South University of Forestry and Technology,2012,32(10):72-78.

[16] 刘志明,晏明,张旭东,等.用气象卫星监测大范围森林虫害方法研究[J].自然灾害学报,2002,11(3):109-114. Liu Z M,Yan M,Zhang X D,et al.Methodical study on monitoring wide-range forest insect pest by meteorsat[J].Journal of Natural Disasters,2002,11(3):109-114.

[17] 亓兴兰,刘健,陈国荣,等.应用MODIS遥感数据监测马尾松毛虫害研究[J].西南林学院学报,2010,30(1):42-46. Qi X L,Liu J,Chen G R,et al.Studies on monitoring of Dendrolimus punctatus damage with MODIS data[J].Journal of Southwest Forestry University,2010,30(1):42-46.

[18] Pu R L,Gong P,Biging G S,et al.Extraction of red edge optical parameters from Hyperion data for estimation of forest leaf area index[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(4):916-921.

[19] Cho M A,Debba P,Mutanga O,et al.Potential utility of the spectral red-edge region of SumbandilaSat imagery for assessing indigenous forest structure and health[J].International Journal of Applied Earth Observation and Geoinformation,2012,16:85-93.

[1] 王茜, 任广利. 高光谱遥感异常信息在阿尔金索拉克地区铜金矿找矿工作中的应用[J]. 自然资源遥感, 2022, 34(1): 277-285.
[2] 吕品, 熊丽媛, 徐争强, 周学铖. 基于FME的矿山遥感监测矢量数据图属一致性检查方法[J]. 自然资源遥感, 2022, 34(1): 293-298.
[3] 曲海成, 王雅萱, 申磊. 多感受野特征与空谱注意力结合的高光谱图像超分辨率算法[J]. 自然资源遥感, 2022, 34(1): 43-52.
[4] 陈洁, 张立福, 张琳珊, 张红明, 童庆禧. 紫外-可见光水质参数在线监测技术研究进展[J]. 自然资源遥感, 2021, 33(4): 1-9.
[5] 高文龙, 张圣微, 林汐, 雒萌, 任照怡. 煤矿开采中SOM的遥感估算和时空动态分析[J]. 自然资源遥感, 2021, 33(4): 235-242.
[6] 刘咏梅, 范鸿建, 盖星华, 刘建红, 王雷. 基于无人机高光谱影像的NDVI估算植被盖度精度分析[J]. 自然资源遥感, 2021, 33(3): 11-17.
[7] 李双权, 马玉凤, 刘勋, 李长春, 杜军. 郑州邙山枣树沟黄土剖面常量元素含量的高光谱反演[J]. 自然资源遥感, 2021, 33(3): 121-129.
[8] 杜程, 李得林, 李根军, 杨雪松. 基于高原盐湖光谱特性下的溶解氧反演应用与探讨[J]. 自然资源遥感, 2021, 33(3): 246-252.
[9] 姜亚楠, 张欣, 张春雷, 仲诚诚, 赵俊芳. 基于多尺度LBP特征融合的遥感图像分类[J]. 自然资源遥感, 2021, 33(3): 36-44.
[10] 臧传凯, 沈芳, 杨正东. 基于无人机高光谱遥感的河湖水环境探测[J]. 自然资源遥感, 2021, 33(3): 45-53.
[11] 王华, 李卫卫, 李志刚, 陈学业, 孙乐. 基于多尺度超像素的高光谱图像分类研究[J]. 自然资源遥感, 2021, 33(3): 63-71.
[12] 蒋校, 钟昶, 连铮, 吴亮廷, 邵治涛. 卫星遥感地质信息产品分类标准研究进展[J]. 自然资源遥感, 2021, 33(3): 279-283.
[13] 舒慧勤, 方俊永, 鲁鹏, 顾万发, 王潇, 张晓红, 刘学, 丁兰坡. 基于多源高分辨率数据的遗址空间考古精细识别研究[J]. 国土资源遥感, 2021, 33(2): 162-171.
[14] 陈栋, 姚维岭. 基于ArcPy与定制ArcToolbox的矿山新增图斑自动编号及方法改进[J]. 国土资源遥感, 2021, 33(2): 262-269.
[15] 肖艳, 辛洪波, 王斌, 崔利, 姜琦刚. 基于小波变换和连续投影算法的黑土有机质含量高光谱估测[J]. 国土资源遥感, 2021, 33(2): 33-39.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
版权所有 © 2015 《自然资源遥感》编辑部
地址:北京学院路31号中国国土资源航空物探遥感中心 邮编:100083
电话:010-62060291/62060292 E-mail:zrzyyg@163.com
本系统由北京玛格泰克科技发展有限公司设计开发