基于无人机载LiDAR数据的玉米涝灾灾情评估

doi:10.3864/j.issn.0578-1752.2017.15.012

摘要/Abstract

摘要： 【目的】基于无人机平台的遥感技术是目前研究的热点，也是推动现代化农业快速发展的主要力量之一。笔者欲通过分析涝灾研究区激光雷达点云数据反演的玉米冠层高度，快速准确实现玉米涝灾受灾范围监测和灾情评估，为防灾减灾、高产稳产、农业保险理赔等提供依据。拓展无人机载LiDAR数据在农业领域的应用价值，为农业等相关部门快速有效掌握农情信息提供保障。【方法】2016年7月19—20日，以因大暴雨导致涝灾的北京市昌平区一块玉米大田作为研究区，基于无人机平台获取研究区激光雷达数据。通过冠层高度模型（canopy height model，CHM）反演出玉米冠层高度，采用正态统计理论的双阈值划分策略确定阈值，构建基于玉米冠层高度差异的涝灾灾情遥感监测模型，评价玉米涝灾灾情严重程度，并基于地面实测数据进行精度评价。【结果】涝灾发生后，玉米长势存在一定差异，最明显的差异体现在玉米植株高度。基于正态统计理论和野外测量，最终确定严重涝灾玉米冠层高度为0.30—0.84 m，中度涝灾玉米冠层高度为0.84—1.70 m，冠层高度1.70 m以上为轻度受灾区域。通过野外实测样本对无人机载LiDAR数据估算结果进行混淆矩阵分析，总体分类精度达到72.15%，Kappa系数为0.44。结合数码影像做进一步验证，结果表明研究区玉米涝灾遥感空间制图结果与数码影像结果基本一致。【结论】通过无人机载LiDAR数据能实现玉米冠层高度反演，结合涝灾后玉米植株高度差异特征能有效反映不同涝灾程度，实现区域尺度下玉米涝灾受灾范围监测和灾情等级评估，有利于便捷高效获取灾情灾害信息。

关键词: 玉米, 涝灾, 灾情评估, 无人机载LiDAR, 冠层高度

Abstract: 【Objective】Unmanned aerial vehicle (UAV) remote sensing technology is a hot research topic in the remote sensing sector, which is also one of the forces driving the development of modern agriculture. The objective of this study is to quickly and precisely measure the area of maize waterlogging disaster and evaluate disaster levels by analyzing maize canopy height derived from UAV LiDAR point cloud data. Thus it can provide a guideline for disaster prevention and mitigation, high and stable yield, agricultural insurance claims, etc. The aim of this study is to expand the application of UAV LiDAR data in agriculture, and provide a guarantee for agriculture field to quickly and effectively master agricultural information.【Method】The experiment was carried out and the UAV LiDAR data were obtained in Changping District, Beijing, where suffered a heavy rainstorm which led to a large-scale maize waterlogging on July 19-20, 2016. LiDAR point cloud data were classified and extracted, and canopy height of maize was obtained by LiDAR point cloud data from canopy height model (CHM). A double threshold partition strategy based on the normal statistics theory was adopted to determine the thresholds and a remote sensing monitoring model for maize waterlogging was built by analyzing the differences of canopy heights to evaluate the disaster levels of the maize waterlogging. Finally, the accurate assessment of the model was conducted by comparing the in-field measured data with predicted results from the built model.【Result】(1) After the occurrence of waterlogging of maize, there was a significant difference of maize growth between pre and post the disaster, and maize height showed the most obvious difference after the disaster. The maize canopy heights of final severe waterlogging, medium waterlogging, and the slight waterlogging were 0.30-0.84 m, 0.84-1.70 m, and above 1.70 m, respectively. (2) The confusion matrix analysis on the results estimated using the airborne LiDAR data was performed via ground survey samples; the overall classification accuracy of waterlogging degree reached 72.15%, and the Kappa coefficient was 0.44. (3) In general, remote sensing mapping was consistent with the monitoring data from the digital images.【Conclusion】The maize canopy height inversion can be achieved by UAV LiDAR data, and the waterlogging levels can be effectively reflected by the differences in maize plant heights. UAV LiDAR data can measure the area of maize waterlogging and evaluate disaster levels at regional scale, providing a convenient and efficient way to acquire the disaster information.

Key words: maize, waterlogging, evaluation of disaster level, unmanned aerial vehicle (UAV) LiDAR, canopy height

甘平，董燕生，孙林，杨贵军，李振海，杨凡，王立志，王建雯. 基于无人机载LiDAR数据的玉米涝灾灾情评估[J]. 中国农业科学, 2017, 50(15): 2983-2992.

GAN PING, DONG YanSheng, SUN Lin, YANG GuiJun, LI ZhenHai, YANG Fan, WANG LiZhi, WANG JianWen. Evaluation of Maize Waterlogging Disaster Using UAV LiDAR Data[J]. Scientia Agricultura Sinica, 2017, 50(15): 2983-2992.

0
/ / 推荐

导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2017.15.012

https://www.chinaagrisci.com/CN/Y2017/V50/I15/2983

参考文献

[1] 蒋尚明, 王友贞, 汤广民, 金菊良, 付娟. 淮北平原主要农作物涝渍灾害损失评估研究. 水利水电技术, 2011, 42(8): 63-67.

Jiang S M, Wang Y Z, Tang G M, Jin J L, Fu J. Study on assessment of loss form waterlogging disaster for main crops within Huaibei Plain. Water Resources and Hydropower Engineering, 2011, 42(8): 63-67. (in Chinese)

[2] Ahmed F, Rafii M Y, Ismail M R, Juraimi A S, Rahim H A, Asfaliza R, Latif M A. Waterlogging tolerance of crops: Breeding, mechanism of tolerance, molecular approaches, and future prospects. Biomed Research International, 2013: 963525. DOI: 10.1155/2013/963525.

[3] 刘忠, 黄峰, 李保国. 2003-2011年中国粮食增产的贡献因素分析. 农业工程学报, 2013, 29(23): 1-8.

Liu Z, Huang F, Li B G. Investigating contribution factors to China’s grain output increase in period of 2003 to 2011. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(23): 1-8. (in Chinese)

[4] 余卫东, 冯利平, 胡程达, 彭记永. 苗期涝渍对黄淮地区夏玉米生长和产量的影响. 生态学杂志, 2015, 34(8): 2161-2166.

Yu W D, Feng L P, Hu C D, Peng J Y. Effects of waterlogging during seedling stage on the growth and yield of summer maize in Huang-Huai Region. Chinese Journal of Ecology, 2015, 34(8): 2161-2166. (in Chinese)

[5] 顾晓鹤, 韩立建, 王纪华, 黄文江, 何馨. 中低分辨率小波融合的玉米种植面积遥感估算. 农业工程学报, 2012, 28(3): 203-209.

Gu X H, Han L J, Wang J H, Huang W J, He X. Estimation of maize planting area based on wavelet fusion of multi-resolution images. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(3): 203-209. (in Chinese)

[6] 郭伟, 赵春江, 顾晓鹤, 黄文江, 马智宏, 王慧芳, 王大成. 乡镇尺度的玉米种植面积遥感监测. 农业工程学报, 2011, 27(9): 69-74.

Guo W, Zhao C J, Gu X H, Huang W J, Ma Z H, WANG H F, Wang D C. Remote sensing monitoring of maize planting areas at town level. Transactions of the Chinese Society of Agricultural Engineering, 2011, 27(9): 69-74. (in Chinese)

[7] Qiu F, Zheng Y, Zhang Z, Xu S. Mapping of QTL associated with waterlogging tolerance during the seedling stage in maize. Annals of Botany, 2007, 99(6): 1067-1081.

[8] 杨晓琳, 黄晶, 陈阜, 褚庆全. 黄淮海农作区玉米需水量时空变化特征比较研究. 中国农业大学学报, 2011, 16(5): 26-31.

Yang X L, Huang J, Chen F, CHU Q Q. Comparison of temporal and spatial variation of water requirements of corn in Huang-huai-hai farming system region. Journal of China Agricultural University, 2011, 16(5): 26-31. (in Chinese)

[9] 南纪琴, 肖俊夫, 刘战东. 黄淮海夏玉米高产栽培技术研究. 中国农学通报, 2010, 26(21):106-110.

Nan J Q, Xiao J F, Liu Z D. Study on the technologies of maize high-yield cultivation in Huang Huai Hai. Chinese Agricultural Science Bulletin, 2010, 26(21): 106-110. (in Chinese)

[10] 余卫东, 冯利平, 盛绍学, 石磊. 黄淮地区涝渍胁迫影响夏玉米生长及产量. 农业工程学报, 2014, 30(13): 127-136.

Yu W D, Feng L P, Sheng S X, Shi L. Effect of waterlogging at jointing and tasseling stages on growth and yield of summer maize. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(13): 127-136. (in Chinese)

[11] 刘祖贵, 刘战东, 肖俊夫, 南纪琴, 巩文军. 苗期与拔节期淹涝抑制夏玉米生长发育、降低产量. 农业工程学报, 2013, 29(5): 44-52.

Liu Z G, Liu Z D, Xiao J F, Nan J Q, Gong W J. Waterlogging at seedling and jointing stages inhibits growth and development, reduces yield in summer maize. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(5): 44-52. (in Chinese)

[12] 周新国, 韩会玲, 李彩霞, 郭树龙, 郭冬冬, 陈金平. 拔节期淹水玉米的生理性状和产量形成. 农业工程学报, 2014, 30(9): 119-125.

Zhou X G, Han H L, Li C X, Guo S L, Guo D D, Chen J P. Physiological characters and yield formation of corn (Zea mays L.) under waterlogging stress in jointing stage. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(9): 119-125. (in Chinese)

[13] 马玉平, 孙琳丽, 俄有浩. 黄淮海夏玉米不同发育阶段对旱涝灾害的敏感性. 自然灾害学报, 2015(6): 90-96.

Ma Y P, Sun L L, E Y H. Sensitivity of summer maize in different developmental stages in Huang-Huai-Hai plain to drought and waterlogging. Journal of Natural Disasters, 2015(6): 90-96. (in Chinese)

[14] 王矿, 薛亚峰, 王友贞, 汤广民, 胡铁松, 袁宏伟. 玉米涝渍胁迫的水分产量关系试验研究. 灌溉排水学报, 2012, 31(6): 67-70.

Wang K, Xue Y F, Wang Y Z, Tang G M, Hu T S, Yuan H W. Experimental study of relationship between water and yield of maize. Journal of Irrigation and Drainage, 2012, 31(6): 67-70. (in Chinese)

[15] Zou X L, Jiang Y Y, Liu L, Zhang Z X, Zheng Y L. Identification of transcriptome induced in roots of maize seedlings at the late stage of waterlogging. BMC Plant Biology, 2010, 10(1): 315-319.

[16] 王立志, 顾晓鹤, 胡圣武, 杨贵军, 王磊, 范友波, 王艳杰. 基于多时相HJ-1B CCD影像的玉米倒伏灾情遥感监测. 中国农业科学, 2016, 49(21): 4120-4129.

Wang L Z, Gu X H, Hu S W, Yang G J, Wang L, Fan Y B, Wang Y J. Remote sensing monitoring of maize lodging disaster with multi-temporal HJ-1B CCD image. Scientia Agricultura Sinica, 2016, 49(21): 4120-4129. (in Chinese)

[17] 徐鹏, 顾晓鹤, 邱贺, 孟鲁闽. 基于多时相HJ影像的水稻洪涝灾情和产量监测. 灾害学, 2014, 29(2): 188-192.

Xu P, Gu X H, Qiu H, Meng L M. Monitoring of disaster situation and yield of rice under flood and waterlogging based on multi-temporal HJ images. Journal of Catastrophology, 2014, 29(2): 188-192. (in Chinese)

[18] 郭庆华, 刘瑾, 陶胜利, 薛宝林, 李乐, 徐光彩, 李文楷, 吴芳芳, 李玉美, 陈琳海, 庞树鑫. 激光雷达在森林生态系统监测模拟中的应用现状与展望. 科学通报, 2014(6): 459-478.

Guo Q H, Liu J, Tao S L, Xue B L, Li L, Xu G C, Li W K, Wu F F, Li Y M, Chen L H, Pang S X. Perspectives and prospects of LiDAR in forest ecosystem monitoring and modeling. Chinese Science Bulletin, 2014(6): 459-478. (in Chinese)

[19] SOLODUKHIN V I, ZUKOV A J, MAZUGIN I N. Laser aerial profiling of a forest. Lew Niilkh Leningrad Lesnoe Khozyaistvo, 1977(10): 53-58.

[20] Næsset E. Practical large-scale forest stand inventory using a small-footprint airborne scanning laser. Scandinavian Journal of Forest Research, 2004, 19(2): 164-179.

[21] García M, Riaño D, Chuvieco E, Danson F M. Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data. Remote Sensing of Environment, 2010, 114(4): 816-830.

[22] Simonson W D, Allen H D, Coomes D A. Remotely sensed indicators of forest conservation status: Case study from a Natura 2000 site in southern Portugal. Ecological Indicators, 2013, 24(1): 636-647.

[23] 庞勇, 赵峰, 李增元, 周淑芳, 邓广, 刘清旺, 陈尔学. 机载激光雷达平均树高提取研究. 遥感学报, 2008, 12(1): 152-158.

Pang Y, Zhao F, Li Z Y, Zhou S F, Deng G, Liu Q W, Chen E X. Forest height inversion using airborne LiDAR technology. Journal of Remote Sensing, 2008, 12(1): 152-158. (in Chinese)

[24] 董立新, 李贵才, 唐世浩. 中国南方森林冠顶高度LiDAR反演—以江西省为例. 遥感学报, 2011, 15(6): 1301-1314.

Dong L X, Li G C, Tang S H. Inversion of forest canopy height in south of China by integrating GLAS and MERSI: The case of Jianxi province in China. Journal of Remote Sensing, 2011, 15(6): 1301-1314. (in Chinese)

[25] 周梦维, 柳钦火, 刘强, 肖青. 基于机载小光斑全波形LiDAR的作物高度反演. 农业工程学报, 2010, 26(8): 183-188.

Zhou M W, Liu Q H, Liu Q, Xiao Q. Inversion for crop height by small-footprint-waveform airborne LiDAR. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(8): 183-188. (in Chinese)

[26] D'Oliveira M V N, Reutebuch S E, Mcgaughey R J, Andersen H E. Estimating forest biomass and identifying low-intensity logging areas using airborne scanning LiDAR in Antimary State Forest, Acre State, Western Brazilian Amazon. Remote Sensing of Environment, 2012, 124: 479-491.

[27] 邵光成, 俞双恩, 刘娜, 徐立波. 以涝渍连续抑制天数为冬小麦排水指标的试验. 农业工程学报, 2010, 26(8): 56-60.

Shao G C, Yu S E, Liu N, Xu L B. Study on continuous days of water logging and excessive soil water as drainage index of wheat. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(8): 56-60. (in Chinese)

[28] 余卫东, 冯利平, 刘荣花. 玉米涝渍灾害研究进展与展望. 玉米科学, 2013(4): 143-147.

Yu W D, Feng L P, Liu R H. Research progress and prospective of waterlogging on maize. Journal of Maize Sciences, 2013(4): 143-147. (in Chinese)

[29] 赵春江. 农业遥感研究与应用进展. 农业机械学报, 2014, 45(12): 277-293.

Zhao C J. Advances of research and application in remote sensing for agriculture. Transactions of the Chinese Society of Agricultural Machinery, 2014, 45(12): 277-293. (in Chinese)

[30] 钱龙, 王修贵, 罗文兵, 吴琳. 涝渍胁迫对棉花形态与产量的影响. 农业机械学报, 2015, 46(10): 136-143.

Qian L, Wang X G, Luo W B, Wu L. Effects of waterlogging stress on morphology and yield of cotton. Transactions of the Chinese Society of Agricultural Machinery, 2015, 46(10): 136-143. (in Chinese)

[31] Li W, Niu Z, Huang N, Wang C, Gao S, Wu C Y. Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye city, Northwest China. Ecological Indicators, 2015, 57(2): 486-496.

[32] 史振声, 李海燕, 李凤海, 吴玉群, 杨翠翠, 王志斌, 王宏伟, 吕香玲, 朱敏. 玉米株高的年际间变化及其与产量的关系研究. 玉米科学, 2013(5): 24-29.

Shi Z S, Li H Y, Li F H, Wu Y Q, Yang C C, Wang Z B, Wang H W, LÜ X L, Zhu M. Relationship between the interannual change of maize height and yield. Journal of Maize Sciences, 2013(5): 24-29. (in Chinese)