多光谱无人机不同飞行高度下苹果树高的提取

doi:10.6048/j.issn.1001-4330.2024.07.018

新疆农业科学 ›› 2024, Vol. 61 ›› Issue (7): 1710-1716.DOI: 10.6048/j.issn.1001-4330.2024.07.018

• 园艺特产·贮藏保鲜加工 • 上一篇下一篇

多光谱无人机不同飞行高度下苹果树高的提取

张振飞¹(), 郭靖²(), 颜安¹(), 侯正清¹, 袁以琳¹, 肖淑婷¹, 孙哲¹

1.新疆农业大学资源与环境学院,乌鲁木齐 830052
2.新疆林业科学院园林绿化研究所,乌鲁木齐 830092

收稿日期:2024-01-25 出版日期:2024-07-20 发布日期:2024-09-04
通信作者: 郭靖(1982-),女,山东人,副研究员,硕士,硕士生导师,研究方向为苹果良种选育与栽培,(E-mail)191315471@qq.com；
颜安(1983 -),男,四川安岳人,教授,博士,硕士生/博士生导师,研究方向为数字农业技术、农业资源与环境,(E-mail) zryanan@163.com
作者简介:张振飞(1998-),男,河南安阳人,硕士研究生,研究方向为农业信息化,(E-mail)1291716283@qq.com
基金资助:
新疆维吾尔自治区重点研发计划项目“新疆杏李、杏等主要果树抗寒关键技术研究”(2023B02026)

Study on extraction of apple tree height at different flight altitudes using multispectral UAV

ZHANG Zhenfei¹(), GUO Jing²(), YAN An¹(), HOU Zhengqing¹, YUAN Yilin¹, XIAO Shuting¹, SUN Zhe¹

1. College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
2. Institute of Landscape Architecture, Xinjiang Academy of Forestry Sciences, Urumqi 830092, China

Received:2024-01-25 Published:2024-07-20 Online:2024-09-04
Supported by:
Xinjiang Uygur Autonomous Region Key Research and Development Project “Research on Key Techniques for Cold Resistance in Major Fruit Trees Such as Xinjiang Apricots (Prunus armeniaca) and Plums (Prunus domestica × armeniaca) ”(2023B02026)

摘要/Abstract

摘要：

【目的】利用多光谱无人机影像快速、准确、无损的获取苹果树高信息,实现无人机遥感技术对苹果树生长状况的监测,并分析无人机飞行高度对树高提取结果的影响。【方法】利用大疆精灵4多光谱无人机分别获取30、60和90 m飞行高度的苹果树无人机影像,经大疆智图(DJI Terra)软件处理生成DOM和DSM影像数据,基于生成的DOM和DSM,利用克里金插值法生成研究区DEM,将DSM和DEM作差生成苹果树CHM提取树高,与实地测量的果树高值进行回归分析和精度验证。【结果】30 m飞行高度平均树高提取精度为88.49%,R²为0.837 8,RMSE为0.4 031 m;60 m飞行高度平均树高提取精度为74.72%,R²为0.6577,RMSE为0.884 6 m;90 m飞行高度平均树高提取精度为56.20%,R²为0.527 3,RMSE为1.476 7 m。【结论】利用多光谱无人机遥感技术可以实现对苹果树高的提取,提取精度随着无人机飞行高度的增加而降低,30 m飞行高度提取结果最佳,90 m飞行高度提取结果最差。在合适的飞行高度内,多光谱无人机遥感技术可以快速、准确、无损的实现对果园果树生长状况的监测,提高果园的管理效率。

关键词: 多光谱无人机; 飞行高度; 苹果树

Abstract:

【Objective】The purpose of this study is to utilize multispectral unmanned aerial vehicle (UAV) imagery to rapidly, accurately, and non-destructively acquire height information of apple trees, aiming to achieve monitoring of apple tree growth conditions using UAV remote sensing technology and analyze the influence of UAV flight height on the extraction results of tree height. 【Methods】The DJI Phantom 4 multispectral UAV was employed to acquire UAV imagery of apple trees at flight heights of 30, 60, and 90 m, respectively. The acquired imagery was processed using DJI Terra software to generate digital orthophoto models (DOM) and digital surface models (DSM). Based on the generated DOM and DSM, a digital elevation model (DEM) of the study area was created using the Kriging interpolation method. The difference between the DSM and DEM was used to generate the canopy height model (CHM) for extracting tree height. Regression analysis and accuracy validation were conducted by comparing the extracted tree heights with field-measured values.【Results】The average accuracy of tree height extraction at a flight height of 30 m was 88.49%, with an R² value of 0.8378 and an RMSE of 0.403,1 m. At a flight height of 60m, the average accuracy of tree height extraction was 74.72%, with an R² value of 0.657,7 and an RMSE of 0.884,6 m. At a flight height of 90 m, the average accuracy of tree height extraction was 56.20%, with an R² value of 0.527,3 and an RMSE of 1.476,7 m. 【Conclusion】The use of multispectral UAV remote sensing technology enables the extraction of apple tree height possible. The extraction accuracy decreases with an increase in UAV flight height. The best results are obtained at a flight height of 30 m, while the poorest results are obtained at a flight height of 90 m. Within appropriate flight heights, multispectral UAV remote sensing technology can rapidly, accurately, and non-destructively monitor the growth conditions of orchard fruit trees, thereby improving the management efficiency for orchard operators.

Key words: multispectral UAV; flight altitude; apple tree

中图分类号:

S127

张振飞, 郭靖, 颜安, 侯正清, 袁以琳, 肖淑婷, 孙哲. 多光谱无人机不同飞行高度下苹果树高的提取[J]. 新疆农业科学, 2024, 61(7): 1710-1716.

ZHANG Zhenfei, GUO Jing, YAN An, HOU Zhengqing, YUAN Yilin, XIAO Shuting, SUN Zhe. Study on extraction of apple tree height at different flight altitudes using multispectral UAV[J]. Xinjiang Agricultural Sciences, 2024, 61(7): 1710-1716.

图/表 6

图1 无人机影像拼接流程

Fig.1 UAV image stitching process

图2 高程采样点

Fig.2 Elevation sampling points

图3 无人机不同飞行高度地面高程值(DEM) 注:a:30 m飞行高度;b:60 m飞行高度;c:90 m飞行高度

Fig.3 Digital elevation model of UAV at different flying heights Note:a:30 m flight altitude;b:60 m flight altitude;c:90 m flight altitude

图4 无人机不同飞行高度冠层高度模型(CHM) 注:a:30 m飞行高度;b:60 m飞行高度;c:90 m飞行高度

Fig.4 Canopy height model of UAV at different flying heights(CHM) Note:a:30 m flight altitude;b:60 m flight altitude;c:90 m flight altitude

表1 提取树高值与实测树高值回归统计

Tab.1 Regression analysis of extracting the measured plant height values and the actual measured plant height values

飞行高度 Flying altitude (m)	精度范围 Accuracy range(%)	平均提取精度 Average extraction accuracy (%)	R²	RMSE (m)
30 60 90	64.26~99.76 10.60~99.90 7.62~91.83	88.49 74.72 56.20	0.837 8 0.657 7 0.527 3	0.403 1 0.884 6 1.476 7

图5 不同飞行高度苹果树高提取值与实测值关系散点图注:蓝、红、绿分别为30、60和90 m飞行高度散点图

Fig.5 Scatter plot of the relationship between extracted values and measured values of apple plant height at different flight heights Note:Blue,red and green are 30,60 and 90 m scatt plot of flight altitude

参考文献 20

[1]	刘宏, 牛荣. 新疆特色林果业现状和发展趋势[J]. 山西农经, 2018, (9): 29-30.
	LIU Hong, NIU Rong. Present situation and development trend of characteristic forest and fruit industry in Xinjiang[J]. Shanxi Agricultural Economy, 2018, (9): 29-30.
[2]	赵达君, 戴泉, 永春芳. 新疆瓜果出口基地发展现状、问题及对策研究[J]. 经济视角(下), 2009, (8): 5-6, 9.
	ZHAO Dajun, DAI Quan, YONG Chunfang. Xinjiang fruits export site’s developing status, problems and relevant measures[J]. Economic Vision, 2009, (8): 5-6, 9.
[3]	韩政伟, 郭靖, 张振飞, 等. 新疆乡土苹果新品种玛平1号的选育[J]. 果树学报, 2023, 40(3): 588-591.
	HAN Zhengwei, GUO Jing, ZHANG Zhenfei, et al. Breeding report of Xinjiang native apple Maping 1[J]. Journal of Fruit Science, 2023, 40(3): 588-591.
[4]	吴佳锐. 阿克苏冰糖心苹果区域品牌建设研究[D]. 武汉: 武汉轻工大学, 2019.
	WU Jiarui. On the Regional Brand Construction of Aksu Candy Heart Apple[D]. Wuhan: Wuhan Polytechnic University, 2019.
[5]	焦亚辉, 颜安, 赵英, 等. 基于无人机影像的沙棘树高提取及叶面积指数反演方法比较[J]. 新疆农业大学学报, 2020, 43(4): 241-251.
	JIAO Yahui, YAN An, ZHAO Ying, et al. Inversion methods comparison of seabuckthorn tree height and leaf area index based on UAV images[J]. Journal of Xinjiang Agricultural University, 2020, 43(4): 241-251.
[6]	万祖毅. 基于无人机遥感的柑橘果树信息提取及应用研究[D]. 重庆: 西南大学, 2020.
	WAN Zuyi. Extraction and Application of Citrus Fruit Tree Information Based on UAV Remote Sensing[D]. Chongqing: Southwest University, 2020.
[7]	张宏鸣, 谭紫薇, 韩文霆, 等. 基于无人机遥感的玉米株高提取方法[J]. 农业机械学报, 2019, 50(5): 241-250.
	ZHANG Hongming, TAN Ziwei, HAN Wenting, et al. Extraction method of maize height based on UAV remote sensing[J]. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(5): 241-250.
[8]	梁永检, 吴文志, 施泽升, 等. 基于无人机RGB遥感的甘蔗株高估测[J]. 作物杂志, 2023, (1): 226-232.
	LIANG Yongjian, WU Wenzhi, SHI Zesheng, et al. Estimation of sugarcane plant height based on UAV RGB remote sensing[J]. Crops, 2023, (1): 226-232.
[9]	Jing L H, Hu B X, Li J L, et al. Automated delineation of individual tree crowns from lidar data by multi-scale analysis and segmentation[J]. Photogrammetric Engineering & Remote Sensing, 2012, 78(12): 1275-1284.
[10]	王佳, 杨慧乔, 冯仲科, 等. 利用轻小型飞机遥感数据建立人工林特征参数模型[J]. 农业工程学报, 2013, 29(8): 164-170, 296.
	WANG Jia, YANG Huiqiao, FENG Zhongke, et al. Model of characteristic parameter for forest plantation with data obtained by light small aerial remote sensing system[J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(8): 164-170, 296.
[11]	王伟. 无人机影像森林信息提取与模型研建[D]. 北京: 北京林业大学, 2015.
	WANG Wei. Forest Information Extraction And Model Building Based on UAV Image[D]. Beijing: Beijing Forestry University, 2015.
[12]	王欣, 陈传法. LiDAR森林冠层高度模型凹坑去除方法[J]. 测绘科学, 2016, 41(12): 157-161.
	WANG Xin, CHEN Chuanfa. Method for removing pits of canopy height model from airborne LiDAR data[J]. Science of Surveying and Mapping, 2016, 41(12): 157-161.
[13]	曹明兰, 张力小, 王强. 无人机遥感影像中行道树信息快速提取[J]. 中南林业科技大学学报, 2016, 36(10): 89-93.
	CAO Minglan, ZHANG Lixiao, WANG Qiang. Rapid extraction of rural house information from UAV remote-sensing images[J]. Journal of Central South University of Forestry & Technology, 2016, 36(10): 89-93.
[14]	白明雄, 张超, 陈棋, 等. 基于无人机可见光遥感的单木树高提取方法研究[J]. 林业资源管理, 2021, (1): 164-172.
	BAI Mingxiong, ZHANG Chao, CHEN Qi, et al. Study on the extraction of individual tree height based on UAV visual spectrum remote sensing[J]. Forest Resources Management, 2021, (1): 164-172.
[15]	王金鑫, 秦子龙, 曹泽宁, 等. 基于八叉树的修正克里金空间插值算法[J]. 郑州大学学报(工学版), 2021, 42(6): 21-27.
	WANG Jinxin, QIN Zilong, CAO Zening, et al. Modified Kriging spatial interpolation algorithm based on octree mechanism[J]. Journal of Zhengzhou University (Engineering Science), 2021, 42(6): 21-27.
[16]	汤国安, 杨昕. ArcGIS地理信息系统空间分析实验教程(2版)[M]. 北京: 科学出版社, 2012: 448-461.
	TANG Guoan, YANG Xin. Experimental course of spatial analysis of ArcGIS geographic information system(2nd ed.)[M]. Beijing: Science Press, 2012: 448-461.
[17]	颜安, 郭涛, 陈全家, 等. 基于无人机影像的棉花株高预测[J]. 新疆农业科学, 2020, 57(8): 1493-1502. DOI
	YAN An, GUO Tao, CHEN Quanjia, et al. Prediction of cotton plant height based on UAV image[J]. Xinjiang Agricultural Sciences, 2020, 57(8): 1493-1502. DOI
[18]	焦亚辉. 基于无人机影像的沙棘表型信息提取及叶面积指数估测[D]. 乌鲁木齐: 新疆农业大学, 2021.
	JIAO Yahui. Phenotypic Information Extraction and Leaf Area Index Estimation of Seabuckthorn Based on UAV Images[D]. Urumqi: Xinjiang Agricultural University, 2021.
[19]	谢巧雅, 余坤勇, 邓洋波, 等. 杉木人工林冠层高度无人机遥感估测[J]. 浙江农林大学学报, 2019, 36(2): 335-342.
	XIE Qiaoya, YU Kunyong, DENG Yangbo, et al. Height measurement of Cunninghamia lanceolata plantations based on UAV remote sensing[J]. Journal of Zhejiang A & F University, 2019, 36(2): 335-342.
[20]	Yu X, Hyypp J, Hyypp H, et al. Effects of flight altitude on tree height estimation using airborne laser scanning[J]. Proceedings of the Isprs Working Group Viii/ 2 Laser Scanners for Forest & Landscape Assessment, 2012.

多光谱无人机不同飞行高度下苹果树高的提取

Study on extraction of apple tree height at different flight altitudes using multispectral UAV

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 6

参考文献 20

相关文章 9

编辑推荐

Metrics

[1]	张振飞, 郭靖, 颜安, 袁以琳, 肖淑婷, 侯正清, 孙哲. 基于多光谱无人机不同飞行高度下苹果树冠幅信息的提取[J]. 新疆农业科学, 2024, 61(6): 1468-1476.
[2]	耿松毅, 孙洪涛, 赵伟琦, 王梅, 芦屹, 马荣. 苹果树腐烂病发生及新型防治药剂筛选[J]. 新疆农业科学, 2024, 61(6): 1461-1467.
[3]	张艺加, 程平, 王磊, 武胜利. 不同灌溉量对矮化密植苹果树生理特性和苹果产量及品质的影响[J]. 新疆农业科学, 2024, 61(5): 1140-1150.
[4]	黄伟, 王宁, 宋博, 王苏玲, 秦新政, 宋素琴, 罗义, 魏增宙, 张丽娟, 王玮. 不同相态娄彻氏链霉菌A144挥发性物质对苹果树腐烂病菌的抑制效果[J]. 新疆农业科学, 2024, 61(10): 2475-2483.
[5]	封帆, 谢开云, 艾比布拉·伊马木, 万江春. 果园生草对苹果园杂草控制、土壤养分及果树营养状况的影响[J]. 新疆农业科学, 2023, 60(4): 982-991.
[6]	李亚鹏, 张王斌, 仪子博. 苹果树腐烂病病原种类及其亲缘关系分析[J]. 新疆农业科学, 2022, 59(3): 700-706.
[7]	牛春林,叶晓芸,艾尼,王振华,热依汗,姜国勇,高雁,宋素琴,楚敏. 克拉玛依果树腐烂病病原菌鉴定及其拮抗菌的筛选[J]. 新疆农业科学, 2018, 55(2): 304-311.
[8]	孙晓霞;王钰婷;牛建新. 新疆苹果树上苹果锈果类病毒(ASSVd)的检测与全序列分析[J]. , 2015, 52(4): 693-698.
[9]	苟巧;张王斌;但红侠;邢红亮;谢新;李春艳;姚永生. 不同寄主来源腐烂病菌对苹果树致病性研究[J]. , 2015, 52(11): 2085-2092.