Single Tree Segmentation in Close-Planting Orchard Using UAV Digital Image

XU Weimeng; YANG Hao; LI Zhenhong; CHENG Jinpeng; LIN Hate; YANG Guijun

doi:10.13203/j.whugis20220024

Volume 42 Issue 11

Nov. 2022

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2022 > 47(11): 1906-1916. > DOI: 10.13203/j.whugis20220024

XU Weimeng, YANG Hao, LI Zhenhong, CHENG Jinpeng, LIN Hate, YANG Guijun. Single Tree Segmentation in Close-Planting Orchard Using UAV Digital Image[J]. Geomatics and Information Science of Wuhan University, 2022, 47(11): 1906-1916. DOI: 10.13203/j.whugis20220024

Citation:

PDF (35953 KB)

Single Tree Segmentation in Close-Planting Orchard Using UAV Digital Image

XU Weimeng^{1, 2, 3,},
YANG Hao^{2, 3},
LI Zhenhong^1, ,,
CHENG Jinpeng^{2, 3, 4},
LIN Hate¹,
YANG Guijun^{2, 3}

1.
College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
2.
Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Beijing 100097, China
3.
Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
4.
School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China

Funds:

The National Natural Science Foundation of China 42171303

the National Key Research and Development Program of China 2017YFE0122500

Guangdong Provincial Key Research and Development Program 2019B020216001

More Information

Author Bio:
XU Weimeng, postgraduate, specializes in agricultural remote sensing. E-mail: xuweimeng1212@163.com
Corresponding author:
LI Zhenhong, PhD, professor. E-mail: zhenhong.li@chd.edu.cn
Received Date: January 06, 2022
Available Online: November 15, 2022
Published Date: November 04, 2022

Graphical Abstract

Abstract

Abstract

Objectives Single tree canopy extraction is of great significance for fruit tree health status, nutritional composition, and yield prediction.As a low-cost, low-risk data source, high-resolution remote sensing images obtained by drones provide new technical means for accurately estimating tree numbers and delineating tree canopy profiles. Using unmaned aerial vehicle(UAV) digital images as the data source, a single-tree segmentation algorithm based on regional seed blocks is proposed to solve the single-tree segmentation problem of densely planted fruit trees.
Methods The canopy of the fruit tree is extracted by the maximum likelihood method to generate digital surface model (DSM)of the canopy, and Gaussian filter is combined with morphological opening and self-adapted threshold segmentation generates regional seed blocks as the basis for tree statistics and as the marker of the marked-controlled watered segmentation.
Results The results show that the overall tree recall rate is 95.22%, the precision rate is 99.09%. The overall accuracy rate of single tree contour extraction is 93.45%, the overall omission error is 5.87%, and the overall commission error is 0.90%. Compared with the previous local maximum seed point extraction results, the overall accuracy is 18.66% higher, and the precision of the fine crown contour extraction is 17.75% higher.
Conclusions The watershed method based on the regional seed block can effectively prevent the overlapping area of the canopy from being repeatedly divided into multiple fruit trees. On the basis of preserving the canopy outline of the fruit tree to the greatest extent, the segmentation error of the fruit tree is reduced.It provides a reference for the method of extracting the crown of a single fruit tree in a densely planted orchard in flat terrain.
- unmaned aerial vehicle(UAV),
- tree crown delineation,
- marked-controlled watered segmentation,
- digital image

FullText(HTML)

References (35)

References

[1]	杨全月, 董泽宇, 马振宇, 等. 基于SfM的针叶林无人机影像树冠分割算法[J]. 农业机械学报, 2020, 51(6): 181-190 https://www.cnki.com.cn/Article/CJFDTOTAL-NYJX202006019.htm Yang Quanyue, Dong Zeyu, Ma Zhenyu, et al. Conigerous Forest Crown Segmentation Algorithm of UAV Images Based on SfM[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(6): 181-190 https://www.cnki.com.cn/Article/CJFDTOTAL-NYJX202006019.htm
[2]	杨曦光, 于颖, 范文义. 森林冠层光谱与林下背景光谱尺度差异分析[J]. 武汉大学学报∙信息科学版, 2020, 45(4): 511-516 Yang Xiguang, Yu Ying, Fan Wenyi. Analysis of Scale Difference Between Forest Canopy and BackGround Reflectances[J]. Geomatics and Information Science of Wuhan University, 2020, 45(4): 511-516 光谱与林下背景光谱尺度差异
[3]	于颖, 宋张亮, 范文义, 等. 植被冠层光谱和叶片光谱的尺度转换[J]. 武汉大学学报∙信息科学版, 2018, 43(10): 1560-1565 doi: 10.13203/j.whugis20160552 Yu Ying, Song Zhangliang, Fan Wenyi, et al. Scale Conversion from Canopy Spectra to Leaf Spectra[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1560-1565 doi: 10.13203/j.whugis20160552
[4]	胡凯龙, 刘清旺, 崔希民, 等. 多源遥感数据支持下的区域性森林冠层高度估测[J]. 武汉大学学报∙信息科学版, 2018, 43(2): 289-298 doi: 10.13203/j.whugis20160066 Hu Kailong, Liu Qingwang, Cui Ximin, et al. Regional Forest Canopy Height Estimation Using Multi-source Remote Sensing Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(2): 289-298 doi: 10.13203/j.whugis20160066
[5]	Wang Z, Underwood J, Walsh K B. Machine Vision Assessment of Mango Orchard Flowering [J]. Computers and Electronics in Agriculture, 2018, 151: 501-511
[6]	陈日强, 李长春, 杨贵军, 等. 无人机机载激光雷达提取果树单木树冠信息[J]. 农业工程学报, 2020, 36(22): 50-59 https://www.cnki.com.cn/Article/CJFDTOTAL-NYGU202022007.htm Chen Riqiang, Li Changchun, Yang Guijun, et al. Extraction of Crown Information from Individual Fruit Tree by UAV LiDAR[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(22): 50-59 https://www.cnki.com.cn/Article/CJFDTOTAL-NYGU202022007.htm
[7]	Yan W, Guan H, Cao L, et al. A Self-adaptive Mean Shift Tree-Segmentation Method Using UAV LiDAR Data [J]. Remote Sensing, 2020, 12(3): 515 doi: 10.3390/rs12030515
[8]	Yan W, Guan H, Cao L, et al. An Automated Hierarchical Approach for Three-Dimensional Segmentation of Single Trees Using UAV LiDAR Data [J]. Remote Sensing, 2018, 10(12): 1999 doi: 10.3390/rs10121999
[9]	Zhao D, Pang Y, Li Z, et al. Filling Invalid Values in a LiDAR-Derived Canopy Height Model with Morphological Crown Control [J]. International Journal of Remote Sensing, 2013, 34(13): 4636-4654
[10]	Gougeon F A. A Crown-Following Approach to the Automatic Delineation of Individual Tree Crowns in High Spatial Resolution Aerial Images[J]. Canadian Journal of Remote Sensing, 1995, 21(3): 274-284.
[11]	Brandtberg T, Walter F. Automated Delineation of Individual Tree Crowns in High Spatial Resolution Aerial Images by Multiple-Scale Analysis [J]. Machine Vision and Applications, 1998, 11(2): 64-73
[12]	Jing L, Hu B, Noland T, et al. An Individual Tree Crown Delineation Method Based on Multi-scale Segmentation of Imagery [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 70: 88-98
[13]	Dong X, Zhang Z, Yu R, et al. Extraction of Information About Individual Trees from High-Spatial-Resolution UAV-Acquired Images of an Orchard [J]. Remote Sensing, 2020, 12(1): 133
[14]	Pollock R. The Automatic Recognition of Individual Trees in Aerial Images of Forests Based on a Synthetic Tree Crown Image Model [D]. Vancouver: University of British Columbia, 1996
[15]	Tarp-Johansen M J. Automatic Stem Mapping in Three Dimensions by Template Matching from Aerial Photographs [J]. Scandinavian Journal of Forest Research, 2002, 17(4): 359-368
[16]	Meyer F, Beucher S. Morphological Segmentation [J]. Journal of Visual Communication and Image Representation, 1990, 1(1): 21-46
[17]	Ke Y, Quackenbush L J. A Review of Methods for Automatic Individual Tree-Crown Detection and Delineation from Passive Remote Sensing [J]. International Journal of Remote Sensing, 2011, 32(17): 4725-4747
[18]	Wang L, Gong P, Biging G S. Individual Tree-Crown Delineation and Treetop Detection in High-Spatial-Resolution Aerial Imagery [J]. Photogrammetric Engineering and Remote Sensing, 2004, 70(3): 351-357
[19]	Dralle K, Rudemo M. Stem Number Estimation by Kernel Smoothing of Aerial Photos [J]. Canadian Journal of Forest Research, 1996, 26(7): 1228-1236
[20]	Zhao D, Pang Y, Li Z, et al. Isolating Individual Trees in a Closed Coniferous Forest Using Small Footprint LiDAR Data [J]. International Journal of Remote Sensing, 2014, 35(20): 7199-7218
[21]	Dralle K, Rudemo M. Automatic Estimation of Individual Tree Positions from Aerial Photos [J]. Canadian Journal of Forest Research, 1997, 27(11): 1728-1736 http://forest.ckcest.cn/d/hxwx/AVkIo2DC49MUqoKBL_dP.html
[22]	Ok A O, Ozdarici-Ok A. 2-D Delineation of Individual Citrus Trees from UAV-Based Dense Photogrammetric Surface Models [J]. International Journal of Digital Earth, 2018, 11(6): 583-608
[23]	Xu X, Zhou Z, Tang Y, et al. Individual Tree Crown Detection from High Spatial Resolution Imagery Using a Revised Local Maximum Filtering [J]. Remote Sensing of Environment, 2021, 258: 112397
[24]	雷浩川. 多分类器集成的遥感影像分类研究[D]. 北京: 中国地质大学(北京), 2018 Lei Haochuan. Clasification of Remote Sensing Ima‑ges with Multiple Classifier Ensembles[D] Beijing: China University of Geosciences(Beijing), 2018
[25]	Soille P. Morphological Image Analysis: Principles and Applications [M]. Berlin: Springer, 2013
[26]	Mu Y, Fujii Y, Takata D, et al. Characterization of Peach Tree Crown by Using High-Resolution Images from an Unmanned Aerial Vehicle [J]. Horticulture Research, 2018, 5(1): 1-10
[27]	郭昱杉, 刘庆生, 刘高焕, 等. 基于标记控制分水岭分割方法的高分辨率遥感影像单木树冠提取[J]. 地球信息科学学报, 2016, 18(9): 1259-1266 https://www.cnki.com.cn/Article/CJFDTOTAL-DQXX201609015.htm Guo Yushan, Liu Qingsheng, Liu Gaohuan, et al. Individual Tree Crown Extraction of High-Resolution Image Based on Marker-Controlled Watershed Segmentation Method[J]. Journal of Geo-information Science, 2016, 18(9): 1259-1266 https://www.cnki.com.cn/Article/CJFDTOTAL-DQXX201609015.htm
[28]	Chen Q, Baldocchi D, Gong P, et al. Isolating Individual Trees in a Savanna Woodland Using Small Footprint LiDAR Data [J]. Photogrammetric Engineering and Remote Sensing, 2006, 72(8): 923-932
[29]	Huang H, Li X, Chen C. Individual Tree Crown Detection and Delineation from Very-High-Resolution UAV Images Based on Bias Field and Marker-Controlled Watershed Segmentation Algorithms [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(7): 2253-2262
[30]	Deng G, Li Z. An Improved Marker-Controlled Watershed Crown Segmentation Algorithm Based on High Spatial Resolution Remote Sensing Imagery [M]//Recent Advances in Computer Science and Information Engineering. Berlin, Heidelberg: Springer, 2012: 567-572
[31]	Pouliot D, King D, Bell F, et al. Automated Tree Crown Detection and Delineation in High-Resolution Digital Camera Imagery of Coniferous Forest Regeneration [J]. Remote Sensing of Environment, 2002, 82(2/3): 322-334
[32]	Woebbecke D M, Meyer G E, von Bargen K, et al. Color Indices for Weed Identification Under Various Soil, Residue, and Lighting Conditions [J]. Transactions of the ASAE, 1995, 38(1): 259-269
[33]	Qi C, Baldocchi D, Gong P, et al. Isolating Individual Trees in a Savanna Woodland Using Small Footprint LiDAR Data[J]. Photogrammetric Engineering and Remote Sensing, 2006, 72(8): 923-932
[34]	Dong X Y, Zhang Z C, Yu R Y, et al. Extraction of Information About Individual Trees from High-Spatial-Resolution UAV-Acquired Images of an Orchard [J]. Remote Sensing, 2020, 12(1): 133
[35]	李旭. 基于无人机影像的林木冠幅轮廓提取[D]. 福州: 福州大学, 2018 Li Xu. Individual Tree Crown Detection and Delineation Based on UAV Images[D]. Fuzhou: Fuzhou University, 2018

[1]	ZHU Shaolin, YUE Dongjie, HE Lina, CHEN Jian, LIU Shengnan. BDS-2/BDS-3 Joint Triple-Frequency Precise Point Positioning Models and Bias Characteristic Analysis[J]. Geomatics and Information Science of Wuhan University, 2023, 48(12): 2049-2059. DOI: 10.13203/j.whugis20210273
[2]	LIU Zhiqiang, YUE Dongjie, WANG Hu, ZHENG Dehua. An Approach for Real-Time GPS/GLONASS Satellite Clock Estimation with GLONASS Code Inter-Frequency Biases Compensation[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1209-1215. DOI: 10.13203/j.whugis20150542
[3]	RUAN Rengui, WU Xianbing, FENG Laiping. Comparison of Observation Models and Ionospheric Elimination Approaches for Single Frequency Precise Point Positioning[J]. Geomatics and Information Science of Wuhan University, 2013, 38(9): 1023-1028.
[4]	ZOU Xuan, JIANG Weiping, SU Lina, LIU Jingnan. A New Single-Frequency PPP Method Using Dynamic Reference Network[J]. Geomatics and Information Science of Wuhan University, 2013, 38(4): 403-407.
[5]	TU Rui, HUANG Guanwen, ZHANG Qin, WANG Li. PPP Algorithm of Single Frequency Based on Corrections of Single-base Station and Ionospheric Parameters Estimation[J]. Geomatics and Information Science of Wuhan University, 2012, 37(2): 170-173.
[6]	TU Rui, HUANG Guanwen, ZHANG Qin, WANG Li. The Research of Dual Frequency Solution Method for Single Frequency Precise Point Positioning(PPP) Based on SEID Model[J]. Geomatics and Information Science of Wuhan University, 2011, 36(10): 1187-1190.
[7]	SHI Chuang, GU Shengfeng, GENG Changjiang, SONG Weiwei. High-Precision Single-Frequency Point Positioning with Randomness of Ionosphere Delay Correction in Consideration[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 807-810.
[8]	LIU Jihua, OU Jikun, SUN Baoqi, ZHONG Shiming. The GEO Satellite Precise Orbit Determination Based on Inter-satellite Single Difference Method[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 24-28.
[9]	SONG Weiwei, SHI Chuang, YAO Yibin, YE Shirong. Ionosphere Delay Processing Methods and Positioning Precision of Single Frequency Precise Point Positioning[J]. Geomatics and Information Science of Wuhan University, 2009, 34(7): 778-781.
[10]	ZHANG Xiaohong, LI Xingxing, GUO Fei, ZHANG Ming. Realization and Precision Analysis of Single-Frequency Precise Point Positioning Software[J]. Geomatics and Information Science of Wuhan University, 2008, 33(8): 783-787.

Cited By

Cited by

Periodical cited type(11)

1.	段博文，白征东，郭锦萍. 北斗二号卫星伪距偏差分析与建模. 测绘工程. 2024(02): 18-27 .
2.	高扬，沙海，楚恒林，王梦丽. 北斗B1C、B2a信号非理想性分析及接收约束建议. 武汉大学学报(信息科学版). 2023(04): 587-592 .
3.	耿涛，李钟兴，谢新，马壮，赵齐乐. GNSS接收机伪距偏差确定方法及其对定位的影响. 武汉大学学报(信息科学版). 2023(07): 1134-1145 .
4.	周中华，万祥，程艳，刘志忠，汪文君，张雪丽. 一种地基GNSS接收机差分码偏差估算方法. 空间科学学报. 2022(01): 170-178 .
5.	许海林，周恩泽，童梦想，鄂盛龙，田翔，罗颖婷. GPS/BDS/Galileo单点定位精度分析. 测绘地理信息. 2022(04): 19-24 .
6.	李浩东，赵齐乐，陶钧，龙宇浩. 北斗三号卫星FCB估计及其模糊度固定. 武汉大学学报(信息科学版). 2022(09): 1439-1446 .
7.	慕仁海，党亚民，许长辉. BDS-3新频点单点定位研究. 测绘通报. 2021(03): 12-17 .
8.	毛飞宇，龚晓鹏，辜声峰，王琛琛，楼益栋. 北斗三号卫星导航信号接收机端伪距偏差建模与验证. 测绘学报. 2021(04): 457-465 .
9.	徐宗秋，丁新展，徐彦田，唐龙江，李磊，胡艳阳. BDS静态精密单点定位模糊度固定解精度分析. 测绘科学. 2019(07): 30-34 .
10.	李森，周命端，陈积旭. 北斗数据工程控制网应用实验及精度分析. 测绘科学. 2019(09): 1-6 .
11.	唐卫明，刘前，高柯夫，邓辰龙，崔健慧，沈明星. 北斗伪距码偏差对基线解算的影响分析. 武汉大学学报(信息科学版). 2018(08): 1199-1206 .

Other cited types(13)

Get Citation

PDF

XML

Article views (1023) PDF downloads (164) Cited by(24)

Single Tree Segmentation in Close-Planting Orchard Using UAV Digital Image

Abstract

References

Related Articles

Cited by

Periodical cited type(11)

Other cited types(13)

Catalog

Related

Single Tree Segmentation in Close-Planting Orchard Using UAV Digital Image

Abstract

References

Related Articles

Cited by

Periodical cited type(11)

Other cited types(13)

Catalog

Related

Export File

Citation

Format

Content