Automatic citrus tree extraction from UAV images and digital surface models using circular Hough transform

Abstract Tree counts and sizes are important information to apply to crop yield estimation and agricultural planning. Therefore, obtaining automatic extraction of trees, their locations, diameters, and counts from remotely sensed data is a challenging task. In this study, a novel approach is proposed for the automatic extraction of citrus trees using unmanned aerial vehicle (UAV) multispectral images (MSIs) and digital surface models (DSMs). The tree boundaries were extracted by using sequential thresholding, Canny edge detection and circular Hough transform algorithms. The performance of the developed approach was assessed on three test areas that include different characteristics with regard to tree counts, diameters, densities and background covers. The proposed tree extraction procedure was applied to DSM that were generated from UAV images (Data Set 1), UAV MSIs (Data Set 2) and both of them together (Data Set 3). The accuracies of the obtained results were assessed using three different techniques that evaluate the tree extraction results according to the counts, areas and locations. The obtained results indicate the success of the developed approach with delineation accuracies that exceeded 80% for each test area using each data set. The most accurate results were obtained when Data Set 1 was used. Although Data Set 2 provides the lowest accuracies when compared with other data sets, the delineation accuracies are still high and can be used especially for counting trees and detecting tree locations.

[1]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Liviu Theodor Ene,et al.  Comparative testing of single-tree detection algorithms under different types of forest , 2011 .

[3]  Kenneth Olofsson,et al.  Comparison of three individual tree crown detection methods , 2005, Machine Vision and Applications.

[4]  Naif Alajlan,et al.  An automatic approach for palm tree counting in UAV images , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[5]  Saudi Arabia,et al.  Histogram Based Circle Detection , 2012 .

[6]  Naoto Yokoya,et al.  Hyperspectral Tree Species Classification of Japanese Complex Mixed Forest With the Aid of Lidar Data , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[7]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[8]  L. Wallace,et al.  Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds , 2016 .

[9]  Alfred Stein,et al.  Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[10]  Morten Andreas Dahl Larsen,et al.  Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions , 2011 .

[11]  P. Gong,et al.  Individual Tree-Crown Delineation and Treetop Detection in High-Spatial-Resolution Aerial Imagery , 2004 .

[12]  F. Gougeon.  A Crown-Following Approach to the Automatic Delineation of Individual Tree Crowns in High Spatial Resolution Aerial Images , 1995 .

[13]  Ville Kankare,et al.  Diameter distribution estimation with laser scanning based multisource single tree inventory , 2015 .

[14]  Hind Taud,et al.  Detection of circular structures on satellite images , 1992 .

[15]  Hao Jiang,et al.  Papaya Tree Detection with UAV Images Using a GPU-Accelerated Scale-Space Filtering Method , 2017, Remote. Sens..

[16]  Yerach Doytsher,et al.  Right‐Angle Rooftop Polygon Extraction in Regularised Urban Areas: Cutting the Corners , 2004 .

[17]  Liviu Theodor Ene,et al.  Single tree detection in heterogeneous boreal forests using airborne laser scanning and area-based stem number estimates , 2012 .

[18]  André Stumpf,et al.  bject-oriented mapping of urban trees using Random Forest lassifiers , 2013 .

[19]  Darius S. Culvenor,et al.  TIDA: an algorithm for the delineation of tree crowns in high spatial resolution remotely sensed imagery , 2002 .

[20]  R. Pu,et al.  A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species , 2012 .

[21]  Terje Gobakken,et al.  Inventory of Small Forest Areas Using an Unmanned Aerial System , 2015, Remote. Sens..

[22]  C. Schmullius,et al.  Comparison of UAV photograph-based and airborne lidar-based point clouds over forest from a forestry application perspective , 2017 .

[23]  Puteh Saad,et al.  Object Detection using Circular Hough Transform , 2005 .

[24]  D. King,et al.  Approaches for optimal automated individual tree crown detection in regenerating coniferous forests , 2005 .

[25]  Carola-Bibiane Schönlieb,et al.  Individual Tree Species Classification From Airborne Multisensor Imagery Using Robust PCA , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[26]  E. Næsset.  Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia , 2007 .

[27]  Yang Liu,et al.  Automatic Forest Mapping at Individual Tree Levels from Terrestrial Laser Scanning Point Clouds with a Hierarchical Minimum Cut Method , 2016, Remote. Sens..

[28]  Le Wang,et al.  How to assess the accuracy of the individual tree-based forest inventory derived from remotely sensed data: a review , 2016 .

[29]  Lindi J. Quackenbush,et al.  A comparison of three methods for automatic tree crown detection and delineation from high spatial resolution imagery , 2011 .

[30]  Linhai Jing,et al.  An individual tree crown delineation method based on multi-scale segmentation of imagery , 2012 .

[31]  Asli Ozdarici-Ok,et al.  Automatic detection and delineation of citrus trees from VHR satellite imagery , 2015 .

[32]  I. Colomina,et al.  Unmanned aerial systems for photogrammetry and remote sensing: A review , 2014 .

[33]  S. Aranganayagi,et al.  EDGE DETECTION USING MULTISPECTRAL THRESHOLDING , 2016 .

[34]  Andrea Berton,et al.  Forestry applications of UAVs in Europe: a review , 2017 .

[35]  Lin Li,et al.  A dual growing method for the automatic extraction of individual trees from mobile laser scanning data , 2016 .

[36]  Enric Pastor,et al.  UAV Flight Experiments Applied to the Remote Sensing of Vegetated Areas , 2014, Remote. Sens..

[37]  Eufemia Tarantino,et al.  A tree counting algorithm for precision agriculture tasks , 2013, Int. J. Digit. Earth.

[38]  M. Pierrot-Deseilligny,et al.  A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery , 2013 .

[39]  Mustafa Turker,et al.  Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[40]  Yi Lin,et al.  A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements , 2010 .

[41]  Arko Lucieer,et al.  An Assessment of the Repeatability of Automatic Forest Inventory Metrics Derived From UAV-Borne Laser Scanning Data , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[42]  Juha Hyyppä,et al.  Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging , 2017, Remote. Sens..

[43]  Jungho Im,et al.  A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classification , 2015 .

[44]  Barry Boots,et al.  Techniques for accuracy assessment of tree locations extracted from remotely sensed imagery. , 2005, Journal of environmental management.

[45]  A. M. Cross,et al.  Detection of circular geological features using the Hough transform , 1988 .

[46]  Fang Qiu,et al.  Individual Tree Segmentation from LiDAR Point Clouds for Urban Forest Inventory , 2015, Remote. Sens..

[47]  L. Tang,et al.  Drone remote sensing for forestry research and practices , 2015, Journal of Forestry Research.

[48]  D. Roberts,et al.  Urban tree species mapping using hyperspectral and lidar data fusion , 2014 .

[49]  Dejan Grigillo,et al.  Automated building extraction from IKONOS images in suburban areas , 2012 .

[50]  M. I. Saripan,et al.  Semi-automatic detection and counting of oil palm trees from high spatial resolution airborne imagery , 2011 .

[51]  Txomin Hermosilla,et al.  Automated extraction of tree and plot-based parameters in citrus orchards from aerial images , 2013 .

[52]  Yinghai Ke,et al.  A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing , 2011 .

[53]  Bin Wu,et al.  Individual tree crown delineation using localized contour tree method and airborne LiDAR data in coniferous forests , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[54]  J. Chris McGlone,et al.  Fusion of HYDICE hyperspectral data with panchromatic imagery for cartographic feature extraction , 1999, IEEE Trans. Geosci. Remote. Sens..

[55]  M. Erikson.  Species classification of individually segmented tree crowns in high-resolution aerial images using radiometric and morphologic image measures , 2004 .

[56]  Pablo J. Zarco-Tejada,et al.  Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods , 2014 .

[57]  Valentyn Tolpekin,et al.  Multitemporal change detection of urban trees using localized region - based active contours in VHR images , 2012 .

[58]  Liviu Theodor Ene,et al.  Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data , 2014 .

[59]  Stephen V. Stehman,et al.  Agent-based region growing for individual tree crown delineation from airborne laser scanning (ALS) data , 2015 .

[60]  F. Agüera,et al.  Automatic greenhouse delineation from QuickBird and Ikonos satellite images , 2009 .

[61]  Barbara Koch,et al.  Prior-knowledge-based single-tree extraction , 2011 .

[62]  Pablo J. Zarco-Tejada,et al.  High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials , 2015, Remote. Sens..

[63]  N. Pfeifer,et al.  Water surface mapping from airborne laser scanning using signal intensity and elevation data , 2009 .

[64]  S. Cui,et al.  Complex building description and extraction based on Hough transformation and cycle detection , 2012 .