{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T09:20:34Z","timestamp":1780392034427,"version":"3.54.1"},"reference-count":60,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2016,3,17]],"date-time":"2016-03-17T00:00:00Z","timestamp":1458172800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The invasive emerald ash borer (EAB, Agrilus planipennis Fairmaire) infects and eventually kills endemic ash trees and is currently spreading across the Great Lakes region of North America. The need for early detection of EAB infestation is critical to managing the spread of this pest. Using WorldView-2 (WV2) imagery, the goal of this study was to establish a remote sensing-based method for mapping ash trees undergoing various infestation stages. Based on field data collected in Southeastern Ontario, Canada, an ash health score with an interval scale ranging from 0 to 10 was established and further related to multiple spectral indices. The WV2 image was segmented using multi-band watershed and multiresolution algorithms to identify individual tree crowns, with watershed achieving higher segmentation accuracy. Ash trees were classified using the random forest classifier, resulting in a user\u2019s accuracy of 67.6% and a producer\u2019s accuracy of 71.4% when watershed segmentation was utilized. The best ash health score-spectral index model was then applied to the ash tree crowns to map the ash health for the entire area. The ash health prediction map, with an overall accuracy of 70%, suggests that remote sensing has potential to provide a semi-automated and large-scale monitoring of EAB infestation.<\/jats:p>","DOI":"10.3390\/rs8030256","type":"journal-article","created":{"date-parts":[[2016,3,17]],"date-time":"2016-03-17T11:36:02Z","timestamp":1458214562000},"page":"256","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Ash Decline Assessment in Emerald Ash Borer Infested Natural Forests Using High Spatial Resolution Images"],"prefix":"10.3390","volume":"8","author":[{"given":"Justin","family":"Murfitt","sequence":"first","affiliation":[{"name":"Department of Geography, University of Toronto Mississauga, 3359 Mississauga Rd, Mississauga, ON L5L 1C6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhong","family":"He","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Toronto Mississauga, 3359 Mississauga Rd, Mississauga, ON L5L 1C6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6655-0898","authenticated-orcid":false,"given":"Jian","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Toronto, 100 St. George Street, Toronto, ON M5S 3G3, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy","family":"Mui","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Toronto Mississauga, 3359 Mississauga Rd, Mississauga, ON L5L 1C6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"De Mille","sequence":"additional","affiliation":[{"name":"Credit Valley Conservation, Mississauga, ON L5N 6R4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,3,17]]},"reference":[{"key":"ref_1","unstructured":"Agnecy, C.F.I. (2014). RMD-13-01: Regulated Areas for Emerald Ash Borer (EAB) (Agrilus planipennis Fairmaire), Canadian Food Inspection Agency."},{"key":"ref_2","unstructured":"McManus, K.A., and Gottschalk, K.W. (2009, January 13\u201316). Ecological impacts of emerald ash borer in forests of southeast Michigan. Proceedings of the 20th U.S. Department of Agriculture Interagency Research Forum on Invasive Species, Annapolis, MD, USA."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1007\/s10886-011-9954-z","article-title":"Distinguishing defensive characteristics in the phloem of ash species resistant and susceptible to emerald ash borer","volume":"37","author":"Cipollini","year":"2011","journal-title":"J. Chem. Ecol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s10530-005-0236-y","article-title":"Characterised and projected costs of nonindigenous species in Canada","volume":"8","author":"Colautti","year":"2006","journal-title":"Biol. Invasions"},{"key":"ref_5","first-page":"118","article-title":"Emerald ash borer: Invasion of the urban forest and the threat to North America\u2019s ash resource","volume":"104","author":"Poland","year":"2006","journal-title":"J. For."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1093\/jee\/101.5.1643","article-title":"Progression of ash canopy thinning and dieback outward from the initial infestation of emerald ash borer (Coleoptera: Buprestidae) in southeastern Michigan","volume":"101","author":"Smitley","year":"2008","journal-title":"J. Econ. Entomol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1146\/annurev-ento-011613-162051","article-title":"Emerald ash borer invasion of North America: History, biology, ecology, impacts, and management","volume":"59","author":"Herms","year":"2014","journal-title":"Annu. Rev. Entomol."},{"key":"ref_8","unstructured":"Siegert, N.W., McCullough, D.G., Liebhold, A.M., and Telewski, F.W. (2010, January 26\u201327). Spread and dispersal of emerald ash borer: A dendrochronological approach. Proceedings of the Emerald Ash Borer Research and Technology Development Meeting, Pittsburgh, PA, USA."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1603\/EC09305","article-title":"Azadirachtin: An effective systemic insecticide for control of Agrilus planipennis (Coleoptera: Buprestidae)","volume":"103","author":"McKenzie","year":"2010","journal-title":"J. Econ. Entomol."},{"key":"ref_10","unstructured":"Hay, G.J., and Castilla, G. (2008). Object-Based Image Analysis, Springer."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1282","DOI":"10.1109\/LGRS.2015.2393255","article-title":"An automated method to parameterize segmentation scale by enhancing intrasegment homogeneity and intersegment heterogeneity","volume":"12","author":"Yang","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_12","unstructured":"Yang, J., He, Y., and Caspersen, J. (2014, January 13\u201318). A multi-band watershed segmentation method for individual tree crown delineation from high resolution multispectral aerial image. Proceedings of the IEEE International Geoscience and Remote Sensing System, Quebec City, QC, Canada."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.isprsjprs.2003.10.002","article-title":"Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information","volume":"58","author":"Benz","year":"2004","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.cviu.2007.08.003","article-title":"Image segmentation evaluation: A survey of unsupervised methods","volume":"110","author":"Zhang","year":"2008","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.isprsjprs.2014.04.008","article-title":"A multi-band approach to unsupervised scale parameter selection for multi-scale image segmentation","volume":"94","author":"Yang","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.isprsjprs.2014.12.015","article-title":"A discrepancy measure for segmentation evaluation from the perspective of object recognition","volume":"101","author":"Yang","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/j.rse.2010.12.017","article-title":"Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery","volume":"115","author":"Myint","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1080\/01431160110040323","article-title":"An assessment of support vector machines for land cover classification","volume":"23","author":"Huang","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.isprsjprs.2010.11.001","article-title":"Support vector machines in remote sensing: A review","volume":"66","author":"Mountrakis","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1117\/12.413892","article-title":"Support vector machines for remote sensing image classification","volume":"4170","author":"Roli","year":"2001","journal-title":"Proc. SPIE"},{"key":"ref_21","unstructured":"Duda, R.O., Hart, P.E., and Stork, D.G. (2001). Pattern Classification, John Wiley & Sons, Inc.. [2nd ed.]."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1002\/j.1537-2197.1993.tb13796.x","article-title":"Responses of leaf spectral reflectance to plant stress","volume":"80","author":"Carter","year":"1993","journal-title":"Am. J. Bot."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1080\/01431169408954109","article-title":"Ratios of leaf reflectances in narrow wavebands as indicators of plant stress","volume":"15","author":"Carter","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1104\/pp.47.4.591","article-title":"Large effects of small water deficits on chlorophyll accumulation and ribonucleic acid synthesis in etiolated leaves of jack bean (Canavalia ensiformis [L.] DC.)","volume":"47","author":"Bourque","year":"1971","journal-title":"Plant Physiol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2665","DOI":"10.1016\/j.rse.2007.12.011","article-title":"Ash decline assessment in emerald ash borer-infested regions: A test of tree-level, hyperspectral technologies","volume":"112","author":"Pontius","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zhang, K., Hu, B., Hanou, I., and Jin, L. (2012, January 22\u201327). Early detecting ash Emerald Ash Borer (EAB) infestation using Hyperspectral imagery. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352714"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4515","DOI":"10.3390\/rs6054515","article-title":"Evaluating the potential of worldview-2 data to classify tree species and different levels of ash mortality","volume":"6","author":"Waser","year":"2014","journal-title":"Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Schomaker, M.E., Zarnoch, S.J., Bechtold, W.A., Latelle, D.J., Burkman, W.G., and Cox, S.M. (2007). Crown-Condition Classification: A Guide to Data Collection and Analysis, General Technical Report SRS-102.","DOI":"10.2737\/SRS-GTR-102"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.ecolmodel.2006.03.003","article-title":"Modeling the spread of the Emerald Ash Borer","volume":"7","author":"Bendor","year":"2006","journal-title":"Ecol. Model."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1093\/forestry\/72.1.59","article-title":"Assessing forest canopies and understorey illumination: Canopy closure, canopy cover and other measures","volume":"72","author":"Jennings","year":"1999","journal-title":"Forestry"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1016\/j.agrformet.2007.11.015","article-title":"Estimation of leaf area and clumping indexes of crops with hemispherical photographs","volume":"148","author":"Demarez","year":"2008","journal-title":"Agric. For. Meteorol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1487","DOI":"10.1093\/treephys\/26.11.1487","article-title":"Assessment of oak forest condition based on leaf biochemical variables and chlorophyll fluorescence","volume":"26","author":"Rossini","year":"2006","journal-title":"Tree Physiol."},{"key":"ref_33","unstructured":"Laben, C.A., and Brower, B.V. (2000). Process for Enhancing the Spatial Resolution of Multispectral Imagery Using Pansharpening. (611875), U.S. Patent."},{"key":"ref_34","unstructured":"Li, C., Liu, L., Wang, J., Zhao, C., and Wang, R. (2004, January 20\u201324). Comparison of two methods of the fusion of remote sensing images with fidelity of spectral information. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, USA."},{"key":"ref_35","first-page":"22","article-title":"Obect-oriented image analysis and scale-space: Theory and methods and evaluating multiscale lanscape structure","volume":"34","author":"Blaschke","year":"2001","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_36","first-page":"2271","article-title":"System for Automated Geoscientific Analyses (SAGA) v. 2.1.4","volume":"8","author":"Conrad","year":"2015","journal-title":"Geosci. Model Dev. Discuss."},{"key":"ref_37","unstructured":"Definiens AG (2009). Definiens Developer 7 User Guide, Definiens AG."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0167-5877(05)80004-2","article-title":"Interpreting vegetation indices","volume":"11","author":"Jackson","year":"1991","journal-title":"Prev. Vet. Med."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2455","DOI":"10.1016\/j.biombioe.2011.02.028","article-title":"A review of remote sensing methods for biomass feedstock production","volume":"35","author":"Ahamed","year":"2011","journal-title":"Biomass Bioenergy"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/0034-4257(90)90085-Z","article-title":"Calculating the vegetation index faster","volume":"73","author":"Crippen","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"150","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"663","DOI":"10.2307\/1936256","article-title":"Derivation of leaf-area index from quality of light on the forest floor","volume":"50","author":"Jordan","year":"1969","journal-title":"Ecology"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/0034-4257(94)00114-3","article-title":"Estimating PAR absorbed by vegetation from bidirectional reflectance measurements","volume":"51","author":"Roujean","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"4715","DOI":"10.1080\/01431160600758543","article-title":"Broadband vegetation index performance evaluated for a low-cover environment","volume":"27","author":"Baugh","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_46","unstructured":"Team, R.C. (2013). R: A Language and Environmnet for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.rse.2004.03.006","article-title":"Wavelet transform applied to EO-1 hyperspectral data for forest LAI and crown closure mapping","volume":"91","author":"Pu","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Latif, Z.A., Zamri, I., and Omar, H. (2012, January 23\u201325). Determination of tree species using Worldview-2 data. Proceedings of the IEEE 8th International Colloquium on Signal Processing and its Applications, Malacca, Malaysia.","DOI":"10.1109\/CSPA.2012.6194754"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s10310-003-0045-z","article-title":"Classifying tree species in a northern mixed forest using high-resolution IKONOS data","volume":"9","author":"Katoh","year":"2004","journal-title":"J. For. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.3390\/rs4092661","article-title":"Tree species classification with random forest using very high spatial resolution 8-band WorldView-2 satellite data","volume":"4","author":"Immitzer","year":"2012","journal-title":"Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"3809","DOI":"10.1002\/hyp.9916","article-title":"A method to map riparian exotic vegetation (Salix spp.) area to inform water resource management","volume":"28","author":"Doody","year":"2014","journal-title":"Hydrol. Process."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"4825","DOI":"10.1109\/JSTARS.2015.2461136","article-title":"Performance of support vector machines and artifical neural network for mapping endangered tree species using WorldView-2 data in Dukuduku Forest, South Africa","volume":"8","author":"Omer","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2632","DOI":"10.1109\/TGRS.2012.2216272","article-title":"Tree species classification in boreal forests with hyperspectral data","volume":"51","author":"Dalponte","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1016\/j.rse.2012.06.011","article-title":"A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species","volume":"124","author":"Pu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.isprsjprs.2013.10.010","article-title":"Integrating environmental variables and WorldView-2 image data to improve the prediction and mapping of Thaumastocoris peregrinus (bronze bug) damage in plantation forests","volume":"87","author":"Oumar","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1127\/1432-8364\/2014\/0229","article-title":"Early detection of bark beetle infestation in Norway spruce (Picea abies, L.) using WorldView-2 data","volume":"2014","author":"Immitzer","year":"2014","journal-title":"Photogramm. Fernerkundung Geoinform."},{"key":"ref_57","unstructured":"Ch\u00e1vez, R.O., and Clevers, J.G.P.W. (2012). Object-Based Analysis of 8-Bands Worldview2 Imagery for Assessing Health Condition of Desert Trees, Wageningen University."},{"key":"ref_58","unstructured":"Filchev, L. (2012, January 21\u201323). An assessment of european spruce bark beetle infestation using WorldView-2 Satellite data. Proceedings of the 1st European SCGIS Conference with International Participation \u201cBest Practices: Application of GIS Technologies for Conservation of Natural and Cultural Heritage Sites\u201d, Sofia, Bulgaria."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"29","DOI":"10.2307\/1311538","article-title":"Integrated responses of plants to stress","volume":"41","author":"Chapin","year":"1991","journal-title":"Bioscience"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"53","DOI":"10.5849\/njaf.10-053","article-title":"Effects of ice storm damage on hardwood survival and growth in Ohio","volume":"29","author":"Turcotte","year":"2012","journal-title":"North. J. Appl. For."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/3\/256\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:20:52Z","timestamp":1760210452000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/3\/256"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,3,17]]},"references-count":60,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2016,3]]}},"alternative-id":["rs8030256"],"URL":"https:\/\/doi.org\/10.3390\/rs8030256","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,3,17]]}}}