{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T10:47:08Z","timestamp":1769165228203,"version":"3.49.0"},"reference-count":50,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T00:00:00Z","timestamp":1565308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006280","name":"Ministerio de Ciencia y Tecnolog\u00eda","doi-asserted-by":"publisher","award":["ESPECTRAMED (CGL2017-86161-R)"],"award-info":[{"award-number":["ESPECTRAMED (CGL2017-86161-R)"]}],"id":[{"id":"10.13039\/501100006280","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High levels of \u2018Candidatus Phytoplasma pini\u2019 have produced extensive forest mortality on Pinus halepensis Mill forests in eastern Spain. This has led to the widespread levels of forest mortality. We used archival Landsat imagery and shapes algorithm implemented in the Google Earth Engine to explore the potential of the LandTrendr algorithm and its outputs, together with field observations, to analyze and predict the health status in P. halepensis stands affected by \u2018Candidatus Phytoplasma pini\u2019 in Andalusia (south-eastern Spain). We found that the Landsat time series algorithm (LandTrendr) has captured both long- and short-duration trends and changes in spectral reflectance related to phytoplasma disturbance in the Aleppo pine forest stands investigated. The normalized burn ratio (NBR) trends were positively associated with environmental variables: Annual precipitation, mean temperature, soil depth, percent base saturation and aspect. Environmental variables were tested for their contributions to the mapping of changes in Aleppo pine cover in the study area, as an empirical modeling approach to disturbance mapping in forests of south-eastern Spain. The methodology outlined in this paper has produced valuable results that indicate new possibilities for the use in forest management of remote-sensing technologies based on spectral trajectories associated with pest-diseases defoliation. Given the likely increase in pest risks in the forests of southern Europe, accurate assessment and map of pest outbreaks on forests will become increasingly important, both for research and for practical applications in forest management.<\/jats:p>","DOI":"10.3390\/rs11161868","type":"journal-article","created":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T11:11:31Z","timestamp":1565349091000},"page":"1868","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Analysis of Site-dependent Pinus halepensis Mill. Defoliation Caused by \u2018Candidatus Phytoplasma pini\u2019 through Shape Selection in Landsat Time Series"],"prefix":"10.3390","volume":"11","author":[{"given":"Jesus","family":"Trujillo-Toro","sequence":"first","affiliation":[{"name":"Department of Forestry Engineering, Laboratory of Silviculture, Dendrochronology and Climate Change, DendrodatLab- ERSAF, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 C\u00f3rdoba, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3470-8640","authenticated-orcid":false,"given":"Rafael M.","family":"Navarro-Cerrillo","sequence":"additional","affiliation":[{"name":"Department of Forestry Engineering, Laboratory of Silviculture, Dendrochronology and Climate Change, DendrodatLab- ERSAF, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 C\u00f3rdoba, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1016\/j.foreco.2009.09.001","article-title":"A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests","volume":"259","author":"Allen","year":"2010","journal-title":"For. Ecol. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1007\/s10584-011-0372-6","article-title":"Selective drought-induced decline of pine species in southeastern Spain","volume":"113","author":"Camarero","year":"2012","journal-title":"Clim. Chang."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"956","DOI":"10.1016\/j.foreco.2013.09.050","article-title":"Contrasting vulnerability and resilience to drought-induced decline of densely planted vs. natural rear-edge Pinus nigra forests","volume":"310","author":"Camarero","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Navarro-Cerrillo, R.M., Rodriguez-Vallejo, C., Silveiro, E., Hortal, A., Palacios-Rodr\u00edguez, G., Duque-Lazo, J., and Camarero, J.J. (2018). Cumulative Drought Stress Leads to a Loss of Growth Resilience and Explains Higher Mortality in Planted than in Naturally Regenerated Pinus pinaster Stands. Forests, 9.","DOI":"10.3390\/f9060358"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Pe\u00f1a-Gallardo, M., Vicente-Serrano, S.M., Camarero, J.J., Gazol, A., S\u00e1nchez-Salguero, R., Dom\u00ednguez-Castro, F., El Kenawy, A., Beguer\u00eda-Portug\u00e9s, S., Guti\u00e9rrez, E., and De Luis, M. (2018). Drought Sensitiveness on Forest Growth in Peninsular Spain and the Balearic Islands. Forests, 9.","DOI":"10.3390\/f9090524"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1525\/bio.2010.60.8.6","article-title":"Climate Change and Bark Beetles of the Western United States and Canada: Direct and Indirect Effects","volume":"60","author":"Bentz","year":"2010","journal-title":"BioScience"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.foreco.2014.11.030","article-title":"Spatiotemporal dynamics of recent mountain pine beetle and western spruce budworm outbreaks across the Pacific Northwest Region, USA","volume":"339","author":"Meigs","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1474","DOI":"10.1073\/pnas.1010070108","article-title":"Widespread crown condition decline, food web disruption, and amplified tree mortality with increased climate change-type drought","volume":"108","author":"Carnicer","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_9","first-page":"163","article-title":"Cartograf\u00eda de defoliaci\u00f3n en los pinares de pino silvestre (Pinus sylvestris L.) y pino salgare\u00f1o (Pinus nigra Arnold.) en la Sierra de los Filabres","volume":"16","author":"Varo","year":"2007","journal-title":"Rev. Ecosistemas"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1016\/j.foreco.2009.07.034","article-title":"Potential effects of climate change on insect herbivores in European forests\u2014General aspects and the pine processionary moth as specific example","volume":"259","author":"Netherer","year":"2010","journal-title":"For. Ecol. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1099\/ijs.0.63285-0","article-title":"\u2018Candidatus Phytoplasma pini\u2019, a novel taxon from Pinus silvestris and Pinus halepensis","volume":"55","author":"Schneider","year":"2005","journal-title":"Int. J. Syst. Evol. Microbiol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1126\/science.aac6759","article-title":"Forest health and global change","volume":"349","author":"Trumbore","year":"2015","journal-title":"Science"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.rse.2013.11.006","article-title":"Mapping forest growth and decline in a temperate mixed forest using temporal trend analysis of Landsat imagery, 1987\u20132010","volume":"141","author":"Czerwinski","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"S296","DOI":"10.4039\/tce.2016.11","article-title":"Remote sensing of forest pest damage: A review and lessons learned from a Canadian perspective","volume":"148","author":"Hall","year":"2016","journal-title":"Can. Entomol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.foreco.2005.09.021","article-title":"Surveying mountain pine beetle damage of forests: A review of remote sensing opportunities","volume":"221","author":"Wulder","year":"2006","journal-title":"For. Ecol. Manag."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2431","DOI":"10.1016\/j.rse.2010.05.018","article-title":"Assessing canopy mortality during a mountain pine beetle outbreak using GeoEye-1 high spatial resolution satellite data","volume":"114","author":"Dennison","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.foreco.2015.10.042","article-title":"Forest disturbance across the conterminous United States from 1985\u20132012: The emerging dominance of forest decline","volume":"360","author":"Cohen","year":"2016","journal-title":"For. Ecol. Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"377","DOI":"10.5424\/fs\/2013223-04417","article-title":"Remote monitoring of forest insect defoliation. A review","volume":"22","author":"Silva","year":"2013","journal-title":"For. Syst."},{"key":"ref_19","first-page":"1067","article-title":"Comparison of Change-Detection Techniques for Monitoring Tropical Forest Clearing and Vegetation Regrowth in a Time Series","volume":"67","author":"Hayes","year":"2001","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","unstructured":"Key, C.H., and Benson, N.C. (2005). Landscape assessment: Remote sensing of severity, the normalized burn ratio and ground measure of severity, the composite burn index. FIREMON: Fire Effects Monitoring and Inventory System, USDA Forest Service, Rocky Mountain Res. Station."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Housman, I.W., Chastain, R.A., and Finco, M.V. (2018). An Evaluation of Forest Health Insect and Disease Survey Data and Satellite-Based Remote Sensing Forest Change Detection Methods: Case Studies in the United States. Remote Sens., 10.","DOI":"10.20944\/preprints201805.0360.v1"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3518","DOI":"10.1111\/gcb.13358","article-title":"Shape selection in Landsat time series: A tool for monitoring forest dynamics","volume":"22","author":"Moisen","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.rse.2011.06.027","article-title":"Monitoring gradual ecosystem change using Landsat time series analyses: Case studies in selected forest and rangeland ecosystems","volume":"122","author":"Vogelmann","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.rse.2012.01.010","article-title":"Opening the archive: How free data has enabled the science and monitoring promise of Landsat","volume":"122","author":"Wulder","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1890\/130066","article-title":"Bringing an ecological view of change to Landsat-based remote sensing","volume":"12","author":"Kennedy","year":"2014","journal-title":"Front. Ecol. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Dickinson, M., and Hodgetts, J. (2013). The Phytoplasmas: An Introduction. Phytoplasma: Methods and Protocols, Humana Press. Methods in Molecular Biology.","DOI":"10.1007\/978-1-62703-089-2"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2897","DOI":"10.1016\/j.rse.2010.07.008","article-title":"Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr\u2014Temporal segmentation algorithms","volume":"114","author":"Kennedy","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_28","unstructured":"Ferretti, M. (1994). Mediterranean Forest Trees a Guide for Crown Assessment, Commission of the European Communities."},{"key":"ref_29","unstructured":"QGIS Development Team (2018). QGIS Geographic Information System, Open Source Geospatial Foundation Project."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Kennedy, R., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W., Healey, S., Kennedy, R.E., Yang, Z., and Gorelick, N. (2018). Implementation of the LandTrendr Algorithm on Google Earth Engine. Remote Sens., 10.","DOI":"10.3390\/rs10050691"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2011.10.028","article-title":"Object-based cloud and cloud shadow detection in Landsat imagery","volume":"118","author":"Zhu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6481","DOI":"10.3390\/rs5126481","article-title":"Seasonal Composite Landsat TM\/ETM+ Images Using the Medoid (a Multi-Dimensional Median)","volume":"5","author":"Flood","year":"2013","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.rse.2015.12.024","article-title":"Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity","volume":"185","author":"Roy","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3263","DOI":"10.1080\/01431160903186277","article-title":"Curve fitting of time-series Landsat imagery for characterizing a mountain pine beetle infestation","volume":"31","author":"Goodwin","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","unstructured":"Gandullo, J.M., and S\u00e1nchez Palomares, O. (1994). Estaciones Ecol\u00f3gicas de Los Pinares Espa\u00f1oles, ICONA."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1007\/s40333-013-0191-x","article-title":"Mapping aboveground biomass by integrating geospatial and forest inventory data through a k-nearest neighbor strategy in North Central Mexico","volume":"6","author":"Haapanen","year":"2014","journal-title":"J. Arid Land"},{"key":"ref_37","unstructured":"R Core Team (2018). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1111\/j.1600-0587.2013.00205.x","article-title":"Where is positional uncertainty a problem for species distribution modelling?","volume":"37","author":"Naimi","year":"2014","journal-title":"Ecography"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v023.i10","article-title":"yaImpute: An R package for kNN imputation","volume":"23","author":"Crookston","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/j.rse.2007.01.005","article-title":"The k-MSN method for the prediction of species-specific stand attributes using airborne laser scanning and aerial photographs","volume":"109","author":"Maltamo","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_41","unstructured":"Hijmans, R.J., van Etten, J., Cheng, J., Mattiuzzi, M., Sumner, M., Greenberg, J.A., Lamigueiro, O.P., Bevan, A., Racine, E.B., and Shortridge, A. (2019). Package \u2018raster. R Package."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1139\/X08-171","article-title":"Responses of insect pests, pathogens, and invasive plant species to climate change in the forests of northeastern North America: What can we predict? This article is one of a selection of papers from NE Forests 2100: A Synthesis of Climate Change Impacts on Forests of the Northeastern US and Eastern Canada","volume":"39","author":"Dukes","year":"2009","journal-title":"Can. J. For. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1111\/1365-2745.12295","article-title":"To die or not to die: Early warnings of tree dieback in response to a severe drought","volume":"103","author":"Camarero","year":"2015","journal-title":"J. Ecol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Marcone, C., Franco-Lara, L., and To\u0161evski, I. (2018). Major phytoplasma diseases of forest and urban trees. Phytoplasmas Plant Pathog. Bact.-I, 287\u2013312.","DOI":"10.1007\/978-981-13-0119-3_10"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1007\/BF03356469","article-title":"\u2018Candidatus Phytoplasma pini\u2019 in pine species in Croatia","volume":"120","author":"Poljak","year":"2013","journal-title":"J. Plant Dis. Prot."},{"key":"ref_46","first-page":"49","article-title":"Remote sensing of forest insect disturbances: Current state and future directions","volume":"60","author":"Senf","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf. ITC J."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1093\/treephys\/tpr047","article-title":"Hydraulic adjustments underlying drought resistance of Pinus halepensis","volume":"31","author":"Klein","year":"2011","journal-title":"Tree Physiol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.agrformet.2010.02.002","article-title":"Aridification determines changes in forest growth in Pinus halepensis forests under semiarid Mediterranean climate conditions","volume":"150","author":"Lasanta","year":"2010","journal-title":"Agric. For. Meteorol."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Bjorkman, C., and Niemela, P. (2015). Climate Change and Insect Pests, CABI.","DOI":"10.1079\/9781780643786.0000"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1146\/annurev.ento.51.110104.151039","article-title":"Insect vectors of phytoplasmas","volume":"51","author":"Weintraub","year":"2006","journal-title":"Annu. Rev. Entomol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/16\/1868\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:09:59Z","timestamp":1760188199000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/16\/1868"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,9]]},"references-count":50,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["rs11161868"],"URL":"https:\/\/doi.org\/10.3390\/rs11161868","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,9]]}}}