209 research outputs found

    Improvement of Remote Sensing-Based Assessment of Defoliation of Pinus spp. Caused by Thaumetopoea pityocampa Denis and SchiffermĂŒller and Related Environmental Drivers in Southeastern Spain

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    This study used Landsat temporal series to describe defoliation levels due to the Pine Processionary Moth (PPM) in Pinus forests of southeastern Andalusia (Spain), utilizing Google Earth Engine. A combination of remotely sensed data and field survey data was used to detect the defoliation levels of different Pinus spp. and the main environmental drivers of the defoliation due to the PPM. Four vegetation indexes were also calculated for remote sensing defoliation assessment, both inside the stand and in a 60-m buffer area. In the area of study, all Pinus species are affected by defoliation due to the PPM, with a cyclic behavior that has been increasing in frequency in recent years. Defoliation levels were practically equal for all species, with a high increase in defoliation levels 2 and 3 since 2014. The Moisture Stress Index (MSI) and Normalized Difference Infrared Index (NDII) exhibited similar overall (p < 0.001) accuracy in the assessment of defoliation due to the PPM. The synchronization of NDII-defoliation data had a similar pattern for all together and individual Pinus species, showing the ability of this index to adjust the model parameters based on the characteristics of specific defoliation levels. Using Landsat-based NDII-defoliation maps and interpolated environmental data, we have shown that the PPM defoliation in southeastern Spain is driven by the minimum temperature in February and the precipitation in June, March, September, and October. Therefore, the NDII-defoliation assessment seems to be a general index that can be applied to forests in other areas. The trends of NDII-defoliation related to environmental variables showed the importance of summer drought stress in the expansion of the PPM on Mediterranean Pinus species. Our results confirm the potential of Landsat time-series data in the assessment of PPM defoliation and the spatiotemporal patterns of the PPM; hence, these data are a powerful tool that can be used to develop a fully operational system for the monitoring of insect damage

    Climate-Triggered Drought as Causes for Different Degradation Types of Natural Forests: A Multitemporal Remote Sensing Analysis in NE Iran

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    Climate-triggered forest disturbances are increasing either by drought or by other climate extremes. Droughts can change the structure and function of forests in long-term or cause large-scale disturbances such as tree mortality, forest fires and insect outbreaks in short-term. Traditional approaches such as dendroclimatological surveys could retrieve the long-term responses of forest trees to drought conditions; however, they are restricted to individual trees or local forest stands. Therefore, multitemporal satellite-based approaches are progressing for holistic assessment of climate-induced forest responses from regional to global scales. However, little information exists on the efficiency of satellite data for analyzing the effects of droughts in different forest biomes and further studies on the analysis of approaches and large-scale disturbances of droughts are required. This research was accomplished for assessing satellite-derived physiological responses of the Caspian Hyrcanian broadleaves forests to climate-triggered droughts from regional to large scales in northeast Iran. The 16-day physiological anomalies of rangelands and forests were analysed using MODIS-derived indices concerning water content deficit and greenness loss, and their variations were spatially assessed with monthly and inter-seasonal precipitation anomalies from 2000 to 2016. Specifically, dimensions of forest droughts were evaluated in relations with the dimensions of meteorological and hydrological droughts. Large-scale effects of droughts were explored in terms of tree mortality, insect outbreaks, and forest fires using field observations, multitemporal Landsat and TerraClimate data. Various approaches were evaluated to explore forest responses to climate hazards such as traditional regression models, spatial autocorrelations, spatial regression models, and panel data models. Key findings revealed that rangelands’ anomalies did show positive responses to monthly and inter-seasonal precipitation anomalies. However, forests’ droughts were highly associated with increases in temperatures and evapotranspiration and were slightly associated with the decreases in precipitation and surface water level. The hazard intensity of droughts has affected the water content of forests higher than their greenness properties. The stages of moderate to extreme dieback of trees were significantly associated with the hazard intensity of the deficit of forests’ water content. However, the stage of severe defoliation was only associated with the hazard intensity of forests’ greenness loss. Climate hazards significantly triggered insect outbreaks and forest fires. Although maximum temperatures, precipitation deficit, availability of soil moisture and forest fires of the previous year could significantly trigger insect outbreaks, the maximum temperatures were the only significant triggers of forest fires from 2010‒2017. In addition to climate factors, environmental and anthropogenic factors could control fire severity during a dry season. The overall evaluation indicated the evidence of spatial associations between satellite-derived forest disturbances and climate hazards. Future studies are required to apply the approaches that could handle big-data, use the satellite data that have finer wavelengths for large-scale mapping of forest disturbances, and discriminate climate-induced forest disturbances from those that induced by other biotic and abiotic agents.Klimagbedingte Waldstörungen nehmen entweder durch DĂŒrre oder durch andere Klimaextreme zu. DĂŒrren können langfristig die Struktur und Funktion der WĂ€lder verĂ€ndern oder kurzfristig große Störungen wie Baumsterben, WaldbrĂ€nde und InsektenausbrĂŒche verursachen. Traditionelle AnsĂ€tze wie dendroklimatologische Untersuchungen könnten die langfristigen Reaktionen von WaldbĂ€umen auf DĂŒrrebedingungen aufzeigen, sie sind aber auf einzelne BĂ€ume oder lokale WaldbestĂ€nde beschrĂ€nkt. Daher werden multitemporale satellitengestĂŒtzte AnsĂ€tze zur ganzheitlichen Bewertung von klimabedingten Waldreaktionen auf regionaler bis globaler Ebene weiterentwickelt. Es gibt jedoch nur wenige Informationen ĂŒber die Effizienz von Satellitendaten zur Analyse der Auswirkungen von DĂŒrren in verschiedenen Waldbiotopen. Daher sind weitere Studien zur Analyse von AnsĂ€tzen und großrĂ€umigen Störungen von DĂŒrren erforderlich. Diese Forschung wurde durchgefĂŒhrt, um die aus Satellitendaten gewonnenen physiologischen Reaktionen der im Nordosten Irans gelegenen kaspischen hyrkanischen LaubwĂ€lder auf klimabedingte DĂŒrren auf lokaler und regionaler Ebene zu bewerten. Auf der Grundlage der aus MODIS-Daten abgeleiteten Indizes wurden die 16-tĂ€gigen physiologischen Anomalien von Weideland und WĂ€ldern in Bezug auf Wassergehaltsdefizit und GrĂŒnverlust analysiert und ihre Variationen rĂ€umlich mit monatlichen und intersaisonalen Niederschlagsanomalien von 2000 bis 2016 bewertet. Insbesondere wurden die Dimensionen der WalddĂŒrre in Verbindung mit den Dimensionen der meteorologischen und hydrologischen DĂŒrre bewertet. GroßrĂ€umige Auswirkungen von DĂŒrren wurden in Bezug auf Baumsterblichkeit, InsektenausbrĂŒche und WaldbrĂ€nde mit Hilfe von Feldbeobachtungen, multitemporalen Landsat- und TerraClimate Daten untersucht. Verschiedene AnsĂ€tze wurden ausgewertet, um Waldreaktionen auf Klimagefahren wie traditionelle Regressionsmodelle, rĂ€umliche Autokorrelationen, rĂ€umliche Regressionsmodelle und Paneldatenmodelle zu untersuchen. Die wichtigsten Ergebnisse zeigten, dass die Anomalien von Weideland positive Reaktionen auf monatliche und intersaisonale Niederschlagsanomalien aufweisen. Die DĂŒrren in den WĂ€ldern waren jedoch in hohem Maße mit Temperaturerhöhungen und Evapotranspiration verbunden und standen in geringem Zusammenhang mit dem RĂŒckgang von NiederschlĂ€gen und des OberflĂ€chenwasserspiegels. Die GefĂ€hrdungsintensitĂ€t von DĂŒrren hat den Wassergehalt von WĂ€ldern stĂ€rker beeinflusst als die Eigenschaften ihres BlattgrĂŒns. Die Stufen mittlerer bis extremer Baumsterblichkeit waren signifikant mit der GefĂ€hrdungsintensitĂ€t des Defizits des Wassergehalts der WĂ€lder verbunden. Das Ausmaß der starken Entlaubung hing jedoch nur mit der GefĂ€hrdungsintensitĂ€t des GrĂŒnverlustes der WĂ€lder zusammen. Die Klimagefahren haben zu deutlichen InsektenausbrĂŒchen und WaldbrĂ€nden gefĂŒhrt. Obwohl Maximaltemperaturen, Niederschlagsdefizite, fehlende Bodenfeuchte und WaldbrĂ€nde des Vorjahres deutlich InsektenausbrĂŒche auslösen konnten, waren die Maximaltemperaturen die einzigen signifikanten Auslöser von WaldbrĂ€nden von 2010 bis 2017. Neben den Klimafaktoren können auch umweltbedingte und anthropogene Faktoren den Schweregrad eines Brandes wĂ€hrend einer Trockenzeit beeinflussen. Die Gesamtbewertung zeigt Hinweise auf rĂ€umliche ZusammenhĂ€nge zwischen aus Satellitendaten abgeleiteten Waldstörungen und Klimagefahren. Weitere Untersuchungen sind erforderlich, um AnsĂ€tze anzuwenden, die mit großen Datenmengen umgehen können, die Satellitendaten in einer hohen spektralen Auflösung fĂŒr die großmaßstĂ€bige Kartierung von Waldstörungen verwenden und die klimabedingte Waldstörungen von denen zu unterscheiden, die durch andere biotische und abiotische Faktoren verursacht werden

    Analysis of Site-dependent Pinus halepensis Mill. Defoliation Caused by ‘Candidatus Phytoplasma pini’ through Shape Selection in Landsat Time Series

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    High levels of ‘Candidatus Phytoplasma pini’ 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 ‘Candidatus Phytoplasma pini’ 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

    Center for Research on Sustainable Forests 2017 Annual Report

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    Ongoing development within the CRSF to be the region’s research data portal and geospatial observatory for forests of the Northeastern US. In addition to updating the CRSF home website, we continue to support three online tools for forest resources professionals and the public: Northeast Forest Information System (NEFIS) – an online, opensource, web portal for applied forestry information (http://www.nefismembers.org). More than 1,000 documents were uploaded over the year on a wide range of topics, user numbers have doubled, and monthly page views have reached nearly 5,000. Maine Forest Spatial Tool – displays a wide variety of geospatial data on forest resources across the State of Maine for both forest resource professionals and the public (http://mfst.acg.maine.edu). Maine Forest Dashboard – The Dashboard was launched in Spring 2017 and can be accessed at http://www.maineforestdashboard.com. The site provides customizable forest statistics and changes using long-term data from the Maine Forest Service and has had nearly 100 page views since its release in early May. CRSF scientists continue to provide a strong return for every dollar provided by the Maine Economic Improvement Fund (MEIF) to support CRSF research. In the past year, there has been over 21inreturnforevery21 in return for every 1 invested in

    Center for Research on Sustainable Forests 2018 Annual Report

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    The Center for Research on Sustainable Forests (CRSF) was founded in 2006 to build on a rich history of leading forest research and to enhance our understanding of Maine’s forest resources in an increasingly complex world. CRSF brings together the natural and social sciences with an appreciation for the importance of the relationship between people and our ecosystems. We conduct research and inform stakeholders about how to balance the wise-use of our resources while conserving our natural world for future generations. Our mission is to conduct and promote leading interdisciplinary research on issues affecting the management and sustainability of northern forest ecosystems and Maine’s forest-based economy

    Remote Monitoring of Forest Insect Defoliation -A Review-

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    Center for Research on Sustainable Forests 2021 Annual Report

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    The Center for Research on Sustainable Forests (CRSF) and Cooperative Forestry Research Unit (CFRU) continued to move forward on multiple fronts with a particularly productive and rewarding FY18-19. This included leadership on several key new initiatives such as the Forest Climate Change Initiative (FCCI), Intelligent GeoSolutions (IGS), and a funded National Science Foundation (NSF) Track 2 EPSCoR grant (INSPIRES). This is in addition to ongoing leadership and support for important CRSF programs such as NSF’s Center for Advanced Forestry Systems (CAFS), the Northeastern Research Cooperative (NSRC), and FOR/Maine. In short, CRSF is on a bold upward trajectory that highlights its relevance and solid leadership with a rather bright future

    Center for Research on Sustainable Forests 2019 Annual Report

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    The Center for Research on Sustainable Forests (CRSF) and Cooperative Forestry Research Unit (CFRU) continued to move forward on multiple fronts with a particularly productive and rewarding FY18-19. This included leadership on several key new initiatives such as the Forest Climate Change Initiative (FCCI), Intelligent GeoSolutions (IGS), and a funded National Science Foundation (NSF) Track 2 EPSCoR grant (INSPIRES). This is in addition to ongoing leadership and support for important CRSF programs such as NSF’s Center for Advanced Forestry Systems (CAFS), the Northeastern Research Cooperative (NSRC), and FOR/Maine. In short, CRSF is on a bold upward trajectory that highlights its relevance and solid leadership with a rather bright future
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