Monitoring the invasion of an exotic tree (Ligustrum lucidum) from 1983 to 2006 with Landsat TM/ETM+ satellite data and Support Vector Machines in Córdoba, Argentina
نویسندگان
چکیده
a Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, 1630 Linden Drive, Madison, WI 53706, United States b Earth System Analysis, Potsdam Institute for Climate Impact Research (PIK), P.O. Box 60 12 03, Telegraphenberg A62, D-14412 Potsdam, Germany c Instituto Multidisciplinario de Biología Vegetal (IMBIV-CONICET), and Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Av. Vélez Sarsfield 299, C.C. 495, 5000 Córdoba, Argentina d USDA-Forest Service Northern Research Station, 1033 University Place, Suite 360, Evanston, IL 60201, United States e USDA-Forest Service Northern Research Station, 180 Canfield St, Morgantown, WV 26505, United States f Department of Statistics, University of Wisconsin, Madison, 1300 University Avenue, Madison, WI 53706, United States g Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
منابع مشابه
Monitoring the invasion of an exotic tree (<i>Ligustrum lucidum</i>) from 1983 to 2006 with Landsat TM/ETM + satellite data and Support Vector Machines in Córdoba, Argentina
متن کامل
Monitoring the invasion of an exotic tree (Ligustrum lucidum) from 1983 to 2006 withLandsat TM/ETM + satellite data and Support Vector Machines in CÃ3rdoba, Argentina
a r t i c l e i n f o Keywords: Exotic tree invasions Non-native invasive species Ligustrum lucidum Change detection Support Vector Machines classification Urban expansion Landsat Thematic Mapper Argentina Sierras Chicas Córdoba In central Argentina, the Chinese tree glossy privet (Ligustrum lucidum) is an aggressive invasive species replacing native forests, forming dense stands, and is thus a...
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متن کاملبارزسازی فرایند رسوب‌گذاری در سامانه‌های پخش سیلاب با استفاده از داده‌های تصاویر ماهواره‌ای LANDSAT، سنجنده‌های TM و ETM+
Of the applications of remote sensing and satellite images in natural resources is distinguishing and detection of changes in land surface. The image classification using Maximum Likelihood (MLC) is one the prevalent method which is used in a study of the application of TM and ETM+ satellite images to detect sediment deposition on an implemented floodwater spreading scheme. In order to implemen...
متن کاملبارزسازی فرایند رسوب‌گذاری در سامانه‌های پخش سیلاب با استفاده از داده‌های تصاویر ماهواره‌ای LANDSAT، سنجنده‌های TM و ETM+
Of the applications of remote sensing and satellite images in natural resources is distinguishing and detection of changes in land surface. The image classification using Maximum Likelihood (MLC) is one the prevalent method which is used in a study of the application of TM and ETM+ satellite images to detect sediment deposition on an implemented floodwater spreading scheme. In order to implemen...
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