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Forest-type classification is a very complex and difficult subject. The complexity increases with urban and peri-urban forests because of the variety of features that exist in remote sensing images. The success of forest management that includes forest preservation depends strongly on the accuracy of forest-type classification. Several classification methods are used to map urban and peri-urban forests and to identify healthy and non-healthy ones. Some of these methods have shown success in the classification of forests where others failed. The successful methods used specific remote sensing data technology, such as hyper-spectral and very high spatial resolution (VHR) images. However, both VHR and hyper-spectral sensors are very expensive, and hyper-spectral sensors are not widely available on satellite platforms, unlike multi-spectral sensors. Moreover, aerial images are limited in use, very expensive, and hard to arrange and manage. To solve the aforementioned problems, an advanced method, self-organizing–deep learning (SO-UNet), was created to classify forests in the urban and peri-urban environment using multi-spectral, multi-temporal, and medium spatial resolution Sentinel-2 images. SO-UNet is a combination of two different machine learning technologies: artificial neural network unsupervised self-organizing maps and deep learning UNet. Many experiments have been conducted, and the results showed that SO-UNet overwhelms UNet significantly. The experiments encompassed different settings for the parameters that control the algorithms.
Mohamad Awad; Marco Lauteri. Self-Organizing Deep Learning (SO-UNet)—A Novel Framework to Classify Urban and Peri-Urban Forests. Sustainability 2021, 13, 5548 .
AMA StyleMohamad Awad, Marco Lauteri. Self-Organizing Deep Learning (SO-UNet)—A Novel Framework to Classify Urban and Peri-Urban Forests. Sustainability. 2021; 13 (10):5548.
Chicago/Turabian StyleMohamad Awad; Marco Lauteri. 2021. "Self-Organizing Deep Learning (SO-UNet)—A Novel Framework to Classify Urban and Peri-Urban Forests." Sustainability 13, no. 10: 5548.
In order to invade new ecosystems, invasive alien plants need to cope with different microbial communities. Whilst the ability to avoid antagonists is well recognized, the opportunity to establish mutualistic associations is less known, even in widespread invasive species such as Ailanthus altissima (Mill.) Swingle. We sought to evaluate whether the beneficial effects of arbuscular mycorrhizal fungi (AMF) on Ailanthus seedlings are maintained over time, under prolonged pot limitation. We compared three-month-, three-year- and four-year-old mycorrhizal seedlings grown in natural forest soil (NT) with seedlings grown in sterilized (ST) and non-mycorrhizal (NM) soils, in pots of 3.4 L (22 × 15 cm). Growth parameters and leaf traits were assessed, including carbon (δ13C) and nitrogen (δ15N) stable isotope compositions. NT seedlings showed relatively higher vigor in the early stage but, subsequently, the benefits provided by AMF were lost. Interestingly, mycorrhizal seedlings consistently showed about 2‰ δ13C enrichment, relatively to the other treatments. Negative linear relationships between leaf δ13C and N content were found. Higher photosynthesis rates and WUE are the likely causes of the early enhanced growth in mycorrhizal seedlings. The symbiotic relationship between AMF and Ailanthus could be driven by resource availability. Greater insights into such aspects could provide an improved perspective on the ecological limits of Ailanthus.
Emilio Badalamenti; Marco Ciolfi; Marco Lauteri; Paola Quatrini; Tommaso La Mantia. Effects of Arbuscular Mycorrhizal Fungi on the Vegetative Vigor of Ailanthus altissima (Mill.) Swingle Seedlings under Sustained Pot Limitation. Forests 2018, 9, 409 .
AMA StyleEmilio Badalamenti, Marco Ciolfi, Marco Lauteri, Paola Quatrini, Tommaso La Mantia. Effects of Arbuscular Mycorrhizal Fungi on the Vegetative Vigor of Ailanthus altissima (Mill.) Swingle Seedlings under Sustained Pot Limitation. Forests. 2018; 9 (7):409.
Chicago/Turabian StyleEmilio Badalamenti; Marco Ciolfi; Marco Lauteri; Paola Quatrini; Tommaso La Mantia. 2018. "Effects of Arbuscular Mycorrhizal Fungi on the Vegetative Vigor of Ailanthus altissima (Mill.) Swingle Seedlings under Sustained Pot Limitation." Forests 9, no. 7: 409.
In 2006, Kerr entitled an editorial on Science “No doubt about it, the world is warming” (Kerr in Science 312:825, 2006). Particularly in the Northern Hemisphere, at middle latitudes, the mean air temperature is expected to increase by 1 to 3 ℃ while rainfall should decrease by 10–20% (e.g., IPCC, scenario A2, 2001). Ten years later, Guiot and Cramer (Science 354(6311):465–468, 2016) launched a warning for the Mediterranean environments.
Marco Lauteri; Maria Cristina Monteverdi. Understanding the Resilience of Mediterranean Ecosystems to Global Changes: An Overview on Applications of Stable Isotopes of Light Elements in Ecophysiological Studies. Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems 2017, 1423 -1424.
AMA StyleMarco Lauteri, Maria Cristina Monteverdi. Understanding the Resilience of Mediterranean Ecosystems to Global Changes: An Overview on Applications of Stable Isotopes of Light Elements in Ecophysiological Studies. Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems. 2017; ():1423-1424.
Chicago/Turabian StyleMarco Lauteri; Maria Cristina Monteverdi. 2017. "Understanding the Resilience of Mediterranean Ecosystems to Global Changes: An Overview on Applications of Stable Isotopes of Light Elements in Ecophysiological Studies." Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems , no. : 1423-1424.
The authentication and verification of the geographical origin of food commodities are important topics in the food sector. This study shows the spatial variability in δ13C and δ18O of 387 samples of Italian extra-virgin olive oil (EVOO) collected from 2009 to 2011. EVOOs’ δ13C and δ18O values were related to GIS (Geographic Information System) layers of source water δ18O and climate data (mean monthly temperature and precipitation, altitude, xerothermic index) to evaluate the impact of the most significant large-scale drivers for the isotopic composition of Italian EVOOs. A geospatial model of δ18O and δ13C was developed for the authentication and verification of the geographical origin of EVOOs. The geospatial model identified EVOOs from four distinct areas: north, south-central Tyrrhenian, central Adriatic and islands, highlighting the zonation of the expected isotopic signatures. This geospatial approach can be used to define a protocol for analyzing the isotopic composition of EVOOs in order to certify their origin and prevent food fraud. Limits and perspectives of the model are discussed.
Francesca Chiocchini; Silvia Portarena; Marco Ciolfi; Enrico Brugnoli; Marco Lauteri. Isoscapes of carbon and oxygen stable isotope compositions in tracing authenticity and geographical origin of Italian extra-virgin olive oils. Food Chemistry 2016, 202, 291 -301.
AMA StyleFrancesca Chiocchini, Silvia Portarena, Marco Ciolfi, Enrico Brugnoli, Marco Lauteri. Isoscapes of carbon and oxygen stable isotope compositions in tracing authenticity and geographical origin of Italian extra-virgin olive oils. Food Chemistry. 2016; 202 ():291-301.
Chicago/Turabian StyleFrancesca Chiocchini; Silvia Portarena; Marco Ciolfi; Enrico Brugnoli; Marco Lauteri. 2016. "Isoscapes of carbon and oxygen stable isotope compositions in tracing authenticity and geographical origin of Italian extra-virgin olive oils." Food Chemistry 202, no. : 291-301.