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  1. Article ; Online: Combined use of urban Atlas and Corine land cover datasets for the implementation of an ecological network using graph theory within a multi-species approach

    Lumia, Giovanni / Praticò, Salvatore / Di Fazio, Salvatore / Cushman, Samuel / Modica, Giuseppe

    Ecological Indicators. 2023 Apr., v. 148 p.110150-

    2023  

    Abstract: Ecological sustainability has recently risen to prominence in scientific research and management applications. Approaches to measuring ecological connectivity and their application to optimize ecological network (EN) design are powerful tools against ... ...

    Abstract Ecological sustainability has recently risen to prominence in scientific research and management applications. Approaches to measuring ecological connectivity and their application to optimize ecological network (EN) design are powerful tools against landscape fragmentation and biodiversity loss. We focused on building an EN by identifying the most sensitive areas for ecological connectivity within the Reggio Calabria (Italy) metropolitan area. We also proposed a defragmentation scenario to improve the obtained EN. The CORINE Land Cover and the Urban Atlas 2018 were used to obtain a fine-scale representation of the study area. Ten terrestrial mammal species were used to model connectivity following a multi-species approach. Dispersal distance, patch size, and resistance to species movement were used to identify patches and corridors. Vegetational fractional coverage based on three years time series of Sentinel-2 red-edge normalized difference vegetation index was used to discriminate areas with higher naturalness. We used graph theory and connectivity metrics to test the EN's robustness and identify locations for restoration in a defragmentation scenario. The obtained EN, formed by three separate components, was composed of 724 arcs and 300 nodes with an average patch area of 27.04 ha. After the defragmentation hypothesis, the EN, formed by only one component, was composed of 771 arcs and 328 nodes with an average patch area of 26.82 ha. It was possible to analyze an EN's connectivity and evaluate the impact of a scenario intended to enhance multi-species connectivity. By comparing several connectivity metrics, we highlighted the potential of land interventions as a planning tool to enhance future ecological sustainability and biodiversity conservation.
    Keywords biodiversity ; biodiversity conservation ; data collection ; environmental sustainability ; habitat fragmentation ; land cover ; mammals ; mathematical theory ; metropolitan areas ; normalized difference vegetation index ; time series analysis ; Italy ; Remote sensing (RS) ; Vegetation Fractional Coverage (VFC) ; Sentinel-2 ; Google Earth Engine (GEE) ; Graphab ; Landscape connectivity
    Language English
    Dates of publication 2023-04
    Publishing place Elsevier Ltd
    Document type Article ; Online
    Note Use and reproduction
    ZDB-ID 2036774-0
    ISSN 1872-7034 ; 1470-160X
    ISSN (online) 1872-7034
    ISSN 1470-160X
    DOI 10.1016/j.ecolind.2023.110150
    Database NAL-Catalogue (AGRICOLA)

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    In stock of ZB MED Bonn / Germany

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  2. Article ; Online: Multispectral Vegetation Indices and Machine Learning Approaches for Durum Wheat (Triticum durum Desf.) Yield Prediction across Different Varieties

    Badagliacca, Giuseppe / Messina, Gaetano / Praticò, Salvatore / Lo Presti, Emilio / Preiti, Giovanni / Monti, Michele / Modica, Giuseppe

    AgriEngineering. 2023 Nov. 02, v. 5, no. 4 p.2032-2048

    2023  

    Abstract: Durum wheat (Triticum durum Desf.) is one of the most widely cultivated cereal species in the Mediterranean basin, supporting pasta, bread and other typical food productions. Considering its importance for the nutrition of a large population and ... ...

    Abstract Durum wheat (Triticum durum Desf.) is one of the most widely cultivated cereal species in the Mediterranean basin, supporting pasta, bread and other typical food productions. Considering its importance for the nutrition of a large population and production of high economic value, its supply is of strategic significance. Therefore, an early and accurate crop yield estimation may be fundamental to planning the purchase, storage, and sale of this commodity on a large scale. Multispectral (MS) remote sensing (RS) of crops using unpiloted aerial vehicles (UAVs) is a powerful tool to assess crop status and productivity with a high spatial–temporal resolution and accuracy level. The object of this study was to monitor the behaviour of thirty different durum wheat varieties commonly cultivated in Italy, taking into account their spectral response to different vegetation indices (VIs) and assessing the reliability of this information to estimate their yields by Pearson’s correlation and different machine learning (ML) approaches. VIs allowed us to separate the tested wheat varieties into different groups, especially when surveyed in April. Pearson’s correlations between VIs and grain yield were good (R² > 0.7) for a third of the varieties tested; the VIs that best correlated with grain yield were CVI, GNDVI, MTVI, MTVI2, NDRE, and SR RE. Implementing ML approaches with VIs data highlighted higher performance than Pearson’s correlations, with the best results observed by random forest (RF) and support vector machine (SVM) models.
    Keywords Triticum turgidum subsp. durum ; breads ; durum wheat ; economic valuation ; grain yield ; nutrition ; pasta ; support vector machines ; vegetation ; yield forecasting ; Italy ; Mediterranean region
    Language English
    Dates of publication 2023-1102
    Size p. 2032-2048.
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article ; Online
    ISSN 2624-7402
    DOI 10.3390/agriengineering5040125
    Database NAL-Catalogue (AGRICOLA)

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  3. Article: Unveiling the complex canopy spatial structure of a Mediterranean old-growth beech (Fagus sylvatica L.) forest from UAV observations

    Solano, Francesco / Modica, Giuseppe / Praticò, Salvatore / Box, Olivia F. / Piovesan, Gianluca

    Ecological indicators. 2022 Mar. 25,

    2022  

    Abstract: In front of climate change scenarios and global loss of biodiversity, it is essential to monitor the structure of old-growth forests to study ecosystem status and dynamics to inform future conservation and restoration programmes. We propose an Unmanned ... ...

    Abstract In front of climate change scenarios and global loss of biodiversity, it is essential to monitor the structure of old-growth forests to study ecosystem status and dynamics to inform future conservation and restoration programmes. We propose an Unmanned Aerial Vehicle (UAV)-based framework to monitor fine-grained forest top canopy structure in a primary old-growth beech (Fagus sylvatica L.) forest in Pollino National Park, Italy, which belongs to the UNESCO World Heritage (UNESCO WH) serial site “Ancient and Primeval beech forests of the Carpathians and other regions of Europe”. Canopy profile, gap properties and their spatial distribution patterns were analysed using the canopy height model (CHM) derived from UAV surveys. Very high-resolution orthomosaic images coupled with direct field measurement data were used to assess gap detection accuracy and CHM validation. Forest canopy properties along with the vertical layering of the canopy were further explored using second-order statistics. The reconstructed canopy profile revealed a bimodal top height frequency distribution. The upper canopy layer (h>14 m) was the most represented canopy height, with the remaining 50% split between the medium and lowest layer; 551 gaps were identified within 11.5 ha. Gap size varied between 2 m² and 353 m², and 19 m²was the mean gap size; the gap size-frequency relationship reflected a power-law probability distribution. About 97 % of the gaps were < 100 m² in size, showing a significant tendency to cluster. Most gaps were located in the upper and medium canopy layers; however, the highest relative gap area was found in the lowest layer. These results confirmed the high natural integrity of the ecosystem processes that distinguish the old-growth beech stands in respect to managed woodlands. Our findings demonstrate that the low-cost UAV-DAP (Digital Aerial Photogrammetry) workflow has the potential to generate realistic old-growth forest canopy attributes at a very fine scale. The proposed protocol can be adopted for monitoring the structural dynamics of high-value natural forest ecosystems as in the case of UNESCO WH sites or other old-growth stands. This approach is also helpful for mapping and deriving spatially explicit canopy structure information over confined forest areas and determining where conservation actions should be directed to preserve or restore natural ecosystem function.
    Keywords Fagus sylvatica ; United Nations Educational, Scientific and Cultural Organization ; aerial photogrammetry ; biodiversity ; canopy height ; climate change ; ecological function ; forest canopy ; frequency distribution ; models ; national parks ; old-growth forests ; probability distribution ; protocols ; unmanned aerial vehicles ; Italy
    Language English
    Dates of publication 2022-0325
    Publishing place Elsevier Ltd
    Document type Article
    Note Pre-press version
    ZDB-ID 2036774-0
    ISSN 1872-7034 ; 1470-160X
    ISSN (online) 1872-7034
    ISSN 1470-160X
    DOI 10.1016/j.ecolind.2022.108807
    Database NAL-Catalogue (AGRICOLA)

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    In stock of ZB MED Bonn / Germany

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  4. Article: Machine Learning Classification of Mediterranean Forest Habitats in Google Earth Engine Based on Seasonal Sentinel-2 Time-Series and Input Image Composition Optimisation

    Praticò, Salvatore / Solano, Francesco / Di Fazio, Salvatore / Modica, Giuseppe

    Remote Sensing. 2021 Feb. 07, v. 13, no. 4

    2021  

    Abstract: The sustainable management of natural heritage is presently considered a global strategic issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) techniques have been primarily used to map, analyse, and monitor ... ...

    Abstract The sustainable management of natural heritage is presently considered a global strategic issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) techniques have been primarily used to map, analyse, and monitor natural resources for conservation purposes. The need to adopt multi-scale and multi-temporal approaches to detect different phenological aspects of different vegetation types and species has also emerged. The time-series composite image approach allows for capturing much of the spectral variability, but presents some criticalities (e.g., time-consuming research, downloading data, and the required storage space). To overcome these issues, the Google Earth engine (GEE) has been proposed, a free cloud-based computational platform that allows users to access and process remotely sensed data at petabyte scales. The application was tested in a natural protected area in Calabria (South Italy), which is particularly representative of the Mediterranean mountain forest environment. In the research, random forest (RF), support vector machine (SVM), and classification and regression tree (CART) algorithms were used to perform supervised pixel-based classification based on the use of Sentinel-2 images. A process to select the best input image (seasonal composition strategies, statistical operators, band composition, and derived vegetation indices (VIs) information) for classification was implemented. A set of accuracy indicators, including overall accuracy (OA) and multi-class F-score (Fₘ), were computed to assess the results of the different classifications. GEE proved to be a reliable and powerful tool for the classification process. The best results (OA = 0.88 and Fₘ = 0.88) were achieved using RF with the summer image composite, adding three VIs (NDVI, EVI, and NBR) to the Sentinel-2 bands. SVM and RF produced OAs of 0.83 and 0.80, respectively.
    Keywords Internet ; computer software ; conservation areas ; forests ; phenology ; regression analysis ; remote sensing ; summer ; support vector machines ; time series analysis ; Italy
    Language English
    Dates of publication 2021-0207
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    Note NAL-AP-2-clean
    ZDB-ID 2513863-7
    ISSN 2072-4292
    ISSN 2072-4292
    DOI 10.3390/rs13040586
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  5. Article: Characterizing historical transformation trajectories of the forest landscape in Rome's metropolitan area (Italy) for effective planning of sustainability goals

    Solano, Francesco / Praticò, Salvatore / Piovesan, Gianluca / Chiarucci, Alessandro / Argentieri, Alessio / Modica, Giuseppe

    Land degradation & development. 2021 Oct., v. 32, no. 16

    2021  

    Abstract: With the aim at developing a landscape dynamics framework for environmental planning and management and testing the effectiveness of protected areas in achieving the 2030 Agenda of the United Nations sustainability goals, we characterized the historical ... ...

    Abstract With the aim at developing a landscape dynamics framework for environmental planning and management and testing the effectiveness of protected areas in achieving the 2030 Agenda of the United Nations sustainability goals, we characterized the historical transformation trajectories of forest area changes from 1936 to 2010 in the Metropolitan City of Rome Capital (Italy). Remote sensing‐based products coupled with landscape pattern metrics and fragmentation analysis have been implemented, comparing different historical forest maps. The results show a remarkable forest area gain – from 17.6% to 25.5% – thanks to 68,299 ha of recently established forest. Statistical descriptors showed that the highest relative gain occurred in mountain zones, confirming a wide European forest recovery pattern in marginal areas from past deforestation and overexploitation. Deforestation mainly occurred in the flat and hilly areas where almost 26,000 ha of forests were lost since 1936. In summary, two main forest landscape dynamics were reconstructed: (I) the increase of forest cover fragmentation in the lowland areas; and (II) the rise in the forest area in the interior sectors of the mountain landscape, mainly within protected areas. Restoring the forest ecosystem's bioecological integrity has been highlighted as an urgent action for biodiversity conservation and carbon mitigation. In lowland areas, the study revealed the urgent need to establish new protected areas and rewilding spaces as landscape metrics are relatively below the sustainability targets for healthy forest ecosystems. The proposed framework can be used for testing the effectiveness of environmental planning and management in other forest landscapes to achieve the Agenda 2030 goals.
    Keywords biodiversity conservation ; capital ; carbon ; deforestation ; forest ecosystems ; forests ; land degradation ; landscapes ; metropolitan areas ; Italy
    Language English
    Dates of publication 2021-10
    Size p. 4708-4726.
    Publishing place John Wiley & Sons, Ltd.
    Document type Article
    Note JOURNAL ARTICLE
    ZDB-ID 1319202-4
    ISSN 1085-3278
    ISSN 1085-3278
    DOI 10.1002/ldr.4072
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    In stock of ZB MED Bonn / Germany

    Z 5058: Show issues

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  6. Article ; Online: Implementation of multispecies ecological networks at the regional scale: analysis and multi-temporal assessment.

    Modica, Giuseppe / Praticò, Salvatore / Laudari, Luigi / Ledda, Antonio / Di Fazio, Salvatore / De Montis, Andrea

    Journal of environmental management

    2021  Volume 289, Page(s) 112494

    Abstract: Today, major landscape changes affect ecological connectivity exerting adverse effects on ecosystems. Connectivity is a critical element of landscape structure and supports ecosystem functionality. Landscape connectivity can be efficiently increased in ... ...

    Abstract Today, major landscape changes affect ecological connectivity exerting adverse effects on ecosystems. Connectivity is a critical element of landscape structure and supports ecosystem functionality. Landscape connectivity can be efficiently increased in landscape ecology by building ecological networks (EN) through models mimicking the interaction between animal and vegetal species and their environment. ENs are important in sustainable landscape planning, where they need to be studied both by applying landscape metrics and by performing multi-temporal analyses. This paper presents theoretical and practical evidence of an analysis of a multispecies ecological network in Calabria (Italy) and its changes over three decades. Landscape connectivity was modeled basing on 66 focal faunal species' requirements. Human disturbance (HD) was defined and assessed according to distance from different disturbance sources. This allowed for the definition of overall habitat quality (oHQ). Landscape permeability to the animal movement was focused as the main concept to measure landscape fragmentation. Landscape graph theory was applied to perform a spatial comparison of the ENs robustness. Many binary and probabilistic indices and landscape morphological spatial pattern analysis (MSPA) were used in this perspective. We obtained a set of ecological networks, including nodes, patches (i.e., habitat patches), linkages, and corridors, all intertwined in one giant component. The multi-temporal analysis showed many indices' stationary values, while MSPA yielded an increase of habitat quality and habitat patches in core areas. This methodological approach allowed for assessing the regional EN's robustness in the time-span considered, thus providing a reliable tool for landscape planners and communities.
    MeSH term(s) Animals ; Conservation of Natural Resources ; Ecology ; Ecosystem ; Humans ; Italy ; Spatial Analysis
    Language English
    Publishing date 2021-04-03
    Publishing country England
    Document type Journal Article
    ZDB-ID 184882-3
    ISSN 1095-8630 ; 0301-4797
    ISSN (online) 1095-8630
    ISSN 0301-4797
    DOI 10.1016/j.jenvman.2021.112494
    Database MEDical Literature Analysis and Retrieval System OnLINE

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