Estimating stand volume and above-ground biomass of urban forests using LiDAR

Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR). In this study we assessed forest stand volume and above-ground biomass (AGB) in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA) and mean stand height (H) from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first) (proxy of BA) and the 95th percentile of the distribution of all first returns (proxy of H). The R2 were 0.81 (p < 0.01) for the stand volume model and 0.77 (p < 0.01) for the AGB model with a RMSE of 23.66 m3·ha−1 (23.3%) and 19.59 Mg·ha−1 (23.9%), respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H), which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods

Modeling fire ignition probability and frequency using Hurdle models: a cross-regional study in Southern Europe

Abstract Background Wildfires play a key role in shaping Mediterranean landscapes and ecosystems and in impacting species dynamics. Numerous studies have investigated the wildfire occurrences and the influence of their drivers in many countries of the Mediterranean Basin. However, in this regard, no studies have attempted to compare different Mediterranean regions, which may appear similar under many aspects. In response to this gap, climatic, topographic, anthropic, and landscape drivers were analyzed and compared to assess the patterns of fire ignition points in terms of fire occurrence and frequency in Catalonia (Spain), Sardinia, and Apulia (Italy). Therefore, the objectives of the study were to (1) assess fire ignition occurrence in terms of probability and frequency, (2) compare the main drivers affecting fire occurrence, and (3) produce fire probability and frequency maps for each region. Results In pursuit of the above, the probability of fire ignition occurrence and frequency was mapped using Negative Binomial Hurdle models, while the models' performances were evaluated using several metrics (AUC, prediction accuracy, RMSE, and the Pearson correlation coefficient). The results showed an inverse correlation between distance from infrastructures (i.e., urban roads and areas) and the occurrence of fires in all three study regions. This relationship became more significant when the frequency of fire ignition points was assessed. Moreover, a positive correlation was found between fire occurrence and landscape drivers according to region. The land cover classes more significantly affected were forest, agriculture, and grassland for Catalonia, Sardinia, and Apulia, respectively. Conclusions Compared to the climatic, topographic, and landscape drivers, anthropic activity significantly influences fire ignition and frequency in all three regions. When the distance from urban roads and areas decreases, the probability of fire ignition occurrence and frequency increases. Consequently, it is essential to implement long- to medium-term intervention plans to reduce the proximity between potential ignition points and fuels. In this perspective, the present study provides an applicable decision-making tool to improve wildfire prevention strategies at the European level in an area like the Mediterranean Basin where a profuse number of wildfires take place

Modeling the influence of alternative forest management scenarios on wood production and carbon storage: A case study in the Mediterranean region

Forest ecosystems are fundamental for the terrestrial biosphere as they deliver multiple essential ecosystem services (ES). In environmental management, understanding ES distribution and interactions and assessing the economic value of forest ES represent future challenges. In this study, we developed a spatially explicit method based on a multi-scale approach (MiMoSe-Multiscale Mapping of ecosystem services) to assess the current and future potential of a given forest area to provide ES. To do this we modified and improved the InVEST model in order to adapt input data and simulations to the context of Mediterranean forest ecosystems. Specifically, we integrated a GIS-based model, scenario model, and economic valuation to investigate two ES (wood production and carbon sequestration) and their trade-offs in a test area located in Molise region (Central Italy). Spatial information and trade-off analyses were used to assess the influence of alternative forest management scenarios on investigated services. Scenario A was designed to describe the current Business as Usual approach. Two alternative scenarios were designed to describe management approaches oriented towards nature protection (scenario B) or wood production (scenario C) and compared to scenario A. Management scenarios were simulated at the scale of forest management units over a 20-year time period. Our results show that forest management influenced ES provision and associated benefits at the regional scale. In the test area, the Total Ecosystem Services Value of the investigated ES increases 85% in scenario B and decreases 82% in scenario C, when compared to scenario A. Our study contributes to the ongoing debate about trade-offs and synergies between carbon sequestration and wood production benefits associated with socio-ecological systems. The MiMoSe approach can be replicated in other contexts with similar characteristics, thus providing a useful basis for the projection of benefits from forest ecosystems over the futureL'articolo è disponibile sul sito dell'editore www.elsevier.com/locate/envre

Modeling the influence of alternative forest management scenarios on wood production and carbon storage: A case study in the Mediterranean region

Forest ecosystems are fundamental for the terrestrial biosphere as they deliver multiple essential ecosystem services (ES). In environmental management, understanding ES distribution and interactions and assessing the economic value of forest ES represent future challenges. In this study, we developed a spatially explicit method based on a multi-scale approach (MiMoSe-Multiscale Mapping of ecosystem services) to assess the current and future potential of a given forest area to provide ES. To do this we modified and improved the InVEST model in order to adapt input data and simulations to the context of Mediterranean forest ecosystems. Specifically, we integrated a GIS-based model, scenario model, and economic valuation to investigate two ES (wood production and carbon sequestration) and their trade-offs in a test area located in Molise region (Central Italy). Spatial information and trade-off analyses were used to assess the influence of alternative forest management scenarios on investigated services. Scenario A was designed to describe the current Business as Usual approach. Two alternative scenarios were designed to describe management approaches oriented towards nature protection (scenario B) or wood production (scenario C) and compared to scenario A. Management scenarios were simulated at the scale of forest management units over a 20-year time period. Our results show that forest management influenced ES provision and associated benefits at the regional scale. In the test area, the Total Ecosystem Services Value of the investigated ES increases 85% in scenario B and decreases 82% in scenario C, when compared to scenario A. Our study contributes to the ongoing debate about trade-offs and synergies between carbon sequestration and wood production benefits associated with socio-ecological systems. The MiMoSe approach can be replicated in other contexts with similar characteristics, thus providing a useful basis for the projection of benefits from forest ecosystems over the futureL'articolo è disponibile sul sito dell'editore www.elsevier.com/locate/envre

Mapping and assessment of forest ecosystems and their services - Applications and guidance for decision making in the framework of MAES

The aim of this report is to illustrate by means of a series of case studies the implementation of mapping and assessment of forest ecosystem services in different contexts and geographical levels. Methodological aspects, data issues, approaches, limitations, gaps and further steps for improvement are analysed for providing good practices and decision making guidance. The EU initiative on Mapping and Assessment of the state of Ecosystems and their Services (MAES), with the support of all Member States, contributes to improve the knowledge on ecosystem services. MAES is one of the building-block initiatives supporting the EU Biodiversity Strategy to 2020.JRC.H.3-Forest Resources and Climat

How do cardiologists select patients for dual antiplatelet therapy continuation beyond 1 year after a myocardial infarction? Insights from the EYESHOT Post-MI Study

Background: Current guidelines suggest to consider dual antiplatelet therapy (DAPT) continuation for longer than 12 months in selected patients with myocardial infarction (MI). Hypothesis: We sought to assess the criteria used by cardiologists in daily practice to select patients with a history of MI eligible for DAPT continuation beyond 1 year. Methods: We analyzed data from the EYESHOT Post-MI, a prospective, observational, nationwide study aimed to evaluate the management of patients presenting to cardiologists 1 to 3 years from the last MI event. Results: Out of the 1633 post-MI patients enrolled in the study between March and December 2017, 557 (34.1%) were on DAPT at the time of enrolment, and 450 (27.6%) were prescribed DAPT after cardiologist assessment. At multivariate analyses, a percutaneous coronary intervention (PCI) with multiple stents and the presence of peripheral artery disease (PAD) resulted as independent predictors of DAPT continuation, while atrial fibrillation was the only independent predictor of DAPT interruption for patients both at the second and the third year from MI at enrolment and the time of discharge/end of the visit. Conclusions: Risk scores recommended by current guidelines for guiding decisions on DAPT duration are underused and misused in clinical practice. A PCI with multiple stents and a history of PAD resulted as the clinical variables more frequently associated with DAPT continuation beyond 1 year from the index MI

Combining high-resolution images and LiDAR data to model ecosystem services perception in compact urban systems

In this study, we aim to understand how the provision of ecosystem services (ESS) is spatially distributed within a compact urban system considering the structure and spatial arrangement of green spaces in relation to built-up areas and other infrastructures. For this purpose, we devised an approach to assess the ESS provided by urban green spaces through the integration of social data (i.e., stakeholders’ perception of the multiple benefits of green spaces) with remotely sensed data, such as high-resolution satellite images and Laser Imaging Detection and Ranging (LiDAR) point-cloud. We developed a spatially explicit indicator (or metric) called Normalized Difference Green-Building Volume (NDGB), derived from remote sensing, that can be used to predict the way people perceive the ESS conveyed by green spaces in cities. We designed the NDGB metric using the city of Bari, Southern Italy, as a case example by involving four groups of stakeholders (n = 202) to assess ten urban green spaces. Our results show a strong positive relationship between the NDGB and the way stakeholders perceive the ESS provided by these urban green spaces. Thus, our indicator accurately expresses the relationship between stakeholders’ perceptions of ESS provided by green spaces and the physical data (i.e., green space structure) produced by remote sensing technology. The green space most highly evaluated by the NDGB indicator, the periurban park “Lama Balice” was also the one on which all stakeholder group responses converged, including the group of NGOs and associations, which assigned average low scores for perceived ESS across all the green spaces presented in the study. The study was developed using the city of Bari in Southern Italy as testbed. There is a need to further extend and replicate our approach to other urban systems across different regions (e.g., Northern Europe, North America, Asia), especially those which are in the process of pursuing more sustainable green infrastructure planning and development, as they could be inclined to adopt our approach in ongoing decision making processes. We believe our approach can inform planners and decision makers on ESS provision and supply them with evidence of the local co-benefits of green spaces as well as of the spatial distribution of ESS within compact urban systems

Combining high-resolution images and LiDAR data to model ecosystem services perception in compact urban systems

In this study, we aim to understand how the provision of ecosystem services (ESS) is spatially distributed within a compact urban system considering the structure and spatial arrangement of green spaces in relation to built-up areas and other infrastructures. For this purpose, we devised an approach to assess the ESS provided by urban green spaces through the integration of social data (i.e., stakeholders' perception of the multiple benefits of green spaces) with remotely sensed data, such as high-resolution satellite images and Laser Imaging Detection and Ranging (LiDAR) point-cloud. We developed a spatially explicit indicator (or metric) called Normalized Difference Green-Building Volume (NDGB), derived from remote sensing, that can be used to predict the way people perceive the ESS conveyed by green spaces in cities. We designed the NDGB metric using the city of Bari, Southern Italy, as a case example by involving four groups of stakeholders (n = 202) to assess ten urban green spaces. Our results show a strong positive relationship between the NDGB and the way stakeholders perceive the ESS provided by these urban green spaces. Thus, our indicator accurately expresses the relationship between stakeholders' perceptions of ESS provided by green spaces and the physical data (i.e., green space structure) produced by remote sensing technology. The green space most highly evaluated by the NDGB indicator, the periurban park "Lama Balice", was also the one on which all stakeholder group responses converged, including the group of NGOs and associations, which assigned average low scores for perceived ESS across all the green spaces presented in the study. The study was developed using the city of Bari in Southern Italy as testbed. There is a need to further extend and replicate our approach to other urban systems across different regions (e.g., Northern Europe, North America, Asia), especially those which are in the process of pursuing more sustainable green infrastructure planning and development, as they could be inclined to adopt our approach in ongoing decision making processes. We believe our approach can inform planners and decision makers on ESS provision and supply them with evidence of the local co-benefits of green spaces as well as of the spatial distribution of ESS within compact urban systems

Remote Sensing of Urban Forests

Urban forests and green infrastructures at large are of critical importance for contemporary cities as they provide a wide range of ecosystem services (ESS) that enhance the quality of life of urban dwellers. Remote sensing technologies have greatly contributed to assessing and mapping the spatial distribution of ESS in urban areas, although more research is needed given the availability of new sensors from multiple satellites and platforms and the particular characteristics of urban environments (e.g., high heterogeneity). This Special Issue hosts papers focusing on the temporal and spatial dynamics of urban forests with special attention given to the most recent remote sensing technologies as well as advanced methods for processing geospatial data and extracting meaningful information

Assessing Forest Road Network Suitability in Relation to the Spatial Occurrence of Wildfires in Mediterranean Forest Ecosystems

Identifying the relationship between forest roads and wildfires in forest ecosystems is a crucial priority to integrate suppression and prevention within wildfire management. In various investigations, the interaction of these elements has been studied by using road density as one of the anthropogenic dependent variables. This study focused on the use of a broader set of metrics associated with forest road networks, such as road density, the number of links (edges), and access percentage based on two effect zones (road buffers of 75 m and 97 m). These metrics were employed as response variables to assess forest road network suitability in relation to wildfires, specifically the number and size of fires (2000–2021), using the Apulia region (Italy) as a case study. In addition, to enhance the comprehensive understanding of road networks in forest ecosystems in relation to wildfires, this study considered various affecting factors, including land-cover data (forest, maquis, natural grassland), geomorphology (slope, aspect), vegetation (Normalized Difference Vegetation Index (NDVI)), and morphometric indexes (Topographic Position Index (TPI), Terrain Ruggedness Index (TRI), Topographic Wetness Index (TWI)). We used geographically weighted regression (GWR) and ordinary least squares (OLS) to analyze the interaction between forest road metrics and dependent variables. Results showed that the GWR models outperformed the OLS models in term of statistical results such as R2 and the Akaike Information Criterion (AICc). We found that among road metrics, road density and number of links do not effectively demonstrate the correlation between roads and wildfires as a singular criterion. However, they prove to be a beneficial supplementary variable when considered alongside access percentage, particularly within the 75-m buffer zone. Our findings are used to discuss implications for forest road network planning in a broader wildfire management analysis. Our findings demonstrate that forest roads are not one-dimensional and static infrastructure; rather, they are a multi-dimensional and dynamic structure. Hence, they need to be analyzed from various perspectives, including accessibility and ecological approaches, in order to obtain an integrated understating of their interaction with wildfire