Search Results (8)

Vehicle owners often use certified service centers throughout the warranty period, which usually extends for five years after buying. Nonetheless, after this timeframe concludes, a large number of owners turn to unapproved service providers, mainly motivated by financial factors. This change signifies a significant drop in income for automakers and their certified service networks. To tackle this issue, manufacturers utilize customer relationship management (CRM) strategies to enhance customer loyalty, usually depending on segmentation methods to pinpoint potential clients. However, conventional approaches frequently do not successfully forecast which clients are most likely to need or utilize maintenance services. This research introduces a machine learning-driven framework aimed at forecasting the probability of monthly maintenance attendance for customers by utilizing an extensive historical dataset that includes information about both customers and vehicles. Additionally, this predictive approach supports workforce planning and scheduling within after-sales service centers, aligning with AI-driven labor optimization frameworks such as those explored in the AI4LABOUR project. Four algorithms in machine learning—Decision Tree, Random Forest, LightGBM (LGBM), and Extreme Gradient Boosting (XGBoost)—were assessed for their forecasting capabilities. Of these, XGBoost showed greater accuracy and reliability in recognizing high-probability customers. In this study, we propose a machine learning framework to predict vehicle maintenance visits for after-sales services, leading to significant operational improvements. Furthermore, the integration of AI-driven workforce allocation strategies, as studied within the AI4LABOUR (reshaping labor force participation with artificial intelligence) project, has contributed to more efficient service personnel deployment, reducing idle time and improving customer experience. By implementing this approach, we achieved a 20% reduction in information delivery times during service operations. Additionally, survey completion times were reduced from 5 min to 4 min per survey, resulting in total time savings of approximately 5906 h by May 2024. The enhanced service appointment scheduling, combined with timely vehicle maintenance, also contributed to reducing potential accident risks. Moreover, the transition from a rule-based maintenance prediction system to a machine learning approach improved efficiency and accuracy. As a result of this transition, individual customer service visit rates increased by 30%, while corporate customer visits rose by 37%. This study contributes to ongoing research on AI-driven workforce planning and service optimization, particularly within the scope of the AI4LABOUR project. Full article

Wildfires, a natural part of the wildland life cycle, are experiencing a decades-long trend of increased frequency, duration, and magnitude, resulting in increased risk of fatalities and property damage. Fire suppression methods are adapting accordingly, including the increased use of aerial firefighting. Aerial firefighting, conducted in coordination with ground crews, provides real-time reconnaissance of a wildfire and performs strategic drops of retardant to contain and/or suppress the fire. These flight operations require airport and air traffic control infrastructure. The purpose of this report is to provide statistics on the U.S. aerial firefighting fleet, flight operations, and airport utilization and equipment in 2024. This information, which is not readily available, may be of use to airport planners, air navigation service providers, and policy makers. Thirty-four (34) Very Large/Large Air Tankers (VLAT/LATs) were under contract with the United States Forest Service (USFS) Multiple Award Task Order Contracts (MATOCs) in 2024. The aircraft, ranging in age from 27 to 57 years, performed 11,219 retardant drop and reposition flights. Flights operated on 88% of the days with an average of 35 flights per day and a maximum of 200 flights per day. The number of flights per aircraft across the fleet was not uniform (average 288 flights, max 465 flights). Consistent with firefighting practices, the flights operated under Visual Flight Rules (VFR), mostly in the afternoons, with an average retardant drop flight duration of 34 min. Two hundred and seven (207) airports supported at least one departure, with 14 airports supporting 50% of the departures. Eighty-six (86%) percent of the airports were towered and 84% had precision approach procedures. All but two military airports were public airports that are part of the National Plan for Integrated Airport System (NPIAS) and eligible for Airport Improvement Plan (AIP) funding. Runway length and weight bearing are limitations at several airports. Furthermore, operations are no longer limited to airports west of the Rockies, with increased operations in the mid-west and east coast. Full article

Water resources management and planning traditionally focus on visible liquid or blue water. However, green water also maintains social development and ecosystem services. Therefore, blue and green water should be incorporated into the watershed management system for evaluating water resources. To analyze the water resources of the Hanjiang River Basin, the SWAT model was set up using long-term and high-precision geographic data. The methods of wavelet analysis and Pearson’s correlation analysis were used to explore the influence mechanism of climate and vegetation changes on the blue and green water flow (BWF and GWF) of the main ecosystems in the basin. The results showed that: (1) The spatial–temporal distribution of the BWF and GWF in the main ecosystems of the basin over the past 50 years was uneven. Forest ecosystems and farmland ecosystems have a greater concentration of water resources in the south, while grassland ecosystems have a greater concentration of water resources in the east. (2) Climate dominates the BWF and GWF changes in the main ecosystems of the basin. The BWF and the precipitation change cycle are synergistic, and the GWF and the temperature change cycle are synergistic. (3) The correlation between vegetation and BWF and GWF in the farmland ecosystem is significant. Vegetation affects the hydrological change process of the BWF and GWF at the microscale. This study can provide data support and scientific rules for ecosystem water resource management in the basin. Full article

Habitat maps at high thematic and spatial resolution and broad extents are fundamental tools for biodiversity conservation, the planning of ecological networks and the management of ecosystem services. To derive a habitat map for Switzerland, we used a composite methodology bringing together the best available spatial data and distribution models. The approach relies on the segmentation and classification of high spatial resolution (1 m) aerial imagery. Land cover data, as well as habitat and species distribution models built on Earth observation data from Sentinel 1 and 2, Landsat, Planetscope and LiDAR, inform the rule-based classification to habitats defined by the hierarchical Swiss Habitat Typology (TypoCH). A total of 84 habitats in 32 groups and 9 overarching classes are mapped in a spatially explicit manner across Switzerland. Validation and plausibility analysis with four independent datasets show that the mapping is broadly plausible, with good accuracy for most habitats, although with lower performance for fine-scale and linear habitats, habitats with restricted geographical distributions and those predominantly characterised by understorey species, especially forest habitats. The resulting map is a vector dataset available for interactive viewing and download from open EnviDat data sharing platform. The methodology is semi-automated to allow for updates over time. Full article

From a climate change perspective, the governance of natural common-pool resources—the commons—is a key point in the challenge of transitioning to sustainability. This paper presents the main strategic advances of the São Paulo Urban Living Laboratory (ULL) regarding Food, Energy and Water (FEW Nexus) analysis and modelling at the border of a high biodiverse forest in a peri-urban region in southeast Brazil. It is a replicable and scalable method concerning FEW governance. The FEW Nexus is an analytical guide to actions that will enable a colossal set of innovative processes that the transition to sustainability presupposes. Sustainable governance of the FEW dimensions, seen as an innovation-based process, is approached by a decision making tool to understand the past and future dynamics of the system. The governance framework is based on a multi-criteria and multi-attribute set of sustainability-relevant factors used as indicators to model complex system dynamics (SD) and the stakeholders’ future expectations through a Delphi approach. Based on the three main dimensions of the Ecosystem Services Approach—Physical and Material Conditions, Attributes of Communities, and Rules-in-Use—the tool comprises thirteen specific sustainability indicators such as water and carbon footprints, land use social development, payment for ecosystem services, and land use gain indices. Its development was designed to generate a long-term network of socioenvironmental stakeholders’ decision making processes and collective learning about a higher level of sustainable systems. System Dynamics modelling demonstrates the associations between sustainability indicators and the impacts of payment for ecosystem services on the land use social development index, or on the trophic state index. The Delphi foresight approach, using the Promethee-Gaia method, allows us to understand the positions of multiple agents regarding the transition process. In this context, decision making tools can be very useful and effective in answering the “how to” questions of ULLs and paving the way for transition, providing collective planning and decision support frameworks for sustainability transition management. Full article

In 2012, the U.S. Department of Agriculture adopted a new planning rule that outlined a process for developing, amending, and revising land management plans for the 155 National Forests, 20 National Grasslands, and one Tallgrass Prairie managed by the U.S. Forest Service. The rule outlines a framework with three phases: assessment, development/amendment/revision, and monitoring. We are assisting National Forests in the western U.S. with the first phase by completing a series of assessments of riparian and groundwater-dependent ecosystems. Here, we describe our methods and the lessons learned over the course of conducting assessments for seven National Forests. Per the requirements of the planning rule, we conduct a rapid assessment of ecological integrity that uses existing data to evaluate drivers, stressors, structure, function, composition, and connectivity. We have collaborated with National Forests, state agencies, and other research groups to obtain datasets representing various wetland landscape features. Our work supports the plan revision process, from assessment through plan approval, and informs future forest and project planning for the restoration and maintenance of structure, function, composition, and connectivity. We developed our assessment methods in collaboration with resource managers at the National Forest and regional level to ensure useful end products such as published technical reports, literature reviews, photo libraries, or collections of datasets related to riparian and groundwater-dependent ecosystems. Our approach and lessons learned throughout the process are relevant to other resource management planning applications, analyses of landscape condition, as well as assessments of other ecosystems, such as forests or grasslands. Full article

A shared understanding of the benefits and tradeoffs to people from alternative land management strategies is critical to successful decision-making for managing public lands and fostering shared stewardship. This study describes an approach for identifying and monitoring the types of resource benefits and tradeoffs considered in National Forest planning in the United States under the 2012 Planning Rule and demonstrates the use of tools for conceptualizing the production of ecosystem services and benefits from alternative land management strategies. Efforts to apply these tools through workshops and engagement exercises provide opportunities to explore and highlight measures, indicators, and data sources for characterizing benefits and tradeoffs in collaborative environments involving interdisciplinary planning teams. Conceptual modeling tools are applied to a case study examining the social and economic benefits of recreation on the Ashley National Forest. The case study illustrates how these types of tools facilitate dialog for planning teams to discuss alternatives and key ecosystem service outcomes, create easy to interpret visuals that map details in plans, and provide a basis for selecting ecosystem service (socio-economic) metrics. These metrics can be used to enhance environmental impact analysis, and help satisfy the goals of the National Environmental Policy Act (NEPA), the 2012 Planning Rule, and shared stewardship initiatives. The systematic consideration of ecosystem services outcomes and metrics supported by this approach enhanced dialog between members of the Forest planning team, allowed for a more transparent process in identification of key linkages and outcomes, and identified impacts and outcomes that may not have been apparent to the sociologist who is lacking the resource specific expertise of these participants. As a result, the use of the Ecosystem Service Conceptual Model (ESCM) process may result in reduced time for internal reviews and greater comprehension of anticipated outcomes and impacts of proposed management in the plan revision Environmental Impact Statement amongst the planning team. Full article

Tropical forest management increasingly is challenged by multiple, complex, intersecting, and in many cases unprecedented changes in the environment that are triggered by human activity. Many of these changes are associated with the Anthropocene—a new geologic epoch in which humans have become a dominating factor in shaping the biosphere. Ultimately, as human activity increasingly influences systems and processes at multiple scales, we are likely to see more extraordinary and surprising events, making it difficult to predict the future with the level of precision and accuracy needed for broad-scale management prescriptions. In this context of increasing surprise and uncertainty, learning, flexibility, and adaptiveness are essential to securing ecosystem resilience and sustainability, particularly in complex systems such as tropical forests. This article examines the experience to date with and potential for collaborative, adaptive land and resource management in the El Yunque National Forest (EYNF)—the only tropical forest in the U.S. National Forest System. The trajectory of EYNF policy and practice over time and its capacity for learning, flexibility, and adaptiveness to change and surprise are analyzed through an historical institutionalism approach. EYNF policies and practices have shifted from an early custodial approach that focused mostly on protection and prevention to a top-down, technical approach that eventually gave way to an ecosystem approach that has slowly incorporated more flexible, adaptive, and active learning elements. These shifts in EYNF management mostly have been reactive and incremental, with some rarer, rapid changes primarily in response to significant changes in national-level policies, but also to local level conditions and changes in them. Looking to the future, it seems the EYNF may be better positioned than ever before to address increasing uncertainty and surprise at multiple scales. However, it must be able to count on the resources necessary for implementing adaptive, collaborative forest management in a tropical setting and on the institutional and organizational space and flexibility to make swift adjustments or course corrections in response to system changes and surprises. Full article