Web Map Research Articles

Developing primary care services for stroke survivors: the Improving Primary Care After Stroke (IPCAS) research programme

Background It is recognised that longer-term needs after stroke may not be well addressed by current services. The aim of this programme of research was to develop a novel primary care model to address these needs and to evaluate this new approach. Objectives The work was divided into three workstreams: development of a primary care model development of a ‘Managing Life After Stroke’ programme (including self-management) for people with stroke evaluation of the effectiveness and cost effectiveness of these interventions. Design The development of the primary care model involved information gathering in the form of literature reviews, patient and public involvement workshops, qualitative studies (interviews and focus groups), a consensus study and a pilot study, all feeding into a multidisciplinary intervention development group that approved the final primary care model. In parallel, a further literature review, consultation workshops with healthcare professionals and patients and public involvement fed into the iterative development of the ‘My Life After Stroke’ programme. In the final phase of the programme, the two interventions were evaluated in a cluster randomised controlled trial, which included a process evaluation and within-trial cost-effectiveness analysis. Setting General practices in the East of England and East Midlands. Participants People with a history of stroke identified from general practice stroke registers. Interventions The Improving Primary Care After Stroke model of primary care delivery. This comprised five components: a structured review; a direct point of contact; improving communication between primary and secondary care; local service mapping; and training of primary care professionals. The ‘My Life After Stroke’ self-management programme for people with stroke comprised an initial individual session, four weekly group-based sessions and a final individual session. Main outcome measures The coprimary end points for the trial were two subscales (emotion and participation) of the Stroke Impact Scale v3.0 at 12 months after randomisation. Secondary outcomes included the Stroke Impact Scale Short Form, the EuroQol-5 Dimension, five level questionnaire, the ICEpop CAPability measure for Adults, the Southampton Stroke Self-Management Questionnaire and the Health Literacy Questionnaire. Data sources General practice records for health economic costing data. Patient questionnaires for outcomes. Results Trial: 46 clusters (general practices) were randomised with 1040 participants. At 12 months, there was a 0.64 (97.5% confidence interval −1.7 to +2.8) improvement in the emotion outcome in the intervention arm compared to the control arm and a 1.3 (97.5% confidence interval −2.0 to +4.6) increase in the participation outcome in the intervention arm compared to control. There was also no evidence of effect of the intervention on short form Stroke Impact Scale, quality of life (EuroQol 5 Dimension 5 level questionnaire), well-being (ICEpop CAPability measure for Adults), Southampton Stroke Self-Management questionnaire or health literacy (Health Literacy Questionnaire). Process evaluation: over 80% of participants received a review. Only a third of patients attended the ‘My Life After Stroke’ course. The direct point of contact service was hardly used. The local directory of services had variable take-up by healthcare professionals. It did not prove possible to support improved communication between primary and secondary care as originally intended. Training fidelity was high. Cost-effectiveness analysis: the intervention increased primary care workload and was associated with a non-significant, higher quality-adjusted life-year at 12 months. The incremental cost per quality-adjusted life-year was £20,863. Limitations There were differences in age, sex and proportion of people from minority ethnic groups in the trial population as compared to a typical general practice stroke register. Uptake of the intervention was variable. Ceiling effects were observed in the primary outcome measure. Follow-up was limited to 12 months. Conclusions This programme of research has reaffirmed the importance of addressing longer-term needs of people after stroke in the community. The most commonly expressed need is fatigue. The primary care model that we developed was not effective at addressing these needs. Our qualitative findings suggest that an intervention focused on patients earlier after their stroke or one which is more intensive might be effective. There was a mismatch between the needs reported by stroke survivors and evidence available for how to address these needs. Future work Research to inform who should be offered poststroke assessment of needs in the community in the longer term (after 6 months). Development and evaluation of interventions to address fatigue, low mood and cognitive problems in people with stroke in the community. Study registration This study is registered as PROSPERO 2015 CRD42015026602. Trial registration This trial is registered as ISRCTNCT03353519. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research programme (NIHR award ref: PTC-RP-PG-0213-20001) and is published in full in Programme Grants for Applied Research; Vol. 12, No. 1. See the NIHR Funding and Awards website for further award information.

Deep learning-based glioma grading and feature visualization analysis

With the rapid development of geolocation information services, which involves large-scale location data querying, including map data and user location data. Traditional data storage and query methods face challenges of storage space and query efficiency, and the ability to process real-time geolocation data becomes critical in Geographic Information Services positioning systems that require servers to achieve millisecond-level response speeds. In addition to this, in geolocation services, for a given latitude and longitude information, it is necessary to quickly determine whether it exists or matches some specific location in the map service. The common traditional information finding algorithm in geographic location service is B-tree, and this paper proposes a geographic location information finding algorithm based on the Bloom filter, which mainly solves two problems. One is the storage problem of large amounts of latitude and longitude information; the other is how to convert the data stored in bytes level to bits level, which greatly reduces the space complexity and the inefficient information finding. The Bloom filter reduces the query time to linear time complexity O(n). The fastest query time for 5 million items of latitude and longitude information can reach 3.12 seconds. This article will illustrate the efficiency of the proposed method through a real-time traffic navigation scenario.

Research on the fast geolocation algorithm based on Bloom filter

With the rapid development of geolocation information services, which involves large-scale location data querying, including map data and user location data. Traditional data storage and query methods face challenges of storage space and query efficiency, and the ability to process real-time geolocation data becomes critical in Geographic Information Services positioning systems that require servers to achieve millisecond-level response speeds. In addition to this, in geolocation services, for a given latitude and longitude information, it is necessary to quickly determine whether it exists or matches some specific location in the map service. The common traditional information finding algorithm in geographic location service is B-tree, and this paper proposes a geographic location information finding algorithm based on the Bloom filter, which mainly solves two problems. One is the storage problem of large amounts of latitude and longitude information; the other is how to convert the data stored in bytes level to bits level, which greatly reduces the space complexity and the inefficient information finding. The Bloom filter reduces the query time to linear time complexity O(n). The fastest query time for 5 million items of latitude and longitude information can reach 3.12 seconds. This article will illustrate the efficiency of the proposed method through a real-time traffic navigation scenario.

Mapping, impacts, characterization and extent of acid sulfate soils in Finland

Acid sulfate soils (ASS) cause big problems worldwide due to their potential to form sulfuric acid during oxidation of sulfidic materials, resulting in very acid soil (pH <4.0). Impacts include acidification of soil and water, leaching of metals, decreased nutrient supply, deterioration of water fauna and flora, and corrosion of infrastructure. These soils also exhibit poor geotechnical properties. Finland has the largest occurrences of ASS in Europe, mainly along the coast of the Baltic Sea. The EU Water Framework Directive brought about wide co-operation to reduce the harmful impacts of ASS in Finland. One urgent step was to localize and characterize the occurrences of ASS. The more than 10 year-long programme, led by the Geological Survey of Finland (GTK), started in 2009 and field work was completed in 2021. During the programme observations, measurements, sampling and analyses were made at 23 000 sites in an area of 5 010 000 ha. Traditionally ASS in Finland have been considered to comprise fine-grained sulfidic sediments and/or their oxidized layers, occurring on agricultural land along the coast below the highest shoreline of the Littorina Sea transgression. This study recognized and classified significant occurrences of other types of potentially harmful ASS materials: (1) coarse-grained ASS (sand), (2) organic ASS (peat) and (3) unsorted ASS (till material). The methods, definition and classification of Finnish ASS have been revised. We calculated the extent of ASS along the coast to be about 1 000 000 ha corresponding to 21% of the area covered in the past by the Littorina Sea, and three to six times more than earlier estimates. In addition, some occurrences of ASS were recognized inland, mainly related to black shales and sulfidic ores. The mapping data can be accessed via the GTK map service (www.gtk.fi) providing information about the distribution and properties of ASS.

A service function chain mapping scheme based on functional aggregation in space-air-ground integrated networks

Being a novel network architecture, the Space-air-ground integrated network (SAGIN) offers advantages such as extensive network coverage and seamless ubiquitous access. However, it also encounters the challenge of balancing a growing user demand with limited network service resources. In order to further improve the utilization rate of network resources, a group of virtual network functions can be connected according to certain business logic to form a dynamic reconfigurable service function chain. This can provide diversified and high-quality network services for users. So by aggregating the same type of network function, we can reduce the cost of service chain mapping. Based on the above ideas, this paper proposes an Aggregation of Service Function Chain mapping algorithm (A-SFC). The aggregated service function chain topology is mapped according to an improved isomorphic graph search mapping algorithm, resulting in a deployment solution that minimizes the mapping cost by aggregating static SFC requests by end-system division. Experimental results show that the algorithm is able to find an effective mapping scheme under resource constraints. In addition to reducing computation, the algorithm effectively minimizes the consumption of computational resources while delivering excellent performance in terms of service delay and mapping cost.

Correction to “Aerial online mapping on‐board system by real‐time object detection for UGV path generation in unstructured outdoor environments”

Correction to “Aerial online mapping on‐board system by real‐time object detection for UGV path generation in unstructured outdoor environments”

Digital identification and pattern recognition capabilities using machine learning methods, navigation systems, and video surveillance

The objects of the study are unmanned vehicles and branches of the bridge of the city of Kyiv (Ukraine), which connects the Great Ring Road, Zhytomyr Highway and Peremogy Avenue. The built routes were analyzed using the technology of recognition of road signs, people and vehicles. The important problem of this research is to analyze the possibilities of detecting obstacles by an unmanned vehicle using pattern recognition, which combines the methods of machine communication, navigation and real-time video surveillance. Based on the study, the results of detecting and avoiding obstacles on the road, where a study was conducted to investigate the main reasons that can cause time delays (traffic jams, weather conditions, accidents). The results of planning and navigation are obtained to determine the appropriate road route, which allows detecting and eliminating obstacles on the road, as well as building a map plan of the route in advance using online map services (Google Maps). It is shown that recognition of road signs (based on the classification using a road sign map consisting of 7 categories), people and vehicles minimizes the occurrence of road accidents, traffic jams and time delays. To recognize the images of road signs, people and vehicles, we studied the road sections connecting to the branched bridge. Thus, the authors have reviewed and analyzed the digital capabilities of pattern identification and recognition using machine learning methods, navigation and video surveillance systems, where the safety of vehicles with detection of road signs and obstacles on the way is of great importance. The results obtained can complement the possibilities of using unmanned vehicles to avoid obstacles and road accidents based on a trained pattern recognition system. This system, using convolutional neural networks and video surveillance navigation systems, will be able to provide the driver and the people around it with safe driving conditions.

Expectations of i-Tree Eco as a tool for urban tree management in Nordic cities

While urban forests are recognized as imperative toward climate adaptation in cities and provide health and recreational benefits to citizens, municipal tree officers often struggle to find successful governance arrangements and budget support toward long-lasting investment and implementation in new planting schemes and protection of existing trees. Since its release in 2006, i-Tree Eco has helped urban tree officers worldwide to find tangible leverage in the means of quantitative mapping, numeric measures, and economic values of ecosystem services. This may in turn help ease gridlocks and potentially support constructive dialogues across sectors, with decision-makers and public engagement. With the release of i-Tree Eco v. 6 in Europe 2018, 13 Nordic cities were engaged in a larger research project with ambitions to use i-Tree Eco for the purpose of retrieving numeric and monetary data of the biophysical structures and ecosystem services of the urban forest. Based on questionnaires and semi-structured interviews, we present the results from the Nordic i-Tree project with a focus on expectations, opportunities, and potential barriers experienced in using i-Tree Eco in urban forest management. The most prominent expectation and foreseeing opportunities were recognized toward using numeric information on trees to change policies and support cross-sectoral collaboration while reaching politicians and the public. Identified barriers involved how limited resources are spent on public outreach and how information about the project to relevant stakeholders were not distributed from the beginning which may have implications on the dissemination of results. As some important ecosystem services, e.g., cultural services, are not captured by i-Tree Eco, presenting the partial value of urban trees may pose also potential risks to cross-sectoral collaboration. Other findings conclude that although numeric information on ecosystem services is seen as beneficial in terms of communicating with different stakeholders, a deeper understanding toward the criteria used in the valuation process and the potential risks of numeric approaches may provide more context-specific applications.

Assessment of a service-learning project experience in mobility and spatial data

To enhance sustainable and walkable cities we need to know which aspects of the urban environment affect children’s walkability and working on measures related to communication and education to ensure widespread awareness in society as a whole. The aim of this paper is to advance the implementation of participative and dynamic techniques at university level and targeting children from a sustainable mobility perspective. Through the Service-Learning project “Let's Walk Safely to School!” three specific objectives – related with learning, service and teaching are addressed. While learning, university students conducted a community service and resolved several challenges related with complementary skills for pedestrian mobility and Geographic Information Systems, while children learn mobility concepts. Its development combines the resolution of a challenge, learning by doing – since the whole process was carried out in a real context –, and cooperative learning. Using the results of a survey of 200 children studying in a school in Madrid, field work, and digital mapping, eight University students developed an interactive web map which classifies the streets around the school according to the children’s comfort level, safety/security and ease of travel. The participants broadened their academic competencies, while exchange skills, knowledge and expertise, and also acquired transversal competencies related to teamwork, organisation and planning, effective communication and knowledge of ICTs.

IeMTLF: Interaction-enhanced Multi-Task Learning Framework for next location prediction

Location-Based Services (LBSs) provide spatial and semantic information of various locations, thanks to the advances in mobile devices and commercial map services. However, most existing studies on next location prediction neglect the semantic information and do not investigate the effects of different levels of semantic granularity. To address these issues, we propose an Interaction-enhanced Multi-Task Learning Framework (IeMTLF) that jointly predicts the next location and its semantic category and leverages higher-order feature interactions to enrich the semantic learning process. Moreover, we examine the effect of two different levels of semantic granularity, namely, specific and abstract, on prediction performance. We conducted extensive experiments on two real-world datasets and demonstrate that IeMTLF outperforms seven baselines on all evaluation metrics, with a maximum gain of more than 13% for Acc@5 compared to the state-of-the-art method. Our implementation code is available at https://github.com/mrc-wyh/IeMTLF.

Identifying where hospital and community trusts are managing general practices in England: a service mapping study.

Organisations providing secondary care in the NHS in England have historically not also provided primary health care, but this is changing. Data on where this kind of 'vertical integration' is happening are lacking, making it difficult to evaluate its impact. To compile a comprehensive list of instances of secondary care trusts running general practices in England, to enable evaluation of the impact of such arrangements. This service mapping study comprises review, collation, synthesis, and analysis of published information describing secondary and primary care provision in the NHS in England in March 2021. Desk-based collection, including hand-searching, of secondary care organisations' statutory annual reports. Triangulation via comparison with national data on general practices, the general practice workforce and practice contracts. It was possible to construct a database of all instances of trusts running general practices in England as of 31 March 2021. We have identified 26 trusts running a total of 85 general practices, operating across a total of 116 practice sites. These practices have on average fewer patients and fewer GP full-time equivalents than other general practices, and before becoming vertically integrated were performing less well in the Quality and Outcomes Framework. We recommend that national statistics recording the details of general practices contracting with the NHS should include whether each practice is owned by another organisation and whether that is an NHS trust, another public body, or a private organisation. Such data are required to enable evaluation of the impacts of this kind of vertical integration.

Implementation of BIM Data in CityGML—Research and Perspectives for Creating a QGIS Plugin for Spatial Analysis: Experience from Poland

The subject of this research was to develop an effective strategy for combining various data sources, including the feasibility of implementing BIM in CityGML into an existing system supported by the GIS program. The study analyzed the path for converting BIM files to the CityGML format and the course of transmission of this data and data from the completed queries to the GIS program. An overview of external sources, map services, tools for acquiring accurate information about the terrain, and IT tools that could potentially be used was also carried out. The collected data proved deficiencies in the geospatial information of the analyzed area, defining the type of missing data necessary for the planned analyses. The results made it possible to determine further work and the basis for developing a plugin for the QGIS program. The plugin should facilitate energy efficiency, urban, and architectural analyses. The article also discusses the future opportunities for developing research directions for developing new 3D models of cities and collecting data for analysis. The analyses took into account the directions of geometric changes in 3D models as the result of the rapid development of digital tools. Ultimately, this research demonstrated the development demand for modern digital tools in the context of spatial and urban analysis, emphasizing the dynamic evolution in the field of GIS and the prospects of accelerating work on the integration of spatial data and their analysis thanks to the possibility of using open-source programs and our own efforts for their expansion.

Теоретико-методичні засади вебкартографування постмілітарних об'єктів

Purpose of the research objective is to develop and substantiate the theoretical and methodological foundations of web mapping of post-military facilities, taking into account the most effective approaches and techniques for collecting, analyzing, processing, and visualizing spatial data. The methodology includes using modern technologies to create accurate and informative interactive maps that provide not only the physical location of the objects but also detailed information, including textual, illustrative materials, graphical data, and 3D models. Results. Based on a comprehensive approach to researching, documenting, and presenting post-military facilities, the article elaborates the theoretical and methodological foundations of their web mapping. The relevance of using innovative digital technologies for creating interactive maps is discussed. The research methodology based on the collection, analysis and visualization of spatial data is considered in detail. The main principles and approaches to web mapping are highlighted, including historicity, systemic integrity, reliability, modernity, coherence, informativeness, presentability, accessibility, technological sophistication, variability of geographic bases, and partnership for effective project implementation. A technological scheme of web mapping is proposed, covering the stages of data collection, processing, and actual web mapping, ensuring a multidisciplinary and integrative approach to solving the set task. Designing and implementing web maps considering historical, cultural, technical data, and the current state of post-military facilities requires the interaction of specialists from various fields of knowledge. Scientific novelty and practical significance. The theoretical and methodological principles of interdisciplinary web mapping of post-military objects were developed for the first time. The principles and approaches to it have been defined, a technological scheme for web mapping of post-military objects has been developed. The proposed methodology and technology determine the practical significance of the research. Based on them, interactive maps of post-military facilities of any territory will be used in various fields of activity: education, science, preservation of historical and cultural heritage, tourism, promotion of the region.

ГЕОАҚПАРАТТЫҚ ТЕХНОЛОГИЯЛАР ГЕОКЕҢІСТІКТІК ОЙЛАУ ДАҒДЫЛАРЫН ДАМЫТУ ҚҰРАЛЫ РЕТІНДЕ

The use of geospatial technologies is becoming increasingly important in geography education, enabling activities such as spatial data retrieval, sampling, organised storage and transfer of necessary information. However, this process is very slow due to many obstacles that hinder the implementation of geospatial technologies in secondary education. Therefore, the purpose of this study was to analyse the current status of geospatial technologies in teaching geography in schools in Kazakhstan and to as-sess the potential of these technologies to develop students’ geospatial skills. The state of application of geospatial technologies in secondary education in Kazakhstan was determined by a survey. The survey involved 208 geography teachers from 17 regions and 3 large cities of Kazakhstan. The survey results showed that 96.2% of respondents use geospatial technologies (geographic information systems – GIS, software, mapping services, geoportals, mobile GIS applications). The most common are mobile GIS applications (69.5%) and mapping services (21.4%). It was also found that 24.1% of respondents use ArcGis and 20.7% use QGIS for GIS-based data design. Although the content of typical secondary school programmes and textbooks reflects the problem of practical application of GIS technologies, it was found that teachers face a number of obstacles in using them. Therefore, teachers would benefit from using not only GIS but also geospatial technologies in general when teaching school geography. In the future, geospatial technologies will help students to develop geospatial thinking skills due to their multifunctional capabilities.

WEB MAPPING OF SURFACE WATER POLLUTION IN LVIV REGION BY MEANS OF GIS AND REMOTE SENSING

The ecological state of surface waters in Lviv region is affected by various factors: soil and air pollution, technogenic load on the territory, inefficient operation of sewage treatment plants in settlements, pollution and littering of rivers with household and other waste. Another important problem leading to surface water pollution in the region is the absence of water protection zones and coastal protective strips. The lack of cartographic materials and the undefined boundaries of water pro-tection zones and coastal protection strips result in violations of land and water legislation. Currently, the state of water bodies in Lviv region is unsatisfactory. The main problems in this area lie in the growing negative impact on the environment and human health. The main purpose of this paper is to create a web map of surface water pollution in Lviv region, in particular, using remote sensing data. To this end, we have collected and systematized geospatial statistical cartographic materials on the ecological state of surface waters. In addition to statistical data, remote sensing (RS) data obtained from various sources have been used to assess the state of surface waters. The necessary software for the development of such a web map has been identified. An algorithm for uploading geospatial data to the created web resource has been developed. Thus, the web maps of surface water pollution in Lviv region have been created in ArcGIS Online, a software environment

A New Approach to Road Incident Detection Leveraging Live Traffic Data: An Empirical Investigation

Accidents can have a significant impact on road safety and the efficiency of transport. With the ever-increasing number of vehicles on the road, it is crucial to quickly detect and respond to such events to decrease the impact. The current paper presents a road accident and incident detection solution utilizing traffic API monitoring and continuously analyzing real-time traffic data from various sources like GPS-enabled devices. Consequently, the proposed approach can identify abnormal patterns in the movement of vehicles, such as unexpected road closures or an accident. It numerically analyzes the traffic pattern and identifies incidents and accidents using live traffic data collected from the map service. When the approach identifies any abnormality, it can immediately let the user know, allowing them to act accordingly. It can facilitate authorities in identifying accident-prone areas and deploy safety measures. This can help law enforcement agencies to identify drivers at risk of causing accidents and implement education and enforcement programs targeted towards them. Hence, the proposed approach can aid in reducing the negative impact of traffic incidents, and the public can respond to these incidents more preparedly.

Corporate Valuation of Indonesian Drone Service Company: Case Study of PT Kelana Geospasial

Indonesia's drone industry is expanding rapidly, fueled by significant investments and the growing necessity of drone technology in agriculture, offshore mining, and aerial photography. The global and Asian drone markets are also on the rise, with a projected 7.1% CAGR increase driven by industrial use and substantial investments. However, valuing Indonesian drone businesses is difficult due to their intangible assets and the startup nature of many companies, which focus more on value creation than financial stability. Established in 2016, PT Kelana Geospatial (PT KG) utilizes Unmanned Aerial Vehicle (UAV) technology for aerial mapping services and collaborates with sectors like agriculture, offshore mining, and aerial photography. They also offer UAV pilot certification and sell related products and parts. Despite their diverse offerings, PT KG faces stagnant growth and needs to enhance productivity with existing resources. The management struggles with valuing potential mergers, maintaining clear financial records, and addressing industry risks. PT KG's growth is mainly driven by mapping and maintenance services, although product sales have declined. Despite an improving financial situation, high production costs and expenses challenge profitability. While positive GPM and OPM indicate potential, NPM remains negative. Recommendations include expanding services, boosting efficiency, and leveraging technology and partnerships. By utilizing These strategies could foster sustainable growth and increase PT KG's enterprise value, currently estimated at IDR 3.84 billion.

Provision of Non-Financial Data: Mapping of Stakeholders, Products and Services

Provision of Non-Financial Data: Mapping of Stakeholders, Products and Services

CLIM-SEG: A generalizable segmentation model for heat and flood risk mapping

With the escalating impact of climate change coupled with increased urbanization, many cities will experience extreme heat events and intense flooding. Current modeling approaches often fail to incorporate high-resolution, frequently updated data sources, such as aerial imagery from web mapping platforms, limiting their effectiveness in identifying areas at risk. To address this gap, the paper presents CLIM-SEG, a novel framework for high-resolution urban heat and flood risk assessment, addressing critical gaps in current climate risk modeling. This framework integrates semantic segmentation of aerial imagery with a weighted sum approach that integrates environmental, socioeconomic, and building data to provide comprehensive risk evaluations at the census tract level. CLIM-SEG synthesize land cover data with hazard and vulnerability factors, producing risk scores ranging from 0 to 1. This low-cost and efficient framework can enable urban planners to prioritize resources for flood mitigation and heat adaptation, addressing the limitations of current approaches and contributing to the field of urban planning and climate change adaptation. The propoosed methodology incorporates a custom-curated dataset of 545 aerial images, including 145 manually annotated segmentation maps, to fine-tune advanced semantic segmentation models. The optimized Segmenter model achieves a pixel accuracy of 97.85% and an Intersection over Union (IoU) of 0.9578 for key urban features, significantly outperforming baseline models. Boston is selected to represent an ideal representation for both heat and flood risk, as the city experiences severe urban heat islands, and is susceptible to coastal and riverine flooding, with over 11,000 structures expected to be affected by 2070 due to sea level rise and increased precipitation. Results from flood and heat risk models indicate that census tracts in South End have the highest flood risk, with a weighted score value of 0.825, while census tracts in the Fenway-Kenmore neighborhood show the highest heat risk, with a score of 0.991. Both of these results have also been verified with other heat and flood risk mapping sources for Boston. The proposed framework of CLIM-SEG not only addresses the challenges faced by Boston but also has the potential to be scaled to other urban areas dealing with the impacts of climate change, providing a valuable tool for risk assessment and decision-making in the face of a changing climate.

SoCal EcoServe: an online mapping tool to estimate wildfire impacts in southern California

Background Wildfires in Mediterranean-type climate regions have numerous impacts on the ecosystem services provided by native shrublands, however, quantifying these impacts is challenging. Aims We developed a reproducible method to quantify fire impacts on ecosystem services and created a tool for resource managers in southern California. Methods The SoCal EcoServe tool consists of two components: a desktop tool and an online mapping tool. We used the Alisal Fire of 2021 as a case study and quantified: aboveground live carbon storage using pre- and post-fire biomass data; water runoff, groundwater recharge and sediment erosion retention by integrating data on burn severity into hydrological and sediment erosion models; and estimated recreation services and biodiversity using pre-fire data. Key results We estimated the Alisal Fire resulted in an immediate post-fire reduction in carbon storage of 25%, of which 20% was estimated to be permanently lost. Water runoff increased by 21%, groundwater recharge 7-fold, and sediment erosion increased 24-fold. Conclusions The EcoServe tool provides an initial approximation of wildfire impacts that can support damage assessments post-fire, track carbon storage and help identify priorities for post-fire restoration. Implications We intend the tool to be used by USDA Forest Service resource managers of shurblands in southern California. However, it can provide the framework for future work in shrublands throughout the western USA.