Adaptation Planning Research Articles

Agile Methodologies in Mobile App Development for Real-Time Data Processing

In the rapidly evolving landscape of mobile app development, the need for real-time data processing has become increasingly critical. Traditional software development methodologies often struggle to keep pace with the dynamic requirements and quick turnarounds demanded by modern mobile applications. Agile methodologies, with their emphasis on iterative development, flexibility, and close collaboration, offer a promising solution for meeting these demands. This paper explores the integration of Agile methodologies in the development of mobile applications specifically designed for real-time data processing. Agile approaches, including Scrum, Kanban, and Extreme Programming (XP), are evaluated for their effectiveness in addressing the challenges of real-time data processing in mobile apps. The study emphasizes the importance of continuous feedback, rapid prototyping, and adaptive planning in ensuring that mobile applications can efficiently process and deliver data in real time. Furthermore, the paper discusses how Agile's incremental delivery model allows development teams to respond swiftly to changing user needs and technological advancements, thereby enhancing the overall performance and user experience of mobile apps.

Agile Methodologies in Mobile App Development for Real-Time Data Processing

In the rapidly evolving landscape of mobile app development, the need for real-time data processing has become increasingly critical. Traditional software development methodologies often struggle to keep pace with the dynamic requirements and quick turnarounds demanded by modern mobile applications. Agile methodologies, with their emphasis on iterative development, flexibility, and close collaboration, offer a promising solution for meeting these demands. This paper explores the integration of Agile methodologies in the development of mobile applications specifically designed for real-time data processing. Agile approaches, including Scrum, Kanban, and Extreme Programming (XP), are evaluated for their effectiveness in addressing the challenges of real-time data processing in mobile apps. The study emphasizes the importance of continuous feedback, rapid prototyping, and adaptive planning in ensuring that mobile applications can efficiently process and deliver data in real time. Furthermore, the paper discusses how Agile's incremental delivery model allows development teams to respond swiftly to changing user needs and technological advancements, thereby enhancing the overall performance and user experience of mobile apps.

Do fintech, natural resources and globalization matter during ecological crises? A step towards ecological sustainability

The rate of biodiversity loss and forest depletion has surged significantly, primarily driven by the substantial increase in worldwide environmental deterioration. This alarming development is nearing the critical temperature limit of 2 °C, necessitating increased scrutiny. This study therefore adopts the Load Capacity Curve framework that amalgamates these concepts, offering a guide for implementing a robust and sustainable adaptation plan in the North African region. The research utilized data spanning from 1991 to 2022 and employed advanced quantitative methods, including quantile regression (QR), augmented mean group (AMG), and the Half-Panel Jackknife (HPJ) Wald-type test, to explore causality. The empirical findings challenge the notion of a U-shaped relationship between per capita GDP and ecological load capacity, revealing instead an inverted U-shaped pattern at the 25th and 50th quantiles. Additionally, the study identifies a negative and significant association between natural resource rents and globalization with the ecological load capacity factor, indicating a detrimental effect. On the other hand, Fintech demonstrates a statistically significant and positive impact on environmental sustainability, indicating a mitigating effect. Causality tests further reveal bidirectional causality between ecological load capacity and per capita GDP, GDP squared, and Fintech, while a unidirectional positive relationship exists between globalization and ecological load capacity. Based on these findings, the study puts forth several policy recommendations to support informed decision-making.

Scalability of CASCADE2001: Gis-Based Flood Risk Screening Tool to Support Watershed Master Planning

Flood risk analysis is the instrument by which floodplain and stormwater utility managers create a sound strategy and adaptation plans to reduce flood potential in their communities. As a result, there is a need to develop a flood risk screening tool to analyze watersheds and find vulnerable areas by leveraging the scientific and technological developments of the last decade to prioritize improvements. Because local municipalities are continuously challenged by the impacts of changes in precipitation and other climatic events, the screening tool needs to be scalable, while providing similar results of spatial inundation extent regardless of the scale. Likewise, the ability to perform this analysis without overwhelming limited modeling budgets is a goal for local governments who may spend large amounts of money on capital in the future to retrofit their stormwater management systems. The present study investigates the scalability of a GIS-based hydrologic-hydraulic model, CASCADE2001, to support development of watershed-based flood protection plans. The comparative analysis of the predicted flood response at three nested levels of scale were applied in south Florida to a 8-digit hydrologic unit code (HUC) level (the Caloosahatchee Watershed), a 12-digit HUC level (the Ninemile Canal Subwatershed within the Caloosahatchee Watershed), and a local municipal level (City of Clewiston, Florida within the Ninemile Canal subwatershed). The findings were that the model was scalable and the infrastructure that mattered with respect to results was driven by the scale.

Institutional Designs for Procedural Justice and Inclusion in Urban Climate Change Adaptation

Although there is broad consensus that more inclusive approaches are needed in climate adaptation planning, it is unclear how cities should redesign rules, institutions, and decision-making processes to produce more equitable forms of participation and engagement. This paper evaluates different planning procedures and institutional arrangements across twenty-five U.S. cities. Although arrangements are context-specific, institutional designs fall into three categories: consultative partnerships, strategic collaborations, and expansive co-governance arrangements. Each institutional design leads to different kinds of inclusion outcomes. Our results empiricize how cities can pursue more inclusive climate adaptation planning and highlight opportunities to advance and implement broader procedural equity goals.

Capacity development training workshop on crop simulation modelling and effects of climate risks on agricultural production systems in Southeast Asia

Southeast Asia (SEA) has experienced frequent floods and droughts, posing severe challenges for farmers, agricultural scientists and extension officers. Consequently, crop modelling has become imperative in developing agricultural production systems and making informed decisions at the field level. The Decision Support System for Agrotechnology Transfer (DSSAT) can be effectively utilised at both farm and regional levels to assess the influence of climate change on production across different spatial scales. Moreover, it supports planning adaptation strategies tailored to the needs of farmers. The one-week hands-on training workshop aims to enhance technical and scientific proficiency in crop simulation modelling and evaluate the effects of climate risks on agricultural production systems in Southeast Asian countries such as Cambodia, Lao PDR, Thailand and Vietnam. A total of 62 participants from the selected countries, including Singapore and Ethiopia, were joined in the training. Among them were 48 male and 24 female individuals, comprising researchers, students, scientists, academicians and extension officers. The participants predominantly acquired knowledge of crop simulation modelling techniques by utilising existing case examples and lecture materials from the DSSAT foundation. Furthermore, the training workshops establish research networks and collaborations among the participant countries, facilitating the exchange of scientific knowledge related to innovative farm management practices and fostering interactions between local agricultural communities and scientists.

Implementing Agile Methodologies in Data Warehouse Projects

Agile techniques have transformed project management and software development by stressing flexibility, collaboration, and customer-centricity. Data warehouse initiatives have traditionally used a waterfall methodology, which may delay, cost more, and misalign with business needs. Agile techniques are applied to data warehouse projects in this article, examining their pros and cons. The study starts with Agile fundamentals including iterative development, incremental delivery, and adaptive planning. It compares these concepts with the linear, sequential waterfall approach employed in data warehousing. Agile approaches like Scrum or Kanban may help data warehouse projects adapt to changing business demands and improve results. The report recommends creating cross-functional Agile teams with data administration, analytical, and development competence to execute Agile in data warehouses. Collaborative teams encourage communication and feedback loops. Sprints, stand-ups, and retrospectives help data warehousing teams make quick changes and meet business goals, according to the report.

Advancing urban climate adaptation through knowledge exchange: A case study of New York City

Cities are experiencing increasingly extreme and longer-lasting hazards due to climate change. In response, urban decision-makers use climate assessments to inform their adaptation programs. To effectively inform planning, climate assessments must be responsive to community priorities and align with information needs. However, there are few empirical studies evaluating the co-production and exchange of climate information within climate assessment processes. To address this gap, we evaluated the Climate Knowledge Exchange (CKE) piloted in 2020 by the Mayor's Office of Climate and Environmental Justice (then the Mayor's Office of Resiliency) in New York City. The CKE is an ongoing engagement process that asked: What are the research gaps and barriers to adaptation in New York City and how can we design inclusive approaches to knowledge exchange that advance equitable adaptation? To answer this question, we facilitated group discussions, distributed surveys, and reviewed adaptation plans to assess the state of climate knowledge. The findings indicate a need for contextually and culturally sensitive approaches to the co-development of actionable knowledge. Additionally, there is a need to reduce barriers to equitable adaptation and to advance the practice of climate-informed decision-making. Our findings advance understanding of the potential role of climate knowledge exchange in adaptation planning.

Heterogenous impact of background meteorological factors on the cooling effect of two types of typical urban parks: Evidence from Shanghai, China

The cooling effect of urban parks (PCE) is widely recognized as an effective way to improve the urban thermal environment. While the influence of various background meteorological factors (BMFs) on PCE has been increasingly documented, further understanding of these impacts, particularly across different types of urban parks, remains insufficient. Here, we selected two typical urban parks, fifteen with green space (PG) and fifteen with blue-green space (PB&G) in Shanghai, China for comparative studies. The impact of BMFs on PCE and the threshold value of efficiency (TVoE) of sampled urban parks under six different dates were quantified through descriptive statistics and correlation analysis. The results showed that: (1) Compared with PG, PB&G had a stronger cooling effect, and were stable under different background meteorological conditions (BMCs). (2) The BMFs enable significant impact on the PCE, both PG and PB&G showed better PCE under higher background air temperature (Ta). (3) The blue space ratio (RBS) of urban parks presented a stronger correlation with PCE than the green space ratio (RGS) under various BMCs, especially in BMCs of lower relative humidity (Rh); thus, the regulation of RBS should be firstly considered for better PCE. (4) The TVoE of PB&G had better fitting results and was also less affected by BMCs, PB&G with an area of 0.93 ha was encouraged for optimal PCE from a cost-benefit perspective in the study area. These findings are essential to decision-makers and can provide actionable knowledge for urban climate adaptation planning.

Effect of Data Integration Techniques on Operational Efficiency in Manufacturing Industries in Iran

Purpose: The aim of the study was to assess the effect of data integration techniques on operational efficiency in manufacturing industries in Iran. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that by seamlessly amalgamating data from disparate sources across production lines, supply chains, and customer feedback systems, manufacturers have been able to streamline processes, optimize resource allocation, and achieve significant cost savings. For instance, real-time data integration facilitates timely decision-making, allowing for adaptive production planning and inventory management. Furthermore, the integration of advanced analytics and machine learning algorithms has enabled predictive maintenance strategies, reducing downtime and enhancing overall equipment effectiveness (OEE). These technological advancements not only bolster operational efficiency but also foster innovation, as companies leverage integrated data insights to drive continuous improvement initiatives and meet evolving consumer demands. Implications to Theory, Practice and Policy: Resource-based view (RBV), technology acceptance model and dynamic capabilities theory may be used to anchor future studies on assessing the effect of data integration techniques on operational efficiency in manufacturing industries in Iran. Manufacturing firms should prioritize strategic implementation plans for data integration technologies to ensure that investments in IoT, AI, ETL, data warehousing, data virtualization, and APIs are aligned with their overall business objectives. Policymakers should provide incentives and support for the adoption of advanced data integration technologies in the manufacturing sector.

Integrating aquatic species, assemblage, and habitat climate change vulnerabilities into a watershed-scale decision support framework

Climate change is increasingly recognized as a serious threat to ecological systems, particularly freshwater systems. As a result, climate adaptation planning is more common in natural resource management. Because conservation resources are limited, decision support tools can help managers prioritize actions. We created the Species and Habitat-based Ecological Decision Support tool (wtrSHEDS) for conservation managers by integrating two distinct indices: one biologically based on aquatic watershed-scale species assemblages and the other a habitat climate change vulnerability index. To do this, we evaluated 60 crayfish and fish species in West Virginia, USA, using the NatureServe Climate Change Vulnerability Index under an A1B emissions scenario. The species vulnerability assessment results indicated that most species we assessed are vulnerable to climate change. Four species of fish and two species of crayfish had extremely high vulnerability due to their dependence on a specific hydrological cycle, sensitivity to barriers, and reproductive dependence on a thermal niche. Aggregating species at the watershed scale (8-digit hydrological unit code [HUC]) using an adapted weighted sum indicated which assemblages were the most and least vulnerable to climate change. Secondly, we created a unique habitat vulnerability index using the established Northeast Association of Fish and Wildlife Agencies habitat vulnerability index and an index of land cover vulnerability from the Forecast Scenario model’s land cover change projections under the A1B emissions scenario to incorporate potential synergistic impacts of land use. Land cover projections were reclassified based on the assumption that developed land would have a higher potential to interact with climate change than forested lands synergistically. We combined the two habitat indices at the watershed scale (HUC 8) and performed a Hot Spot Analysis to 1) combine the assemblage and habitat vulnerability indices and 2) identify watersheds of conservation priority. This assessment methodology illustrates a means of identifying priority conservation areas in West Virginia that utilize pre-existing data, can be modified to suit management needs, and, therefore, one that managers across regions can readily apply to their system.

Conserving biodiversity and managing water resources in the Akagera River catchment, Eastern Rwanda: local engagement and knowledge cocreation through the adaptive planning process

Conserving biodiversity and managing water resources in the Akagera River catchment, Eastern Rwanda: local engagement and knowledge cocreation through the adaptive planning process

Towards greener city logistics: an application of agile routing algorithms to optimize the distribution of micro-hubs in Barcelona

The COVID-19 pandemic accelerated the shift towards online shopping, reshaping consumer habits and intensifying the impact on urban freight distribution. This disruption exacerbated traffic congestion and parking shortages in cities, underscoring the need for sustainable distribution models. The European Union's common transport policy advocates for innovative UFD approaches that promote intermodal transportation, reduce traffic, and optimize cargo loads. Our study addresses these challenges by proposing an agile routing algorithm for an alternative UFD model in Barcelona. This model suggests strategically located micro-hubs selected from a set of railway facilities, markets, shopping centers, district buildings, pickup points, post offices, and parking lots (1057 points in total). It also promotes intermodality through cargo bikes and electric vans. The study has two main objectives: (i) to identify a network of intermodal micro-hubs for the efficient delivery of parcels in Barcelona and (ii) to develop an agile routing algorithm to optimize their location. The algorithm generates adaptive distribution plans considering micro-hub operating costs and vehicle routing costs, and using heuristic and machine learning methods enhanced by parallelization techniques. It swiftly produces high-quality routing plans based on transportation infrastructure, transportation modes, and delivery locations. The algorithm adapts dynamically and employs multi-objective techniques to establish the Pareto frontier for each plan. Real-world testing in Barcelona, using actual data has shown promising results, providing potential scenarios to reduce CO2 emissions and improve delivery times. As such, this research offers an innovative and sustainable approach to UFD, that will contribute significantly to a greener future for cities.

Enhancing climate adaptation: Integrating place-based risk perceptions and coastalscape values using Q+PPGIS

Effective climate change adaptation planning requires evaluating the interplay of physical landscape characteristics and community perceptions of places. Geographic information system (GIS)-based approaches to measuring environmental values can identify locations for planning prioritization. But they seldom are used to consider spatial differences in socio-ecological worldview. This study aims to identify how place-based risk perceptions and landscape values can inform climate change adaptation using a Q+PPGIS method. We integrated mapped landscape values and climate risks (from 39 PPGIS participants) with elicited discourses (for 28 Q-method participants) to develop a novel land classification approach (reflexive Q+PPGIS). The results demonstrate significant differences between wilderness as a discourse and perceived, and the physical features associated with mapped wild areas. Similar differences in discourse and spatial patterns are observed for climate risks. For example, participants’ mapped areas of bushfire risk do not align with agencies’ identified risk areas, their jurisdictions, and capacities to take action. This disconnect presents a challenge to adaptation. Local governments can use this new method to show constituents multiple and often competing community demands for action, enabling honest conversations about feasible actions, responsibilities, and resource allocation.

Analisis Framing Pemberitaan Pemberantasan Narkoba dan Rencana Strategi Humas Badan Narkotika Nasional

This study discusses the role of public relations in planning communication strategies to handle news related to drug trafficking. Based on framing analysis from Antara and Detik.com media, it was found that these two media outlets highlighted drug trafficking as a serious threat, with news that focused on law enforcement actions and their social impact. Related to public relations strategy planning, the Ronald D. Smith model is used which includes four phases: formative research, strategy formulation, tactical implementation, and evaluation. The core of this study emphasizes the importance of structured and adaptive public relations strategic planning in dealing with drug trafficking issues, therefore it is necessary to increase cooperation with the media, adequate resource allocation, and the use of technology to reach a wider audience. Thus, it is hoped that drug eradication efforts can run more effectively and efficiently and get full support

Sensitivity of Local Climate Zones and Urban Functional Zones to Multi-Scenario Surface Urban Heat Islands

Local climate zones (LCZs) and urban functional zones (UFZs) can intricately depict the multidimensional spatial elements of cities, offering a comprehensive perspective for understanding the surface urban heat island (SUHI) effect. In this study, we retrieved two types of land surface temperature (LST) data and constructed 12 SUHI scenarios over the Guangdong–Hong Kong–Macao Greater Bay Area Central region using six SUHI identification methods. It compared the SUHI sensitivity differences among different types of LCZ and UFZ to analyze the global and local sensitivity differences of influencing factors in the 12 SUHI scenarios by utilizing the spatial gradient boosting trees, geographically weighted regression, and the coefficient of variation model. Results showed the following: (1) The sensitivity of different LCZ and UFZ types to multi-scenario SUHI was significantly affected by differences in SUHI identification methods and non-urban references. (2) In the morning, the shading effect of building clusters reduced the surface urban heat island intensity (SUHII) of some built environment types (such as LCZ 1 (compact high-rise zone) to LCZ 5 (open midrise zone)). The SUHIIs of LCZ E (bare rock or paved zone) and LCZ 10 (industry zone) were 4.22 °C and 3.87 °C, respectively, and both are classified as highly sensitive to SUHI. (3) The sensitivity of SUHI influencing factors exhibited regional variability, with importance differences in the sensitivity of importance for factors such as the impervious surface ratio, elevation, average building height, vegetation coverage, and average building volume between LCZs and UFZs. Amongst the 12 SUHI scenarios, an average of 87.43% and 89.97% of areas in LCZs and UFZs, respectively, were found to have low spatial sensitivity types. Overall, this study helps urban planners and managers gain a more comprehensive understanding of the complexity of the SUHI effect in high-density cities, providing a scientific basis for future urban climate adaptability planning.

Tackling the modifiable areal unit problem: Enhancing urban sustainability through improved land surface temperature and its influencing factors analysis

Exploring the modifiable areal unit problem (MAUP) in land surface temperature (LST) and its influencing factors is crucial for understanding LST variation patterns and quantifying the factors' impact. Neglecting the MAUP could lead to an incomplete understanding of LST changes and their driving mechanisms. This study used optimal parameters-based geographical detector and gradient boosting regressor models to investigate the MAUP in LST and its influencing factors. The analysis covered 87 cities across seven climate zones in China, examining MAUP in 12 spatial scales to discern the scale and zoning effects on LST and its influencing factors. The research findings were as follows: (1) The sensitivity of LST influencing factors to spatial scales exhibited both spatial and temporal heterogeneity. Significant differences in the q-values of LST influencing factors were observed across various climate zones and periods (daytime and nighttime), with human factors, particularly those related to residents' work, buildings, life, and rest, showing higher spatial scale dependency than natural factors. (2) Zoning effects significantly impacted the q-values of LST influencing factors and were closely linked to the discretization methods and quantities used, which could alter the trends of these q-values. (3) Across the 12 spatial scales, more than 67.34 % of LST influencing factor interaction types were classified as bi-variable enhancement types. The q-values for LST influencing factor interactions were higher and more stable than those of single factors. LST influencing factor interactions in transitional climate zones exhibited high sensitivity to spatial scales. This research enhances our understanding of LST variations, providing valuable insights for urban climate adaptability planning and the development of climate-resilient cities.

Muddling from the middle out: Multi-scalar governance for place-based and adaptive sustainability in Texas

Given the eclectic and localized nature of environmental risks, planning for sustainability requires solutions that integrate local knowledge and systems while acknowledging the need for continuous re-evaluation. Social-ecological complexity, increasing climate volatility and uncertainty, and rapid technological innovation underscore the need for flexible and adaptive planning. Thus, rules should not be universally applied but should instead be place-based and adaptive. To demonstrate these key concepts, we present a case study of water planning in Texas, whose rapid growth and extreme weather make it a bellwether example. We review historic use and compare the 2002, 2007, 2012, 2017 and 2022 Texas State Water Plans to examine how planning outcomes evolve across time and space. Though imperfect, water planning in Texas is a concrete example of place-based and adaptive sustainability. Urban regions throughout the state exhibit a diversity of strategies that, through the repeated 5-year cycles, are ever responding to evolving trends and emerging technologies. Regional planning institutions play a crucial role, constituting an important soft infrastructure that links state capacity and processes with local agents. As opposed to “top-down” or “bottom-up”, we frame this governance as “middle-out” and discuss how such a structure might extend beyond the water sector.

Scenario planning for climate adaptation and management: a high-level synthesis and standardization of methodology

Scenario planning is a tool used to explore a set of plausible futures shaped by specific trajectories. When applied in participatory contexts, it is known as participatory scenario planning (PSP), which has grown in its usage for planning, policy, and decision-making within the context of climate change. There has been no high-level synthesis of systematic reviews covering the overall state and direction of PSP for climate adaptation and management. We draw from four systematic reviews on PSP published between 2015 and 2021 to substantiate the credibility of the process and identify a set of standard practices to make PSP a more accessible and usable tool for not only researchers, but policymakers, practitioners, and other end users who may benefit from PSP. We summarize and synthesize the range of PSP processes and characteristics, highlighting four common trends that provoke additional inquiry: PSP’s contribution to social learning and bias, the varying use of quantitative information in scenario development, issues related to carrying out monitoring and evaluation, and the varying completion of practices recommended by established PSP literature. We propose four processes as integral to maximizing PSP’s usability for end users and recommend these areas for further study: identifying social imbalances throughout the PSP process, recognizing bias as inherent to PSP, explicitly addressing, and incorporating uncertainty, and allocating resources for monitoring and evaluation.

Gender vulnerability and coping strategies to changing provisioning ecosystem services in Bongo and Kassena-Nankana West districts in the Upper East Region of Ghana

ABSTRACT Ecosystems provide a wide variety of life-sustaining services but are currently facing severe degradation due to changing land use and cover. Women are presumed to be more affected by declines in provisioning ecosystem services (PES). These claims have not been empirically proven across all contexts and have been contested by recent studies. Few studies in Ghana have attempted to examine this gendered environmental change phenomenon. Underpinned by the vulnerability theory, this paper employed an eclectic methodological approach to examine gender differences in vulnerability and coping with changing PES in Ghana. The findings reveal that both males and females depend highly on agricultural and woodland ecosystems for their livelihood needs. The deterioration in the total areas of the major ecosystems has resulted in significant declines in vital PES such as wild edible fruits and vegetables, medicinal plants and building materials for both men and women over the past decade. The study further reveals that the decreases in fuelwood supply affect women more than men because the former group mostly cooks food in their households, using fuelwood. As adaptation mechanisms, male farmers mostly planted trees on their farms to reclaim unfertile land and conserve forests, while female farmers engage in fruits and vegetable trade in the markets, as well as used non-indigenous spices to enhance the taste of food. Both males and females have also resorted to relying on orthodox medicines contrary to the past. To increase ecosystem resilience, the mainstreaming of ecosystem integrity adaptation practices into national adaptation plans is paramount.