Hasil untuk "Geography"

C. Alvares, J. Stape, P. Sentelhas et al.

Koppen's climate classification remains the most widely used system by geographical and climatological societies across the world, with well recognized simple rules and climate symbol letters. In Brazil, climatology has been studied for more than 140 years, and among the many proposed methods Koppen 0 s system remains as the most utilized. Considering Koppen's climate classification importance for Brazil (geography, biology, ecology, meteorology, hydrology, agronomy, forestry and environmental sciences), we developed a geographical information system to identify Koppen's climate types based on monthly temperature and rainfall data from 2,950 weather stations. Temperature maps were spatially described using multivariate equations that took into account the geographical coordinates and altitude; and the map resolution (100 m) was similar to the digital elevation model derived from Shuttle Radar Topography Mission. Patterns of rainfall were interpolated using kriging, with the same resolution of temperature maps. The final climate map obtained for Brazil (851,487,700 ha) has a high spatial resolution (1 ha) which allows to observe the climatic variations at the landscape level. The results are presented as maps, graphs, diagrams and tables, allowing users to interpret the occurrence of climate types in Brazil. The zones and climate types are referenced to the most important mountains, plateaus and depressions, geographical landmarks, rivers and watersheds and major cities across the country making the information accessible to all levels of users. The climate map not only showed that the A, B and C zones represent approximately 81%, 5% and 14% of the country but also allowed the identification of Koppen's climates types never reported before in Brazil.

David Harvey

C. Katz

A. MacCall

Widiyanto Widiyanto, Lestari Eny, Rusdiyana Eksa et al.

The Climate Village Program (ProKlim) aims to strengthen community participation in local climate mitigation and adaptation. Although several areas in Surakarta have reached the Main Class category, sustaining community motivation remains a challenge. This study analyzes the sustainability of ProKlim by examining social, economic, and environmental factors influencing long-term engagement. Using a qualitative case study approach, data were collected through in-depth interviews, FGDs, observations, and documentation. The findings show that strong social capital and local leadership support sustainability, while fluctuating participation, dependence on external incentives, and limited cadre regeneration hinder continuity. Economic activities exist but remain small-scale. The results imply that continuous mentoring, strengthened community-based economic initiatives, and structured monitoring are essential to ensure sustained ProKlim implementation beyond assessment cycle. The result imply that continuous mentoring, strengthened community-base economic initiatives, and structured monitoring to maintain consistent ProKlim implementation beyond competition cycles. Strengthening these aspects is essential for ensuring the ling-term sustainability of Main Class ProKlim as a community-driven climate resilience initiative.

Elvis Frimpong Manso, Alfred Arthur, Joseph Osafo Eduah et al.

Despite the differences in soil and fertilizer properties affecting fertilizer effectiveness, farmers often use nationwide blanket formulations, which may not optimize cocoa yield. Previous trials have shown that fertilizer application outcomes vary by soil type, prompting recommendations for site-specific fertilizer formulations. Nonetheless, the complexity of creating these models leaves farmers relying on available blanket fertilizers instead. To enable farmers to select fertilizer types that will best suit their soils, the effects of soil properties and fertilizer types on the solubility, availability of macronutrients, and pH in two cocoa soils were investigated. Five kilograms of ferralsol and acrisol were prepared in nursery bags, with five different fertilizers (A, B, C, D, and E) applied at rates of 375, 500, and 625 kg·ha−1 were set in factorial experiment laid in completely randomized design with four replicates each. Following a 3-week incubation, nutrient analysis was conducted weekly. Water solubility was assessed by weighing 1, 2, and 3 g of each fertilizer in 200 mL of distilled water and shaken for 3 hours. Results indicate that lower solute-to-solvent ratios decreased NPK, Ca, and Mg solubility. Fertilizer A increased soil pH from 6.81 to 7.45 in ferralsol and from 5.78 to 7.50 in acrisol. The different soils showed different release trends though the same fertilizers were applied. Available phosphorus rose from 4.76 to 166.69 mg·kg−1 in ferralsol and from 4.32 to 170.00 mg·kg−1 in acrisol, while total nitrogen rose from 0.22% to 0.30% in ferralsol and from 0.16% to 0.20% in acrisol. The findings highlight that soil properties influence fertilizer solubility and nutrient availability in cocoa soils.

Ruby Bisht, Amit Kumar Uniyal, Amar Johri et al.

Abstract The research on work-life balance of teachers highlights the significant challenges faced by educators in balancing their professional and personal lives. The study emphasizes the evolving role of teachers, the impact of technology, and the increasing demands placed on them. It also underscores the importance of achieving a healthy work-life balance to reduce stress and improve job satisfaction. This study critically examines research papers and articles related to work-life balance of teachers published between 2014–2024 in the Scopus database. Bibliometric analysis was done with the help of a biblioshiny package of Rstusio and VoS viewer. Out of 554 articles, 112 were located after restricting the search to the English language and publications related to social science, psychology, business, management, and economics for the selected time (2014–2024). The research on the work-life balance of teachers has seen significant growth, especially during the COVID-19 pandemic. The findings highlight that the USA in countries, Fokkens-Bruinsma, M. in authors and Frontiers in Psychology in sources have the highest contribution of articles in related field. Key topics include “human,” “teaching,” “work-life balance,” “questionnaire,” and “education. This study provides a comprehensive overview of the research trends, key contributors, and important topics in the field of work-life balance of teachers. Moreover, it also highlights the growing interest in this area and the need for further research to address the challenges faced by educators. The findings suggest that implementing work-life policies and initiatives tailored to the teaching profession can help address these challenges and promote better well-being among teachers. Overall, the study calls for a greater focus on supporting teachers to ensure they can effectively manage their work and personal responsibilities.

Noémie Letellier, Caitlin G. Jones-Ngo, Michael W. Cheung et al.

Background: As the health burden attributable to wildfire activity increases under climate change, it is crucial to determine which subgroups face heightened vulnerability to wildfire smoke. Marginalized communities may experience disproportionate risk from overlapping individual and community vulnerability factors. We leverage recent developments in machine learning methods for high-dimensional settings to construct detailed profiles of California communities disproportionately impacted by wildfire smoke across 27 potential effect modifiers. Methods: We used daily 2006–2019 data on hospital admissions and emergency department (ED) visits for cardio-respiratory diseases in California. We applied a time-stratified case-crossover study design to analyze the effect of wildfire-specific fine particulate matter (PM2.5) on cardio-respiratory diseases. Then, we investigated heterogeneous effects using a generalized random forest approach, which can handle a large set of individual-level (age, sex, race/ethnicity) and area-level (e.g., poverty level, racial/ethnic segregation) factors to construct vulnerability profiles for each Air Basin, representing areas with similar meteorological and geographic conditions. Results: A 10 µg/m3 increase in wildfire PM2.5 concentration (2-day moving average) was associated with an increased risk of hospital admissions and ED visits related to respiratory diseases (OR = 1.014, 95 % confidence interval = 1.012–1.016). No association was found for cardiovascular diseases. Associations between exposure to wildfire PM2.5 and respiratory diseases varied strongly by individual- (age, sex, race/ethnicity) and area-level factors (such as A/C prevalence, Black/White dissimilarity index). The importance of these effect modifiers, and vulnerability profiles, changed across Air Basins. Conclusions: Machine learning can characterize the complex heterogeneity in wildfire smoke-related health impacts.

Pietro Capovilla

We present an explicit construction of closed oriented aspherical smooth 4-manifolds with $χ= σ= n$ for every positive integer $n$. This proves a conjecture of Edmonds by providing a closed oriented aspherical 4-manifold with Euler characteristic 1, and it shows that the real analogue of the Bogomolov-Miyaoka-Yau inequality fails for aspherical 4-manifolds. By the Hitchin-Thorpe inequality, these manifolds do not admit Einstein metrics. As a further consequence of our construction, we show that every closed aspherical 3-manifold with amenable fundamental group is virtually the $π_1$-injective boundary of an aspherical 4-manifold with vanishing Euler characteristic and vanishing simplicial volume, thereby answering questions of Edmonds and of Löh-Moraschini-Raptis up to finite covers.

Jon Wang, Meng Lu

The use of geospatially dependent information, which has been stipulated as a law in geography, to model geographic patterns forms the cornerstone of geostatistics, and has been inherited in many data science based techniques as well, such as statistical learning algorithms. Still, we observe hesitations in interpreting geographic dependency scientifically as a property in geography, since interpretations of such dependency are subject to model choice with different hypotheses of trends and stationarity. Rather than questioning what can be considered as trends or why it is non-stationary, in this work, we share and consolidate a view that the properties of geographic dependency, being it trending or stationary, are essentially variations can be explained further by unobserved or unknown predictors, and not intrinsic to geographic space. Particularly, geoinformation dependency properties are in fact a projection of high dimensional feature space formed by all potential predictors into the lower dimension of geographic space, where geographic coordinates are equivalent to other predictors for modelling geographic patterns. This work brings together different aspects of geographic dependency, including similarity and heterogeneity, under a coherent framework, and aligns with the understanding of modelling in high dimensional feature space with different modelling concept including the classical geostatistics, Gaussian Process Regression and popular data science based spatial modelling techniques.

N. Vavilov

Luwei Zeng, T. Donna Chen, John S. Miller et al.

Due to accelerated sea level rise and climate change, the transportation system is increasingly affected by recurrent flooding coastal regions, yet the cumulative travel disruption effects are not well understood. In Part 1 of this study, the accessibility impacts of recurrent flooding on the auto mode were examined. In this paper (Part 2 of the study), the impact of recurrent flooding on transit service accessibility was quantified with the aid of spatially and temporally disaggregated crowdsourced flood incident data from WAZE. A fixed route transit network is built for five time of day periods for 710 traffic analysis zones (TAZs), to capture the spatial and temporal variation of transit accessibility reduction due to recurrent flooding. Results show that the greatest transit accessibility reduction occurs during the morning peak hour, with individual TAZ transit accessibility reduction ranging from 0 to 88.2% for work trips (with an average of 6.4%) and ranging from 0 to 99.9% for non-work trips (with an average of 3.7%). Furthermore, social vulnerability analysis indicates that TAZs with a greater share of people with higher vulnerability in transportation and socioeconomic status are more likely to experience recurrent flooding-induced transit accessibility reduction. Results from this study reinforce the notion that transportation impacts under recurrent flooding are not uniformly experienced throughout a region, and this spatial and temporal variation translates to different impacts borne by various population groups. Disaggregate impact analysis like this study can support transportation engineers and planners to prioritize resources to ensure equitable transit accessibility under increasing climate disruptions.

Yichen Wang, Hao Yin, Yifan Yang et al.

Freight truck-related crashes pose significant challenges, leading to substantial economic losses, injuries, and fatalities, with pronounced spatial disparities across different regions. This study adopts a transport geography perspective to examine spatial justice concerns by employing deep counterfactual inference models to analyze how socioeconomic disparities, road infrastructure, and environmental conditions influence the geographical distribution and severity of freight truck crashes. By integrating road network datasets, socioeconomic attributes, and crash records from the Los Angeles metropolitan area, this research provides a nuanced spatial analysis of how different communities are disproportionately impacted. The results reveal significant spatial disparities in crash severity across areas with varying population densities, income levels, and minority populations, highlighting the pivotal role of infrastructural and environmental improvements in mitigating these disparities. The findings offer insights into targeted, location-specific policy interventions, suggesting enhancements in road infrastructure, lighting, and traffic control systems, particularly in low-income and minority-concentrated areas. This research contributes to the literature on transport geography and spatial equity by providing data-driven insights into effective measures for reducing spatial injustices associated with freight truck-related crashes.

Jiahao Yuan, Zixiang Di, Shangzixin Zhao et al.

Large language models (LLMs) face challenges in aligning with diverse cultural values despite their remarkable performance in generation, which stems from inherent monocultural biases and difficulties in capturing nuanced cultural semantics. Existing methods struggle to adapt to unknown culture after fine-tuning. Inspired by cultural geography across five continents, we propose Cultural Palette, a multi-agent framework that redefines cultural alignment as an adaptive "color-blending" process for country-specific adaptation. Our approach harnesses cultural geography across five continents through three key steps: First, we synthesize the Pentachromatic Cultural Palette Dataset using GPT-4o, refining continental-level dialogues with Hofstede's cultural dimensions to establish foundational cultural representations. Second, five continent-level alignment agents form specialized cultural communities that generate region-specific draft responses. Third, a Meta Agent employs Cultural MoErges to dynamically blend these cultural "colors" through attention-gated parameter merging, akin to mixing pigments on a palette, resolving conflicts while preserving cultural nuances to produce the final culturally-aligned response. Extensive experiments across various countries demonstrate that \textit{Cultural Palette} surpasses existing baselines in cultural alignment.

S. Hennein

Aurora Ranting Salsabilla, LGLK. Dewi, Ni Putu Eka Mahadewi

Green marketing mix is an important field of study for companies because it provides opportunities for competitive advantage that can influence consumer purchasing decisions. This research aims to determine the effect of green marketing mix on purchasing decisions for Beach Voluntrip product at PT. Gemilang Media Wisatama (Travelxism) partially and simultaneously. This research uses quantitative research methods and data collection techniques including observation, documentation, interviews, questionnaires, and literature study. Data analysis techniques in this research include research instrument tests, classical assumption tests, descriptive statistical analysis, multiple linear regression analysis, and hypothesis testing. The sampling technique in this research uses probability sampling technique and saturation sampling by distributing questionnaires to domestic tourists aged ? 17 years who had purchased Beach Voluntrip product at Travelxism. The results state that green marketing mix variable has a significant and positive effect on the purchasing decision variable partially and simultaneously. Based on the research results, Travelxism is advised to intensify promotions targeting tourists with an age range of 17-25 years on social media, diversify eco-friendly tourism products and provide competitive prices so they can compete with alternative tourism products and other conventional tourism products.

Amineh Ghorbani, Saba Siddiki, Giangiacomo Bravo

Luca F. Di Cerbo, Rita Pardini

We discuss an approach towards the Hopf problem for aspherical smooth projective varieties recently proposed by Liu, Maxim, and Wang in [LMW21]. In complex dimension two, we point out that this circle of ideas suggests an intriguing conjecture regarding the geography of aspherical surfaces of general type.

P. Krugman

Dani Rodrik, Dani Rodrik, Dani Rodrik et al.

We estimate the respective contributions of institutions, geography, and trade in determining cross-country income levels using recently developed instruments for institutions and trade. Our results indicate that the quality of institutions 'trumps' everything else. Controlling for institutions, geography have at best weak direct effects on incomes, although it has a strong indirect effect through institutions. Similarly, controlling for institutions, trade has a negative, albeit, insignificant direct effect on income, although trade too has a positive effect on institutional quality. We relate our results to recent literature, and where differences exist, trace their origins to choices on samples, specification, and instrumentation.