Impact of Socioeconomic Factors and farm Size on Wheat Productivity: A Case Study of District Peshawar, Pakistan

Ali, Sajad; Khatak, Naeem Ur Rehman; Ahmad, Iftikhar; Ja, Khan; Azra, Azra

doi:10.17582/journal.sja/2020/36.4.1174.1179

Cited by 2 publications

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“…Additionally, Figures 7-9 show that LST has had a negative impact on the NDVI (Sun and Kafatos, 2007;Boqer and Science, 2009). Parts of the previously vegetated terrain are being transformed into urban areas as a result of the fast suburbanization happening in the study area (Malik and Ali, 2015;Ali K. et al, 2019). This growing urbanization, along with other factors, may significantly contribute to local climate variability, aggravating large-scale CC, as has been observed in other nations (Raza and Ijaz, 2009;Yang et al, 2013;Kabiri et al, 2015).…”

Section: Discussionmentioning

confidence: 95%

Evaluation of climate change impact on plants and hydrology

Shah,

Khan,

Muhammad

et al. 2024

Front. Environ. Sci.

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Climate change (CC) is the menace of the hour impacting every facet of human existence. Regional CC and its impact studies are crucial in that they contribute to global change. The current study aims to investigate the prevalence of CC in Charsadda, Pakistan and its impact on vegetation and hydrology of the region to understand microclimate variability contribution to global CC. Utilizing local climate data for 20 years (2001–2020), Modified Mann-Kendall and Sen’s Slope statistics were employed to determine monthly and seasonal trends in climate variables. Significant changing climate variables were regressed on Moderate resolution Imaging Spectroradiometer (MODIS) satellite dataset viz. normalized difference vegetation index (NDVI). Due to the prominent climate factor impacting vegetation, NDVI was further correlated to MODIS land surface temperature (LST). Floods being the conspicuous climate calamity were mapped for 2005 and 2010 using satellites Landsat 5 and 7 dataset viz. normalized difference water index (NDWI) with flood risk assessment by watershed delineation. The findings revealed significant (p < 0.05) variability in climate variables (average monthly and summer maximum temperature, and average monthly and summer precipitation) that are driving CC and impacting vegetation and hydrology in the region. Temperature and solar radiation affect NDVI adversely while precipitation and relative humidity has positive impact on vegetation. NDVI varied greatly spatiotemporally, often increasing but worsening in some areas (Shabqadar, Abazai, Palai and Charsadda city with NDVI = 0.1–0.3) of the study region as a result of extreme weather events. Temporally, NDVI improved with an overall positive trend with a stage (2007–2016) of noticeable zigzag fluctuation. Spatial grids with higher LST (>40°C) were either devoid of or with sparse NDVI (<0.3) presenting global warming as peril to vegetation. NDWI maps (2005, 2010 floods) indicate that after floods wreaked havoc on the region altering the vegetation pattern revealing heavy irregular precipitation as the next to temperature in jeopardizing vegetation of the region. Lower elevation regions along the Swat and Kabul Rivers with a greater risk of flooding were identified by watershed delineation. The study suggests that local governments and stakeholders implement CC mitigation strategies and plans for vegetation restoration, flood alerts with post-flood management for regional sustainable development.

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Section: Discussionmentioning

confidence: 95%

Evaluation of climate change impact on plants and hydrology

Shah,

Khan,

Muhammad

et al. 2024

Front. Environ. Sci.

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“…Researchers have comprehended that vehicle fuel consumption is highly correlated by the traffic patterns, speed of the car, weather conditions, road-graded characteristics, and inherent properties or models of the deliberated vehicle [4,5]. Prominently, the demand for nonrenewable energy is also expected to increase by 36.5% in the next 5-year period from 2019-2024; however, this growing demand is particularly associated with the petroleum products of the automobile industry [6,7]. Therefore, Sustainability 2022, 14, 64 2 of 17 researchers have been considering fuel economy to develop an interaction between renewable and nonrenewable energy sources for environmental sustainability [8,9].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis and Statistical Optimization of Fuel Economy for Sustainable Vehicle Routings

Alsaadi

2021

Sustainability

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In this 21st century, there has been an increase in the usage of renewable products for the economic drifting of vehicle transportations systems. Furthermore, due to recent trends in climate change, researchers have started focusing on statistical optimization techniques for sustainable vehicle routings. However, until now, a major gap has been noticed in the multidomain statistical analysis for optimizing the parametric levels of the vehicle fuel economy. Therefore, in this research work, two widely utilized cars (Toyota and GMC Yukon) are considered on a particular route of Jeddah for the collection of the fuel economy data under the realistic conditions of air conditioner temperature, traffic patterns, and tire pressure. The outcomes of the factorial design of the experiment highlight that the fuel economy is optimal under the low air conditioner temperature, light traffic patterns, and 34 PSI tire pressure. Three replications of the fuel economy have been considered, and the statistical significance of the correlated variables has been justified by implementing the analysis of variance (ANOVA) approach on the various levels of fuel economy. During the analysis, the statistical hypothesis for random exogenous factors has been developed by incorporating a multivariate regression model. The outcomes highlight that both air conditioner temperature and traffic patterns in Jeddah have a significant negative effect on fuel economy. Results also depict that the effect of air conditioner temperature, traffic patterns, and tire pressure is substantially higher for heavy-engine automobiles such as the GMC Yukon compared to light-engine cars (Toyota Corolla). Furthermore, a normality test has also been considered to validate the outcomes of the proposed model. Therefore, it is highly recommended to utilize the proposed methodology in optimizing the trends of fuel economy for sustainable vehicle routings. Based on the findings of multidomain statistical analysis, it is also highly recommended the utilization of the Toyota Corolla car model for investigating the correlation of external undeniable factors (braking frequency, metrological conditions, etc.) with the trends of vehicle fuel economy.

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Impact of Socioeconomic Factors and farm Size on Wheat Productivity: A Case Study of District Peshawar, Pakistan

Cited by 2 publications

References 0 publications

Evaluation of climate change impact on plants and hydrology

Evaluation of climate change impact on plants and hydrology

Comparative Analysis and Statistical Optimization of Fuel Economy for Sustainable Vehicle Routings

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