scholarly journals Decoupling forest characteristics and background conditions to explain urban-rural variations of multiple microclimate regulation from urban trees

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5450 ◽  
Author(s):  
Wenjie Wang ◽  
Bo Zhang ◽  
Lu Xiao ◽  
Wei Zhou ◽  
Huimei Wang ◽  
...  
Keyword(s):  
Light Intensity ◽  
Explanatory Power ◽  
Weather Conditions ◽  
Tree Density ◽  
Urban Trees ◽  
Lower Percentage ◽  
Air Cooling ◽  
Rapid Urbanization ◽  
Unit Distance ◽  
Urban Rural

Background Rapid urbanization in semi-arid regions necessitates greater cooling, humidifying, and shading services from urban trees, but maximizing these services requires an exact understanding of their association with forest characteristics and background street and weather conditions. Methods Here, horizontal and vertical air cooling, soil cooling, shading, and humidifying effects were measured for 605 trees from 152 plots in Changchun. Additionally, weather conditions (Tair, relative humidity, and light intensity), forest characteristics (tree height, diameter at breast height (DBH), under-branch height, canopy size, tree density, and taxonomic family of trees) and background conditions (percentage of building, road, green space, water, and building height, building distance to measured trees) were determined for three urban-rural gradients for ring road development, urban settlement history, and forest types. Multiple analysis of variance and regression analysis were used to find the urban-rural changes, while redundancy ordination and variation partitioning were used for decoupling the complex associations among microclimate regulations, forest characteristics, background street and weather conditions. Results Our results show that horizontal cooling and humidifying differences between canopy shade and full sunshine were <4.5 °C and <9.4%, respectively; while vertical canopy cooling was 1.4 °C, and soil cooling was observed in most cases (peak at 1.4 °C). Pooled urban-rural data analysis showed non-monological changes in all microclimate-regulating parameters, except for a linear increase in light interception by the canopy (r2 = 0.45) from urban center to rural regions. Together with the microclimate regulating trends, linear increases were observed in tree density, Salicaceae percentage, Tair, light intensity outside forests, tree distance to surrounding buildings, and greenspace percentage. Redundancy ordination demonstrated that weather differences were mainly responsible for the microclimate regulation variation we observed (unique explanatory power, 65.4%), as well as background conditions (12.1%), and forest characteristics (7.7%). Discussion In general, horizontal cooling, shading, and humidifying effects were stronger in dry, hot, and sunny weather. The effects were stronger in areas with more buildings of relatively lower height, a higher abundance of Ulmaceae, and a lower percentage of Leguminosae and Betulaceae. Larger trees were usually associated with a larger cooling area (a smaller difference per one unit distance from the measured tree). Given uncontrollable weather conditions, our findings highlighted street canyon and forest characteristics that are important in urban microclimate regulation. This paper provides a management strategy for maximizing microclimate regulation using trees, and methodologically supports the uncoupling of the complex association of microclimate regulations in fast urbanization regions.

scholarly journals Prediction of Pest Insect Appearance Using Sensors and Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4846
Author(s):  
Dušan Marković ◽  
Dejan Vujičić ◽  
Snežana Tanasković ◽  
Borislav Đorđević ◽  
Siniša Ranđić ◽  
...  
Keyword(s):  
Machine Learning ◽  
Relative Humidity ◽  
Weather Conditions ◽  
Daily Basis ◽  
Machine Learning Algorithms ◽  
Lower Percentage ◽  
Timely Manner ◽  
Proposed Model ◽  
Set Up ◽  
Accuracy Of Prediction

The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect’s appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance of some pests, such as Helicoverpa armigera. This paper presents a model of machine learning that can predict the appearance of insects during a season on a daily basis, taking into account the air temperature and relative humidity. Several machine learning algorithms for classification were applied and their accuracy for the prediction of insect occurrence was presented (up to 76.5%). Since the data used for testing were given in chronological order according to the days when the measurement was performed, the existing model was expanded to take into account the periods of three and five days. The extended method showed better accuracy of prediction and a lower percentage of false detections. In the case of a period of five days, the accuracy of the affected detections was 86.3%, while the percentage of false detections was 11%. The proposed model of machine learning can help farmers to detect the occurrence of pests and save the time and resources needed to check the fields.

scholarly journals Spatial Disparities of COVID-19 Cases and Fatalities in United States Counties

2021 ◽  
Vol 18 (16) ◽  
pp. 8259
Author(s):  
Sarah L. Jackson ◽  
Sahar Derakhshan ◽  
Leah Blackwood ◽  
Logan Lee ◽  
Qian Huang ◽  
...  
Keyword(s):  
United States ◽  
Great Plains ◽  
Explanatory Power ◽  
Temporal Trends ◽  
The United States ◽  
First Year ◽  
Significant Case ◽  
Urban Rural ◽  
Spatial And Temporal Trends ◽  
Mitigation Policies

This paper examines the spatial and temporal trends in county-level COVID-19 cases and fatalities in the United States during the first year of the pandemic (January 2020–January 2021). Statistical and geospatial analyses highlight greater impacts in the Great Plains, Southwestern and Southern regions based on cases and fatalities per 100,000 population. Significant case and fatality spatial clusters were most prevalent between November 2020 and January 2021. Distinct urban–rural differences in COVID-19 experiences uncovered higher rural cases and fatalities per 100,000 population and fewer government mitigation actions enacted in rural counties. High levels of social vulnerability and the absence of mitigation policies were significantly associated with higher fatalities, while existing community resilience had more influential spatial explanatory power. Using differences in percentage unemployment changes between 2019 and 2020 as a proxy for pre-emergent recovery revealed urban counties were hit harder in the early months of the pandemic, corresponding with imposed government mitigation policies. This longitudinal, place-based study confirms some early urban–rural patterns initially observed in the pandemic, as well as the disparate COVID-19 experiences among socially vulnerable populations. The results are critical in identifying geographic disparities in COVID-19 exposures and outcomes and providing the evidentiary basis for targeting pandemic recovery.

scholarly journals How Far Has China’s Urbanization Gone?

2018 ◽  
Vol 10 (8) ◽  
pp. 2953 ◽  
Author(s):  
Yiping Xiao ◽  
Yan Song ◽  
Xiaodong Wu
Keyword(s):  
Urban Development ◽  
Spatial Autocorrelation ◽  
Spatial Data ◽  
Spatial Association ◽  
Early Years ◽  
Spatial Data Analysis ◽  
Rapid Urbanization ◽  
Urban Rural ◽  
Global Spatial Autocorrelation ◽  
Over Time

China’s rapid urbanization has attracted wide international attention. However, it may not be sustainable. In order to assess it objectively and put forward recommendations for future development, this paper first develops a four-dimensional Urbanization Quality Index using weights calculated by the Deviation Maximization Method for a comprehensive assessment and then reveals the spatial association of China’s urbanization by Exploratory Spatial Data Analysis. The study leads to three major findings. First, the urbanization quality in China has gradually increased over time, but there have been significant differences between regions. Second, the four aspects of urbanization quality have shown the following trends: (i) the quality of urban development has steadily increased; (ii) the sustainability of urban development has shown a downward trend in recent years; (iii) the efficiency of urbanization improved before 2006 but then declined slightly due to capital, land use, and resource efficiency constraints; (IV) the urban–rural integration deteriorated in the early years but then improved over time. Third, although the urbanization quality has a significantly positive global spatial autocorrelation, the local spatial autocorrelation varies between eastern and western regions. Based on these findings, this paper concludes with policy recommendations for improving urbanization quality and its sustainability in China.

scholarly journals Rancang Bangun Jemuran Otomatis Menggunakan Mikrokontroller WEMOS

CAHAYAtech ◽  
2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Adetya Windiarto Makhmud ◽  
Tutus Praningki ◽  
Ira Luvi Indah
Keyword(s):  
Internet Of Things ◽  
Solar Energy ◽  
Light Intensity ◽  
Weather Conditions ◽  
Daily Activities ◽  
The Internet ◽  
The Right ◽  
The Internet Of Things

Drying clothes is one of the daily activities of people who use solar energy. With these conditions, people are very dependent on weather conditions that are sometimes erratic. One of the right ways is by utilizing technology, namely using an automatic clothesline using a Wemos D1Mini microcontroller, equipped with an LDR sensor that will read light intensity and the DHT11 sensor will read humidity and temperature around the environment. This tool is also based on the Internet of Things which can be accessed from anywhere as long as it is connected to the internet. Keyword: Microcontroller, LDR sensor, DHT11 sensor, Internet of Things.

scholarly journals Identifying Dynamic Changes in Ecosystem Services Supply and Demand for Urban Sustainability: Insights from a Rapidly Urbanizing City in Central China

2020 ◽  
Vol 12 (8) ◽  
pp. 3428 ◽  
Author(s):  
Zhengxin Ji ◽  
Yueqing Xu ◽  
Hejie Wei
Keyword(s):  
Ecosystem Services ◽  
Supply And Demand ◽  
Urban Sustainability ◽  
Well Being ◽  
Central China ◽  
Ecological Management ◽  
Dynamic Changes ◽  
Rapid Urbanization ◽  
Management Regime ◽  
Urban Rural

Identifying the balance and dynamic changes in supply and demand of ecosystem services (ES) can help maintain the sustainability of the regional ecosystem and improve human well-being. To achieve a sustainable ecological management regime in Zhengzhou City, this study presented a comprehensive framework for identifying dynamic changes of ES supply and demand and managing ES. Using land use data of Zhengzhou City in 1995, 2005, and 2015 and incorporating expert knowledge and the ES evaluation matrix, we evaluated the spatiotemporal changes in the ES supply and demand in Zhengzhou. Gradient analysis was conducted to identify urban–rural patterns in the budgets of ES supply and demand. Spatial autocorrelation analysis was employed to identify the hotspot areas of ES surpluses or deficits. The research results show the following: (1) In the past 20 years, the supply-and-demand relationship of ES in Zhengzhou has gradually evolved in a direction where supply falls short of demand. The average budget index of Zhengzhou’s ES supply and demand decreased from 7.30 in 1995 to −4.89 in 2015. Changes in the supply and demand status of ES in Zhengzhou corresponded to the background of rapid urbanization. (2) Urban–rural gradient differences exist in the budgets of ES supply and demand in Zhengzhou. Core development areas, such as the Zhengzhou urban areas, are in deficit, whereas a balance or surplus can be observed in rural areas far from urban centers. (3) The surplus hotspots of ES budgets were mainly distributed in the western and southern mountainous areas of Zhengzhou, and they were scattered and the scope shrank, with a decrease of 2.73 times in 20 years, whereas the deficit hotspots expanded outward with each urban area as the center, with an increase of 5.77%. Ecological management zoning (ecological conservation area, ecological improvement area, and ecological reconstruction area) with the effective guidance of ecological and economic policies could comprehensively improve ES management and achieve urban sustainability. The framework in this study can easily and quickly assess the supply and demand status of ES and provide scientific support for the ecological management in rapidly urbanizing areas.

scholarly journals The Vertical Stratification of Air Temperature in the Center of Athens

2010 ◽  
Vol 49 (6) ◽  
pp. 1219-1232 ◽  
Author(s):  
C. Georgakis ◽  
M. Santamouris ◽  
G. Kaisarlis
Keyword(s):  
Air Temperature ◽  
Open Space ◽  
Ground Level ◽  
Weather Conditions ◽  
Threshold Value ◽  
Critical Threshold ◽  
Aspect Ratios ◽  
Urban Geometry ◽  
Urban Rural ◽  
The Difference

Abstract The intraurban temperature variation in the center of Athens, Greece, was investigated in relation to urban geometry. This paper describes two main tasks: 1) Air temperature was recorded in the center of Athens and at the Meteorological Service Station at the University of Athens. Experimental data were collected through extensive monitoring at four different heights inside five different urban canyons in the center of Athens during the summer period. A measurement uncertainty analysis was carried out to estimate critical threshold values of air temperature below which differences were not significant. 2) The correlation between urban–suburban air temperature differences was assessed, using the geometrical characteristics of each urban street canyon. Urban–rural air temperature differences were considered to be not important if they were below the threshold value of 0.3°C. It was concluded that the major factor controlling urban–suburban air temperature differences was the geometry of the urban area. Other factors were the orientation of the observational sites, the current weather conditions, and the inversion of air masses adjacent to the ground level. An increase in the value of aspect ratios leads to a decrease in the difference between air inside the canyons and at the suburban station. The air temperature profile in an open-space area was the most important defining factor for the stratification of the urban–rural air temperature differences.

scholarly journals Physician distribution across China’s cities: Regional variations

2020 ◽  
Author(s):  
Xuexin Yu ◽  
Wei Zhang ◽  
Jersey Liang
Keyword(s):  
Access To Health Care ◽  
Urban China ◽  
Limited Attention ◽  
Physician Density ◽  
Rapid Urbanization ◽  
Regional Variations ◽  
Urban Agglomerations ◽  
Urban Rural ◽  
Physician Distribution ◽  
Health Demand

Abstract Background Distribution of physicians is a key component of access to health care. Although there is extensive research on urban-rural disparities in physician distribution, limited attention has been directed to the heterogeneity across urban areas.This research depicts variations in physician density across over 600 cities in the context of China’s rapid urbanization. Methods Data came from National Census Surveys and China statistical yearbooks, 2000-2003, and 2010-2013. Cities were characterized in terms of not only administrative level but also geographic regions and urban agglomerations. We analyzed variations in physician supply by applying generalized estimating equations with an ordinal logistic linking function. Results Although overall physician density increased between 2003 and 2013, with population and socioeconomic attributes adjusted, physician density actually declined in urban China. On average, urban districts had a higher physician density than county-level cities, but there were regional variations. Cities in urban agglomerations and those outsides did not differ in physician density.Conclusion Despite the improved inequality between 2003 and 2013, the growth in physician density did not appear to be commensurate with the changes in population health demand. Assessment in physician distribution needs to take into account heterogeneity in population and socioeconomic characteristics.

scholarly journals Spatial Variation of Land Use/Cover Composition and Impact on Surface Urban Heat Island in a Tropical Sub-Saharan City of Accra, Ghana

2020 ◽  
Vol 12 (19) ◽  
pp. 7953
Author(s):  
Darshana Athukorala ◽  
Yuji Murayama
Keyword(s):  
Land Use ◽  
Urban Heat Island ◽  
Heat Island ◽  
Human Beings ◽  
Rapid Urbanization ◽  
Bare Land ◽  
Urban Rural ◽  
Urban Heat ◽  
The Mean ◽  
Sub Saharan

Rapid urbanization is one of the most crucial issues in the world of the 21st century. Notably, the urban heat island phenomenon is becoming more prominent in megacities and their hinterlands in temperate and subtropical climatic regions. In the daytime in summer, there exists a high possibility of accelerating the land surface temperature (LST) in desert cities, due to the alterations made by human beings in the natural environment. In this study, we investigate the spatial formation of LST in a tropical sub-Saharan city of Accra, a gateway to West Africa, using Landsat data in 2003 and 2017. Machine learning techniques and the different spatial and statistical methods such as tasseled cap transformation (TCT), urban-rural gradient, and multiresolution grid-based and landscape metrics were employed to examine procured land use/cover (LUC) and LST maps. LUC was classified into five categories: Built up, Green 1, Green 2, Bare land, and Water. The results of the analysis indicate that Built up, Green 2, and Bare land had caused the highest heating effect while Green 1 and Water had caused the considerable cooling effect during the daytime in Accra. The urban-rural difference in LST recorded 1.4 °C in 2003 and 0.28 °C in 2017. The mean size, mean shape, largest patch, and aggregation of Built up, Green 1, and Green 2 had a strong relationship with the mean LST. It is essential for urban planners to carefully examine the formation and effect of the urban heat island (UHI) for sustainable urban development and landscape policy toward mitigation and adaptation planning in Accra.

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