scholarly journals Semi-stationary measurement as a tool to refine understanding of the soil temperature spatial variability

2015 ◽  
Vol 29 (4) ◽  
pp. 449-457 ◽  
Author(s):  
Michal Lehnert ◽  
Miroslav Vysoudil ◽  
Petr Kladivo
Keyword(s):  
Spatial Variability ◽  
Soil Temperature ◽  
Temperature Measurement ◽  
Computer Technology ◽  
Spatial Data ◽  
Local Level ◽  
Limited Area ◽  
Using Data ◽  
Further Development ◽  
Stationary Measurement

AbstractUsing data obtained by soil temperature measurement at stations in the Metropolitan Station Network in Olomouc, extensive semi-stationary measurement was implemented to study the spatial variability of the soil temperature. With the development of the research and computer technology, the study of the temperature is not limited by the complexity of the processes determining the soil temperature, but by the lack of spatial data. This study presents simple semi-stationary soil temperature measurement methods, which can contribute to the study of the spatial variability of soil temperature. By semi-stationary measurement, it is possible to determine the average soil temperature with high accuracy and the minimum soil temperature with sufficient accuracy at a depth of 20 cm. It was proven that the spatial variability of the minimum soil temperature under grass at a depth of 20 cm can reach up to several degrees Celsius at the regional level, more than 1°C at the local level, and tenths of °C at the sublocal level. Consequently, the standard stationary measurement of the soil temperature can be regarded as representative only for a very limited area. Semi-stationary soil temperature measurement is, therefore, an important tool for further development of soil temperature research.

scholarly journals Spatial variability of soil temperature in an urban area: A case study for a medium-sized European city

2021 ◽  
Vol 25 (1) ◽  
pp. 1-9
Author(s):  
Michal Lehnert ◽  
Petr Šimáček ◽  
David Fiedor ◽  
Martin Jurek
Keyword(s):  
Spatial Variability ◽  
Soil Temperature ◽  
Urban Landscape ◽  
European City ◽  
Conceptual Approach ◽  
Central European ◽  
Temperature Observation ◽  
Shadow Cast ◽  
Stationary Measurement

Even though soil temperature in urban environment influences a range of processes, it has been studied rather sparsely in comparison with surface temperature or air temperature. Our research extends the soil temperature observation in Olomouc (Czechia) and uses semi-stationary measurement to describe detailed spatial variability of soil temperature in the area of a medium-sized Central European city. Differences in soil temperature 20 cm below grass-covered surface may exceed 3°C due to soil type, shadow cast by buildings and grass characteristics, which means that the representativeness of the data on soil temperature from a meteorological station within a city may be limited. Further research and a conceptual approach towards the study of soil temperature in urban landscape is needed.

A short-term decline in anthropogenic emission of CO2 in India due to COVID-19 confinement

2020 ◽  
pp. 030913332096674
Author(s):  
Bikash Ranjan Parida ◽  
Somnath Bar ◽  
Nilendu Singh ◽  
Bakimchandra Oinam ◽  
Arvind Chandra Pandey ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Fossil Fuels ◽  
Local Level ◽  
Energy Generation ◽  
Total Change ◽  
Increasing Demand ◽  
Using Data ◽  
Novel Coronavirus ◽  
Renewable Energy Generation

To curb the spread of novel coronavirus (COVID-19), confinement measures were undertaken, which altered the pattern of energy consumption and India’s anthropogenic CO2 emissions during the effective lockdowns periods (January to June 2020). Such changes are being analyzed using data of energy generated from coal and renewable sources and fossil-based daily CO2 emissions. Results revealed that coal-fired (fossil-based) energy generation fell by –13% in March, –29% in April, and –20% in May, and –16.6% in mid-June 2020 as compared with the same period in 2018–2019. Conversely, the renewable energy generation increased by 19% in March, 12% in April, 17% in May, and 7% in June 2020. The share of fossil-based energy fell by –6.55% in 2020 compared with mean levels, which was further offset by increases of renewable energy. India’s daily fossil-based CO2 emissions fell by –11.6% (–5 to –25.7%) by mid-June 2020 compared with mean levels of 2017–2019 with total change in fossil-based CO2 emission by –139 (–62 to –230) MtCO2, with the largest reduction in the industry (–41%), transport (–28.5%), and power (–21%) followed by the public (–5.4%), and aviation (–4%) sectors. If some levels of lockdown persist until December 2020, both energy consumption and CO2 emissions patterns would be below the 2019 level. The nationwide lockdown has led to a reduction in anthropogenic CO2 emissions and, subsequently, improved air quality and global environment and has also helped in reducing atmospheric CO2 concentrations at the local level but not on the global level. With suitable government policies, switching to a cleaner mode of energy generation other than fossil fuels could be a viable option to minimize CO2 emissions under increasing demand for energy.

scholarly journals USING PARTICIPATORY APPROACH TO IMPROVE AVAILABILITY OF SPATIAL DATA FOR LOCAL GOVERNMENT

2016 ◽  
Vol III-4/W1 ◽  
pp. 139-144
Author(s):  
T. Kliment ◽  
V. Cetl ◽  
H. Tomič ◽  
J. Lisiak ◽  
M. Kliment
Keyword(s):  
Spatial Data ◽  
Local Governments ◽  
Local Level ◽  
Property Tax ◽  
Open Data ◽  
Quality Level ◽  
Tax Rates ◽  
Geospatial Information ◽  
Data Infrastructure ◽  
Participatory Gis

Nowadays, the availability of authoritative geospatial features of various data themes is becoming wider on global, regional and national levels. The reason is existence of legislative frameworks for public sector information and related spatial data infrastructure implementations, emergence of support for initiatives as open data, big data ensuring that online geospatial information are made available to digital single market, entrepreneurs and public bodies on both national and local level. However, the availability of authoritative reference spatial data linking the geographic representation of the properties and their owners are still missing in an appropriate quantity and quality level, even though this data represent fundamental input for local governments regarding the register of buildings used for property tax calculations, identification of illegal buildings, etc. We propose a methodology to improve this situation by applying the principles of participatory GIS and VGI used to collect observations, update authoritative datasets and verify the newly developed datasets of areas of buildings used to calculate property tax rates issued to their owners. The case study was performed within the district of the City of Požega in eastern Croatia in the summer 2015 and resulted in a total number of 16072 updated and newly identified objects made available online for quality verification by citizens using open source geospatial technologies.

scholarly journals Perceived crowding and physical distance rules: a national account perspective

2021 ◽  
Vol 3 (3) ◽  
pp. 330-341
Author(s):  
Andrea Karim El Meligi ◽  
◽  
Donatella Carboni ◽  
Giorgio Garau
Keyword(s):  
National Park ◽  
Local Level ◽  
Social Factor ◽  
Physical Distance ◽  
National Account ◽  
Tourist Attractions ◽  
Macroeconomic Analysis ◽  
Employment Impact ◽  
The Social ◽  
Using Data

<abstract><p>Policies concerning the sustainable tourism are fundamentally addressed to the environmental protection and to minimize the anthropogenic impact when exploiting beaches, archeological sites and other tourist attractions. In this paper, we propose a subjective measure, namely the Perceived factor, in order to take into account the more general dimension of the social factor in the assessment of the Tourism Carrying Capacity (TCC) measures. The analysis evaluates the employment impact of the perceived crowding by using data resulting from a survey conducted in the Asinara National Park. In this respect, a macroeconomic analysis is presented by using a SAM scheme developed at a local level, based on four municipalities representing a potential gravitational area of tourists visiting the Asinara National Park. Afterward, a SAM-based model combined with the sustainability measures is proposed to compute the employment loss due to the Perceived factor.</p></abstract>

scholarly journals Dealing with Maritime Economy at the Local Level. Trends along the Coastal Poland

2018 ◽  
Vol 58 ◽  
pp. 01028
Author(s):  
Barbara Szejgiec-Kolenda ◽  
Jacek Zaucha
Keyword(s):  
Local Level ◽  
Local Economy ◽  
Regional Level ◽  
Data Availability ◽  
Limited Area ◽  
Local Dimension ◽  
Local Economies ◽  
Functional Region ◽  
Maritime Economy ◽  
Blue Economy

Although the interest in the concept of ‘blue economy’ has grown rapidly in recent years, the most studies assess maritime activities’ size, scope, basic trends or position in national economy mostly at the basin/national, sometimes even regional level and there has been little research taking into account the local dimension of maritime economy. This is partly due to a lack of appropriate statistical data concerning maritime economy. The aim of the analysis is to define and describe the local maritime economy in Poland as well as to establish its importance for various territories. This study considers the challenges that maritime local studies face in terms of data availability and provides a research path that is to some extent complementary to analyses at the national and regional level. It explores a two-step approach to measure and evaluate a maritime local economy in Poland in 2016: (1) a more general countrywide attempt to identify the problem; (2) addressing the local dimension of blue economy in the spatially limited area (coastal regions). Moreover, the approach allows to identify territorial differences (functional region types), the extent to which these activities differ among local economies and the pathways for maritime economy structures transitions along the coastal Poland.

scholarly journals Soil Temperature Estimation with Meteorological Parameters by Using Tree-Based Hybrid Data Mining Models

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1407
Author(s):  
Mohammad Taghi Sattari ◽  
Anca Avram ◽  
Halit Apaydin ◽  
Oliviu Matei
Keyword(s):  
Soil Temperature ◽  
Soil Depth ◽  
Sunshine Duration ◽  
Evaluation Criteria ◽  
Nonlinear Problems ◽  
Soil Temperatures ◽  
Different Depths ◽  
Windowing Technique ◽  
Using Data ◽  
Research Decision

The temperature of the soil at different depths is one of the most important factors used in different disciplines, such as hydrology, soil science, civil engineering, construction, geotechnology, ecology, meteorology, agriculture, and environmental studies. In addition to physical and spatial variables, meteorological elements are also effective in changing soil temperatures at different depths. The use of machine-learning models is increasing day by day in many complex and nonlinear branches of science. These data-driven models seek solutions to complex and nonlinear problems using data observed in the past. In this research, decision tree (DT), gradient boosted trees (GBT), and hybrid DT–GBT models were used to estimate soil temperature. The soil temperatures at 5, 10, and 20 cm depths were estimated using the daily minimum, maximum, and mean temperature; sunshine intensity and duration, and precipitation data measured between 1993 and 2018 at Divrigi station in Sivas province in Turkey. To predict the soil temperature at different depths, the time windowing technique was used on the input data. According to the results, hybrid DT–GBT, GBT, and DT methods estimated the soil temperature at 5 cm depth the most successfully, respectively. However, the best estimate was obtained with the DT model at soil depths of 10 and 20 cm. According to the results of the research, the accuracy rate of the models has also increased with increasing soil depth. In the prediction of soil temperature, sunshine duration and air temperature were determined as the most important factors and precipitation was the most insignificant meteorological variable. According to the evaluation criteria, such as Nash-Sutcliffe coefficient, R, MAE, RMSE, and Taylor diagrams used, it is recommended that all three (DT, GBT, and hybrid DT–GBT) data-based models can be used for predicting soil temperature.

scholarly journals Does immigration decrease far-right popularity? Evidence from Finnish municipalities

2020 ◽  
Vol 34 (1) ◽  
pp. 97-139 ◽  
Author(s):  
Jakub Lonsky
Keyword(s):  
Voter Turnout ◽  
Local Level ◽  
Far Right ◽  
Intergroup Contact Theory ◽  
Initial Exposure ◽  
Percentage Point Increase ◽  
Point Increase ◽  
Negative Effect ◽  
Plausible Mechanism ◽  
Using Data

Abstract Across Europe, far-right parties have made significant electoral gains in recent years. Their anti-immigration stance is considered one of the main factors behind their success. Using data from Finland, this paper studies the effect of immigration on voting for the far-right Finns Party on a local level. Exploiting a convenient setup for a shift-share instrument, I find that a 1 percentage point increase in the share of foreign citizens in a municipality decreases the Finns Party’s vote share by 3.4 percentage points. Placebo tests using pre-period data confirm this effect is not driven by persistent trends at the municipality level. The far-right votes lost to immigration are captured by the two pro-immigration parties. Turning to potential mechanisms, immigration is found to increase voter turnout, potentially activating local pro-immigration voters. Moreover, the negative effect is only present in municipalities with high initial exposure to immigrants, consistent with the intergroup contact theory. Finally, I also provide some evidence for the welfare-state channel as a plausible mechanism behind the main result.

scholarly journals Development of Shallow-Depth Soil Temperature Estimation Model Based on Thermal Response in Permafrost Area

2018 ◽  
Vol 8 (10) ◽  
pp. 1886 ◽  
Author(s):  
Keunbo Park ◽  
Heekwon Yang ◽  
Bang Lee ◽  
Dongwook Kim
Keyword(s):  
Soil Temperature ◽  
Temperature Measurement ◽  
Thermal Response ◽  
Estimation Model ◽  
Temperature Estimation ◽  
Soil Temperatures ◽  
Different Depths ◽  
The Relationship ◽  
Temperature Depth ◽  
Good Agreement

A soil temperature estimation model for increasing depth in a permafrost area in Alaska near the Bering Sea is proposed based on a thermal response concept. Thermal response is a measure of the internal physical heat transfer of soil due to transferred heat into the soil. Soil temperature data at different depths from late spring to the early autumn period at multiple permafrost sites were collected using automatic sensor measurements. From the analysis results, a model was established based on the relationship between the normalized cumulative soil temperatures (CRCST*i,m and CST*ud,m) of two different depths. CST*ud,m is the parameter of the soil temperature measurement at a depth of 5 cm, and CRCST*i,m is the parameter of the soil temperature measured at deeper depths of i cm (i = 10, 15, 20, and 30). Additionally, the fitting parameters of the mathematical models of the CRCST*i,m–CST*ud,m relationship were determined. The measured soil temperature depth profiles at a different site were compared with their predicted soil temperatures using the developed model for the model validation purpose. Consequently, the predicted soil temperatures at different soil depths using the soil temperature measurement of the uppermost depth (5 cm) were in good agreement with the measured results.

scholarly journals Translational Roadmap for the Organs-on-a-Chip Industry toward Broad Adoption

2020 ◽  
Vol 7 (3) ◽  
pp. 112 ◽  
Author(s):  
Vanessa Allwardt ◽  
Alexander J. Ainscough ◽  
Priyalakshmi Viswanathan ◽  
Stacy D. Sherrod ◽  
John A. McLean ◽  
...  
Keyword(s):  
Technology Development ◽  
Technology Readiness ◽  
Disruptive Technology ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Commercial Viability ◽  
Performance Benchmarks ◽  
Using Data ◽  
Further Development

Organs-on-a-Chip (OOAC) is a disruptive technology with widely recognized potential to change the efficiency, effectiveness, and costs of the drug discovery process; to advance insights into human biology; to enable clinical research where human trials are not feasible. However, further development is needed for the successful adoption and acceptance of this technology. Areas for improvement include technological maturity, more robust validation of translational and predictive in vivo-like biology, and requirements of tighter quality standards for commercial viability. In this review, we reported on the consensus around existing challenges and necessary performance benchmarks that are required toward the broader adoption of OOACs in the next five years, and we defined a potential roadmap for future translational development of OOAC technology. We provided a clear snapshot of the current developmental stage of OOAC commercialization, including existing platforms, ancillary technologies, and tools required for the use of OOAC devices, and analyze their technology readiness levels. Using data gathered from OOAC developers and end-users, we identified prevalent challenges faced by the community, strategic trends and requirements driving OOAC technology development, and existing technological bottlenecks that could be outsourced or leveraged by active collaborations with academia.

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