Article
Construction & Building Technology
Kewen Wang, Haitao Ma, Chuanglin Fang
Summary: This study evaluates the comprehensive urbanization level (CUL) and urban ecological resilience (UER) in the Northern Slope Economic Belt of Tianshan Mountains (NSEBTM) and analyzes the relationship between CUL and UER using statistical analysis. The results show that CUL and UER in the NSEBTM have gradually increased from 2005 to 2020 with spatial heterogeneity. There is a positive correlation between CUL and UER, and the number of cities with high levels in both aspects has increased over time. These findings provide valuable insights for the analysis of the man-land relationship and contribute to urban sustainable development in arid regions.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Environmental Sciences
Xinyu Lu, Jing Li, Yan Liu, Yang Li, Hong Huo
Summary: In this study, correction techniques were used to improve the satellite inversion of precipitation data in the Tianshan Mountains. It was found that the random forest method showed better correction results than traditional methods, providing a practical reference for estimating precipitation data in non-rainfall observation areas.
Article
Environmental Sciences
Sun Chen, Ma Yonggang, Gong Lu
Summary: The study found that there were significant changes in land use/cover in the northern slope region of Xinjiang during the study period, with an increase in area for all land use/cover types except grassland and unused land. The total ESV decreased, with waterbody having a significantly higher ESV compared to other land use/cover types.
JOURNAL OF ARID LAND
(2021)
Article
Immunology
Venkata Raghava Mohan, Manikandan Srinivasan, Bireshwar Sinha, Ankita Shrivastava, Suman Kanungo, Kulandaipalayam Natarajan Sindhu, Karthikeyan Ramanujam, Santhosh Kumar Ganesan, Arun S. Karthikeyan, Senthil Kumar Jaganathan, Annai Gunasekaran, Alok Arya, Ashish Bavdekar, Temsunaro Rongsen-Chandola, Shanta Dutta, Jacob John, Gagandeep Kang
Summary: This analysis evaluated spatial clustering of typhoid and modeled incidence rates at 4 sites in India, identifying hotspots in Vellore and Kolkata. Despite efforts to improve water and sanitation, environmental factors continue to influence typhoid incidence, highlighting the potential need for vaccination alongside ongoing improvements in water and sanitation.
JOURNAL OF INFECTIOUS DISEASES
(2021)
Article
Environmental Sciences
Shahid Nawaz Khan, Dapeng Li, Maitiniyazi Maimaitijiang
Summary: This study proposes a method called Geographically Weighted Random Forest Regression (GWRFR) to improve crop yield prediction. The GWRFR outperforms other machine learning algorithms and can better address the spatial non-stationarity issue. This method has the potential to be used for yield prediction of other types of crops in different regions.
Article
Green & Sustainable Science & Technology
Gulmira Abbas, Alimujiang Kasimu
Summary: In this study, the researchers tentatively investigated the landuse carbon emissions of the economic belt on the northern slope of Tianshan. They estimated and analyzed the carbon emissions and carbon intensities of 12 cities in the area using remote sensing image and statistical data. The results showed rapid increase in urban land and cropland, significant increase in carbon emissions mainly caused by urban land, negative spatial correlations between carbon emissions and carbon intensities among the cities, and the division of NST into four different zones based on carbon balance zoning analysis.
Article
Construction & Building Technology
Hanghun Jo, Heungsoon Kim
Summary: The recent increase in global energy consumption has accelerated global warming. Developed countries are aiming to reduce energy consumption in cities and promote eco-friendly policies. This study found that population and household characteristics, outdoor temperature, green and water areas, building area according to usage, and construction age significantly affect electrical energy consumption in urban buildings. The influences of these factors also vary by region.
Article
Environmental Sciences
Wen Ma, Jianli Ding, Rui Wang, Jinlong Wang
Summary: This study examines the variation of PM2.5 in the northwestern urban agglomeration of China using near-surface observation data. The results show that NO2 and SO2 are the two most dominant factors influencing PM2.5 concentrations, while meteorological factors also play a significant role. The study highlights the importance of the interaction between pollutant emissions and meteorological factors in affecting PM2.5, providing valuable insights for developing effective emission reduction strategies.
ENVIRONMENTAL POLLUTION
(2022)
Article
Geography
Katherine Ballard, Christopher Bone
Summary: Understanding environmental variables responsible for the spatial distribution of Lyme disease is crucial for predicting disease incidence. Specific land cover types play a significant role in predicting disease locations, but these relationships can vary within each region. It is important to consider the larger geographic context influencing the presence and spread of the disease when implementing Lyme disease mitigation efforts.
Article
Biodiversity Conservation
Guoju Wu, Guobao Xu, Bo Wang, Xiaohong Liu, Tuo Chen, Huhu Kang
Summary: The forest in the Tianshan Mountains has been experiencing a decline in growth and an increased mortality rate due to severe droughts, posing a threat to the ecosystem services they provide. This study examined the post-drought recovery of dominant tree species using tree-ring proxy data and found that post-drought moisture conditions played a crucial role in determining tree growth recovery. The findings highlight the importance of climate conditions and precipitation in managing and conserving forests in response to extreme drought events.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Shukui Tan, Maomao Zhang, Ao Wang, Xuesong Zhang, Tianchi Chen
Summary: This study analyzed the impact mechanisms of China's carbon emissions data during 2010-2017 using the MGWR model, finding positive spatial correlations and further strengthening spatial autocorrelation over time. The MGWR model was shown to be more robust than the GWR model, and the main factors influencing carbon emissions include energy intensity, proportion of green coverage in built-up areas, and industrial structure.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Geography
Alexis Comber, Martin Callaghan, Paul Harris, Binbin Lu, Nick Malleson, Chris Brunsdon
Summary: This paper introduces a new package called gwverse, which aims to provide more functionality and flexibility in spatial analysis, particularly in GWR and GW models. The package meets the needs of different users through its modular structure and customized function approach, and provides several demonstrator modules for GWR analysis.
GEOGRAPHICAL ANALYSIS
(2022)
Article
Forestry
Abdugheni Abliz, Qingdong Shi, Abudukeyimu Abulizi
Summary: In recent years, soil heavy metal pollution has become an important issue. The study area in the northern slope of the eastern Tianshan Mountains was selected to measure six heavy metals. The results showed that certain heavy metals exceeded the soil background value and posed a risk to human health. This research provides a theoretical basis and reference for heavy metal pollution control and human health risk management.
Article
Environmental Studies
Yayan Lu, Xiaoliang Xu, Junhong Zhao, Fang Han
Summary: This study evaluated the ecosystem services provided by the Tianshan Mountains of Xinjiang from 2000 to 2020 using the InVEST and RUSLE models. The results showed that habitat quality and carbon storage remained relatively stable, while soil retention and water yield fluctuated significantly. All ecosystem services exhibited synergies, and middle- and high-altitude areas were the main supply areas. Land-use types and mean annual precipitation were identified as the dominant driving factors for ecosystem services.
Article
Environmental Studies
Mateusz Tomal, Marco Helbich
Summary: A new spatial autoregressive geographically weighted quantile regression method was proposed in this study to address the shortcomings of standard hedonic regression models. Comparing with mean and quantile hedonic regressions, the results showed that the proposed method outperforms other models in terms of fitting accuracy, especially at the tails of the dependent variable distribution. Policy recommendations for the development of private residential rental markets were provided based on the findings, which incorporate spatial effects and price segment requirements.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2023)