Opposite of anthropogenic Video
Anthropogenic ImpactsInfinitely possible: Opposite of anthropogenic
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Implications of plagiarism | anthropogenic impact and climate change" (), "Taxonomical, population, ecological and However, the latest researches show the opposite conclusion: ALAN has a significant influence on reproduction, navigation, behavior, foraging, habitat selection, communication, and social interactions of all living organisms. Title: Senior Lecturer at Luhansk Taras . Human impact on the environment or anthropogenic impact on the environment includes changes to biophysical environments and ecosystems, biodiversity, and natural resources caused directly or indirectly by humans, including global warming, environmental degradation (such as ocean acidification), mass extinction and biodiversity loss, ecological crisis, and ecological collapse. 4 days ago · Deforestation and habitat loss resulting from land use changes are some of the utmost anthropogenic impacts that threaten tropical birds in human-modified landscapes (HMLs). |
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Anderson , G. Bergstrom , R. Pilewskie , B. Schmid , and P. Bintanja , R. Drijfhout , B. Wouters , and C. Katsman , : Important role for ocean warming and increased ice-shelf melt in Antarctic sea-ice expansion. Katsman , : The effect of increased fresh water from Antarctic ice shelves on future trends in Antarctic sea ice. Bitz , C.The influence of landscape patterns on urban thermal environment has received remarkable attention with the rapid urbanization process worldwide. Although numerous studies have revealed the relationship between landscape patterns and the urban thermal environment, there is limited effort to quantify the contributions of landscape patterns and anthropogenic heat to urban heat islands UHI under the seasonal and daily dynamics. This study aims to identify the effects of landscape patterns and anthropogenic heat on UHI intensity in the daytime and nighttime as well as in different seasons.
We first used remotely sensed images to extract the landscape patterns and land surface temperature. Anthropogenic heat was quantified through energy consumption data. Multivariate stepwise regression was used to quantify the effects of landscape patterns and anthropogenic heat on UHI intensity. Eight models were constructed for daytime and nighttime UHI intensity in spring, summer, fall, and winter, respectively. Results demonstrated that the presence of buildings is the main factor affecting UHI intensity in urban area for three seasons except summer. Basically, the contributions of landscape configuration to the UHI in the daytime is higher than landscape composition, while the opposite is true at night. The contribution of anthropogenic heat was low in all seasons due to the high correlation with non-monolayer buildings. Opposite of anthropogenic nighttime UHI intensity models fit better than the daytime, especially in the winter. This study contributes to the understanding of landscape influence on UHI intensity and provides practical guidelines for landscape planning to mitigate UHI effects.
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Heliyon 5 4 :. Boehme P, Berger M, Massier T Estimating the building based energy consumption as an anthropogenic contribution to urban heat islands.
Cities Soc — Sci Total Environ Energy Build — Build Environ Landsc Urban Plan — Atmos Environ 45 4 — Dadashpoor H, Azizi P, Moghadasi M Land use change, urbanization, and change in landscape pattern in a metropolitan area. Sci Total Environ — Ocean Coast Manag opposihe Atmos Environ 39 1 — A literature based study on understanding urban heat vulnerability and the need for resilience opposite of anthropogenic cities in a global climate change context.
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J Clean Prod — Foken T The energy balance closure problem: an overview. Ecol Appl 18 6 — Fonseca JA, Schlueter A Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts.
Appl Energy — Foody GM Explaining the unsuitability of the kappa coefficient in the opposite of anthropogenic and comparison of the accuracy of thematic maps obtained by image classification. Remote Sens Environ. Fujimoto A, Saida A, Fukuhara T A new approach to modeling vehicle-induced heat and its thermal effects on road surface temperature. J Appl Meteorol Clim 51 11 —]
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