|تعداد مشاهده مقاله||111,513,054|
|تعداد دریافت فایل اصل مقاله||86,148,275|
The reciprocal effect of global warming and climatic change (new perspective): A review
|دوره 27، شماره 2، اسفند 2022، صفحه 291-305 اصل مقاله (1.07 M)|
|نوع مقاله: Research Paper|
|شناسه دیجیتال (DOI): 10.22059/jdesert.2022.90831|
|S.K. Alavipanah* 1؛ M. Mansourmoghaddam2؛ Z. Gomeh3؛ E. Galehban3؛ S. Hamzeh3|
|1Department of Remote Sensing and GIS, University of Tehran, Tehran, Iran.|
|2Center for Remote Sensing and GIS studies, Shahid Beheshti University|
|3Department of Remote Sensing and GIS, University of Tehran, Tehran, Iran|
|Climate change is one of the most pressing problems among scientists worldwide, with experts warning about it and even referring to it as unfathomable human agony. In this study, we reviewed previous studies and examined two gaps in the existing approach to climate change studies. First, look at the "side effects" of global warming that have been overlooked in the process and then look at the leading "cause" of global warming, namely "humans" and not its "effects". The findings revealed that a 1.4 °C temperature increase (as predicted by United National (UN) projections) would not only raise this amount but also trigger further global warming. As a result, the premise that global warming produces additional global warming was proven. In the Water Area (WA) class, radiant energy increased by 1194.8%, compared to 1205.8%, 1154.9%, 1115.6% and 1229% in the Vegetation Area Class (VAC), Agricultural Area Class (AAC), Bare Area Class (BAC) and Salt Lake Class (SLC), respectively. Although the Land Surface Temperature (LST) of all classes has only increased by about 0.4 °C, these changes in radiant energy are much more pronounced. The current study also revealed that most legitimate research on this subject has focused on the effects of global warming on environmental variations. These studies, which see these changes as "results" of climate change and global warming, have overlooked the primary cause, "human demands", which has prompted humans to alter or exploit their surroundings actively. This study found that concentrating on humans and encouraging them to focus on happiness rather than pleasure is more helpful in addressing global warming issues than focusing on its impacts, such as rising sea level, storms, drought, etc. The results of this study are helpful for a deeper understanding of global warming and a careful study of the cause and dimensions of this phenomenon.|
|Heat entropy؛ Thermal Remote Sensing؛ Human؛ Warming effects؛ Land Surface Temperature|
AghaKouchak, A., F. Chiang, L. S. Huning, C. A. Love, I. Mallakpour, O. Mazdiyasni, M. Sadegh, 2020. Climate extremes and compound hazards in a warming world. Annual Review of Earth and Planetary Sciences, 48; 519-548.
The reciprocal effect of Global warming and climatic change (new perspective) 303
Aizebeokhai, A. P., 2009. Global warming and climate change: Realities, uncertainties and measures. International journal of physical sciences, 4(13); 868-879. Al‐Ghussain, L., 2019. Global warming: review on driving forces and mitigation. Environmental Progress & Sustainable Energy, 38(1); 13-21. Alavipanah, S. K., 2018. Thermal remote sensing and its application in earth sciences. 4th ed. University of Tehran Press. Alavipanah, S. K., M. Karimi Firozjaei, M., Sedighi, A., Fathololoumi, S., Zare Naghadehi, S., Saleh, S., & P. M.Atkinson, 2022. The Shadow Effect on Surface Biophysical Variables Derived from Remote Sensing: A Review. Land, 11(11); 1-30. As-Syakur, A. R., I. W. S. Adnyana, I. W. Arthana, & I. W. Nuarsa, 2012. Enhanced built-up and bareness index (EBBI) for mapping built-up and bare land in an urban area. Remote Sensing, 4(10); 2957-2970. Asadi, M., A. Oshnooei-Nooshabadi, S.-a. Saleh, F. Habibnezhad, S. Sarafraz-Asbagh, & J. L. Van Genderen, 2022. Simulation of Urban Sprawl by Comparison Cellular Automata-Markov and ANN. Berggren, K., M. Olofsson, M. Viklander, G. Svensson, & A.-M. Gustafsson, 2012. Hydraulic impacts on urban drainage systems due to changes in rainfall caused by climatic change. Journal of Hydrologic Engineering, 17(1); 92-98. Bobrov, P., & O. Galeyev. (2001). Observed effects of soil humus & salt contents on the microwave emissivity of soils. IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No. 01CH37217), Bokaie, M., M. K. Zarkesh, P. D. Arasteh, & A. Hosseini, 2016. Assessment of urban heat island based on the relationship between land surface temperature and land use/land cover in Tehran. Sustainable Cities and Society, 23; 94-104. Christidis, N., P. A. Stott, & S. J. Brown, 2011. The role of human activity in the recent warming of extremely warm daytime temperatures. Journal of Climate, 24(7); 1922-1930. Dean, A., & G. Smith, 2003. An evaluation of per-parcel land cover mapping using maximum likelihood class probabilities. International Journal of Remote Sensing, 24(14); 2905-2920. DeFries, R. S., & J. Townshend, 1994. NDVI-derived land cover classifications at a global scale. International Journal of Remote Sensing, 15(17); 3567-3586. Dosio, A., L. Mentaschi, E. M. Fischer, & K. Wyser, 2018. Extreme heat waves under 1.5 C and 2 C global warming. Environmental Research Letters, 13(5); 054006. Dube, T., P. Moyo, M. Ncube, & D. Nyathi, 2016. The impact of climate change on agro-ecological based livelihoods in Africa: A review. Dube T, Moyo P, Mpofu M, Nyathi D (2016), The impact of climate change on agro-ecological based livelihoods in Africa: A review, Journal of Sustainable Development, 9(1); 256-267. Exelis, 2015. QUick Atmospheric Correction (QUAC®) Version 5.3) [Help document]. Preprocessing > Atmospheric Correction Module > QUick Atmospheric Correction (QUAC®) Fritz, A., & R. Ramirez, 2021. Earth is warming faster than previously thought, scientists say, and the window is closing to avoid catastrophic outcomes. CNN. Retrieved 17 Mar 2022 from https://edition.cnn.com/2021/08/09/world/global-climate-change-report-un-ipcc/index.html Gariano, S. L., & F. Guzzetti, 2016. Landslides in a changing climate. Earth-Science Reviews, 162; 227252. Houghton, J., 2009. Global warming: the complete briefing. Cambridge university press. Ishtiaque, A., M. Shrestha, & N. Chhetri, 2017. Rapid urban growth in the Kathmandu Valley, Nepal: Monitoring land use land cover dynamics of a himalayan city with landsat imageries. Environments, 4(4); 72. LANDSAT 8 data users handbook, 2015. Department of the Interior US Geological Survey. Lustig, R. H., 2017. The hacking of the American mind: The science behind the corporate takeover of our bodies and brains. University of California. Retrieved 18 Mar 2022 from https://www.uctv.tv/shows/The-Hacking-of-the-American-Mind-with-Dr-Robert-Lustig-32572 Lustig, R. H., 2018. The hacking of the American mind: The science behind the corporate takeover of our bodies and brains. Penguin. Lynas, M., B. Z. Houlton, & S. Perry, 2021. Greater than 99% consensus on human caused climate change in the peer-reviewed scientific literature. Environmental Research Letters, 16(11); 114005.
304 DESERT, 27-2, 2022
Maleki, M., J. L. Van Genderen, S. M. Tavakkoli-Sabour, S. S. Saleh, & E. Babaee, 2020. Land use/cover change in Dinevar rural area of West Iran during 2000–2018 and its prediction for 2024 and 2030. Geogr. Tech, 15; 93-105. Mansourmoghaddam M, Ghafarian Malamiri HR, Arabi Aliabad F, Fallah Tafti M, Haghani M, Shojaei, S. 2022. The Separation of the Unpaved Roads and Prioritization of Paving These Roads Using UAV Images. Air, Soil and Water Research, 15. Mansourmoghaddam, M., H. R. Ghafarian Malamiri, I. Rousta, H. Olafsson, & H. Zhang, 2022. Assessment of Palm Jumeirah Island’s Construction Effects on the Surrounding Water Quality and Surface Temperatures during 2001–2020. Water, 14(4); 634. Mansourmoghaddam, M., I. Rousta, M. Zamani, M. H. Mokhtari, M. Karimi Firozjaei, & S. K. Alavipanah, 2021. Study and prediction of land surface temperature changes of Yazd city: assessing the proximity and changes of land cover. Journal of RS and GIS for Natural Resources, 12(4); 1-27. Mansourmoghaddam, M., I. Rousta, M. S. Zamani, M. H. Mokhtari, M. Karimi Firozjaei, & S. K. Alavipanah, 2022. Investigating And Modeling the Effect of The Composition and Arrangement of The Landscapes of Yazd City on The Land Surface Temperature Using Machine Learning and Landsat-8 and Sentinel-2 Data. Iranian Journal of Remote Sensing & GIS. Mutiibwa, D., S. Strachan, & T. Albright, 2015. Land surface temperature and surface air temperature in complex terrain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(10); 4762-4774. Nda, M., M. S. Adnan, K. A. Ahmad, N. Usman, M. A. M. Razi, & Z. Daud, 2018. A review on the causes, effects and mitigation of climate changes on the environmental aspects. International Journal of Integrated Engineering, 10(4). Nelson, E. J., P. Kareiva, M. Ruckelshaus, K. Arkema, G. Geller, E. Girvetz, . . . W. Reid, 2013. Climate change's impact on key ecosystem services and the human well‐being they support in the US. Frontiers in Ecology and the Environment, 11(9); 483-893. Oke, T. R., 2002. Boundary layer climates. Routledge. Pal, S., & S. Ziaul, 2017. Detection of land use and land cover change and land surface temperature in English Bazar urban centre. The Egyptian Journal of Remote Sensing and Space Science, 20(1); 125145. Paola, J. D., & R. A. Schowengerdt, 1995. A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification. IEEE Transactions on Geoscience and remote sensing, 33(4); 981-996. Qin, Z., & A. Karnieli, 1999. Progress in the remote sensing of land surface temperature and ground emissivity using NOAA-AVHRR data. International journal of remote sensing, 20(12); 2367-2393. Ramírez, J. A., & B. Finnerty, 1996. CO 2 and temperature effects on evapotranspiration and irrigated agriculture. Journal of irrigation and drainage engineering, 122(3); 155-163. Riebeek, H., 2010. Global warming: Feature articles. Seneviratne, S., N. Nicholls, D. Easterling, C. Goodess, S. Kanae, J. Kossin, . . . M. Rahimi, 2012. Changes in climate extremes and their impacts on the natural physical environment. Sexton, J. O., D. L. Urban, M. J. Donohue, & C. Song, 2013. Long-term land cover dynamics by multitemporal classification across the Landsat-5 record. Remote sensing of environment, 128; 246-258. Strahler, A. H., 1980. The use of prior probabilities in maximum likelihood classification of remotely sensed data. Remote sensing of Environment, 10(2); 135-163. Sultana, S., & A. Satyanarayana, 2018. Urban heat island intensity during winter over metropolitan cities of India using remote-sensing techniques: Impact of urbanization. International journal of remote sensing, 39(20); 6692-6730. USGS, 2014. OLI and TIRS Calibration Notices. In Landsat 8 Reprocessing to Begin February 3, 2014. Weber, E. U., & P. C. Stern, 2011. Public understanding of climate change in the United States. American Psychologist, 66(4); 315. Wei, W., & J. M. Mendel, 2000. Maximum-likelihood classification for digital amplitude-phase modulations. IEEE transactions on Communications, 48(2); 189-193. Wuebbles, D. J., D. W. Fahey, & K. A. Hibbard, 2017. Climate science special report: fourth national climate assessment, volume I. Xie, Z., S. Wu, G. Liu, & Z. Fang. (2009). Infrared face recognition based on radiant energy and curvelet transformation. 2009 Fifth International Conference on Information Assurance and Security,
The reciprocal effect of Global warming and climatic change (new perspective) 305
Yusuf, Y. A., B. Pradhan, & M. O. Idrees, 2014. Spatio-temporal assessment of urban heat island effects in Kuala Lumpur metropolitan city using landsat images. Journal of the Indian Society of Remote Sensing, 42(4); 829-837. Zahran, S., S. D. Brody, H. Grover, & A. Vedlitz, 2006. Climate change vulnerability and policy support. Society and Natural Resources, 19(9); 771-789. Zare Naghadehi, S., M. Asadi, M. Maleki, S.-M. Tavakkoli-Sabour, J. L. Van Genderen, & S.-S. Saleh, 2021. Prediction of Urban Area Expansion with Implementation of MLC, SAM and SVMs’ Classifiers Incorporating Artificial Neural Network Using Landsat Data. ISPRS International Journal of GeoInformation, 10(8); 513. Zhang, T. C., & R. Y. Surampalli. (2013). Impact of greenhouse gas emissions and climate change. In Climate Change Modeling, Mitigation, and Adaptation (pp. 92-108). American Society of Civil Engineers (ASCE). Zhongming, Z., L. Linong, Y. Xiaona, Z. Wangqiang, & L. Wei, 2021. AR6 Climate Change 2021: The Physical Science Basis. Ziaul, S., & S. Pal, 2016. Image based surface temperature extraction and trend detection in an urban area of West Bengal, India. Journal of Environmental Geography, 9(3-4); 13-25.
تعداد مشاهده مقاله: 1,210
تعداد دریافت فایل اصل مقاله: 734