تحلیل فضایی مخاطرات محیطی

تحلیل فضایی مخاطرات محیطی

تغییرات دمای سطح زمین در شهر حله و ارتباط آن با تغییرات شاخص NDVI

نویسندگان
توفیق جاسم محمد
محمد رحمانی
کمیل عبدی
دانشگاه مازندران
چکیده
دمای محیط شهری یکی از پارامترهایی است که شهروندان هر لحظه با آن در ارتباط هستند. مطالعات نشان می­دهد که دمای کره زمین به دلیل تغییرات محیطی دائما در حال افزایش است. یکی از این پارامترهایی که بر افزایش دما تاثیر می­گذارد؛ رشد فیزیکی شهر و به تبع آن تخریب و از بین رفتن پوشش گیاهی است. در این مطالعه، با استفاده از تصاویر ماهواره لندست برای سال­های 2001، 2011 و 2021؛ و اجرای الگوریتم تک­کانال، دمای سطح زمین در شهر حله عراق محاسبه و تغییرات آن مورد بررسی و تحلیل قرار گرفت. در طرف مقابل شاخص NDVI به عنوان یک شاخص پوشش گیاهی در تاریخ­های مذکور محاسبه و تغییرات آن با تغییرات دمایی سطح زمین مورد تحلیل قرار گرفت. نتایج کلی این تحقیق نشان داد که مساحت شهر حله در طی دوره مورد مطالعه حدودا دو برابر شده است و این موضوع باعث کاهش میزان پوشش گیاهی و افزایش دمای سطح زمین شده است. در پایان، همبستگی بین دمای سطح زمین و شاخص NDVI محاسبه شد که به­ترتیب برای سال­های 2001، 2011 و 2021 برابر با 46.92، 44.35 و 52.98 درصد بود. این موضوع نشان از رابطه قوی بین این دو پارامتر و تاثیر کاهش پوشش گیاهی بر افزایش دمای سطح زمین می­دهد.
کلیدواژه‌ها
دمای سطح زمین
پوشش گیاهی
NDVI
رشد شهر
شهر حله

عنوان مقاله English

Changes in ground surface temperature in the city of Halle and its relationship with changes in the NDVI index

نویسندگان English

tofigh jasem mohammad
mohammad rahmani
komeil abdi
Mazandaran University
چکیده English

Changes in ground surface temperature in the city of Halle and its relationship with changes in the NDVI index

abstract

The temperature of the urban environment is one of the parameters that citizens are in contact with at any moment. Studies show that the global temperature is constantly increasing due to environmental changes. One of these parameters that affect the increase in temperature; The physical growth of the city and its consequent destruction and loss of vegetation. In this study, using Landsat satellite images for the years 2001, 2011 and 2021; and the implementation of the single-channel algorithm, the surface temperature of the ground in the Iraqi city of Halla was calculated and its changes were investigated and analyzed. On the other hand, the NDVI index was calculated as a vegetation index on the mentioned dates and its changes were analyzed with the temperature changes of the earth's surface. The general results of this research showed that the area of the city of Halle has doubled during the study period, and this has caused a decrease in the amount of vegetation and an increase in the temperature of the earth's surface. In the end, the correlation between the surface temperature and the NDVI index was calculated, which was equal to 46.92, 44.35 and 52.98% for the years 2001, 2011 and 2021, respectively. This issue shows the strong relationship between these two parameters and the effect of the reduction of vegetation on the increase in the temperature of the earth's surface.



Key words: Earth surface temperature, vegetation, NDVI, city growth, Halle city

کلیدواژه‌ها English

Earth surface temperature
Vegetation
NDVI
city growth
Halle city
2. Ahmed, M. R., Hassan, Q. K., Abdollahi, M., & Gupta, A. (2020). Processing of near real time land surface temperature and its application in forecasting forest fire danger conditions. Sensors, 20(4), 984.
3. Bren d’Amour, C., Reitsma, F., Baiocchi, G., Barthel, S., Güneralp, B., Erb, K. H., ... & Seto, K. C. (2017). Future urban land expansion and implications for global croplands. Proceedings of the National Academy of Sciences, 114(34), 8939-8944.
4. Chabuk, A., Al-Ansari, N., Hussain, H. M., Knutsson, S., & Pusch, R. (2016). Landfill site selection using geographic information system and analytical hierarchy process: A case study Al-Hillah Qadhaa, Babylon, Iraq. Waste Management & Research, 34(5), 427-437.
5. Chabuk, A., Al-Ansari, N., Hussain, H. M., Knutsson, S., Pusch, R., & Laue, J. (2017). Combining GIS applications and method of multi-criteria decision-making (AHP) for landfill siting in Al-Hashimiyah Qadhaa, Babylon, Iraq. Sustainability, 9(11), 1932.
6. Chen, L., & Dirmeyer, P. A. (2019). Differing responses of the diurnal cycle of land surface and air temperatures to deforestation. Journal of Climate, 32(20), 7067-7079.
7. Chen, W., Yue, W., Mu, J., & Xu, S. (2022). Waterbody loss due to urban expansion of large Chinese cities in last three decades.
8. Choudhury, D., Das, K., & Das, A. (2019). Assessment of land use land cover changes and its impact on variations of land surface temperature in Asansol-Durgapur Development Region. The Egyptian Journal of Remote Sensing and Space Science, 22(2), 203-218.
9. Dehingia, H., Das, R. R., Rahaman, S. A., Surendra, P., & Hanjagi, A. D. (2022). DECADAL TRANSFORMATION OF LAND USE-LAND COVER AND FUTURE SPATIAL EXPANSION IN BANGALORE METROPOLITAN REGION, INDIA: OPEN-SOURCE GEOSPATIAL MACHINE LEARNING APPROACH. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 589-595.
10. Dwivedi, A., & Mohan, B. K. (2018). Impact of green roof on micro climate to reduce Urban Heat Island. Remote Sensing Applications: Society and Environment, 10, 56-69.
11. Falahatkar, S., Hosseini, S. M., & Soffianian, A. R. (2011). The relationship between land cover changes and spatial-temporal dynamics of land surface temperature. Indian Journal of Science and Technology, 4(2), 76-81.
12. Felde, G. W., Anderson, G. P., Cooley, T. W., Matthew, M. W., Berk, A., & Lee, J. (2003, July). Analysis of Hyperion data with the FLAASH atmospheric correction algorithm. In IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No. 03CH37477) (Vol. 1, pp. 90-92). IEEE.
13. Ferreira, L. S., & Duarte, D. H. S. (2018, August). Land surface temperature, vegetation cover and urban morphology over different local climate zones in São Paulo Metropolitan Region. In 10th International Conference on Urban Climate/14th Symposium on the Urban Environment. AMS.
14. Fleck, R., Gill, R. L., Saadeh, S., Pettit, T., Wooster, E., Torpy, F., & Irga, P. (2022). Urban green roofs to manage rooftop microclimates: A case study from Sydney, Australia. Building and Environment, 209, 108673.
15. Fonseka, H. P. U., Zhang, H., Sun, Y., Su, H., Lin, H., & Lin, Y. (2019). Urbanization and its impacts on land surface temperature in Colombo metropolitan area, Sri Lanka, from 1988 to 2016. Remote Sensing, 11(8), 957.
16. Guangmeng, G., & Mei, Z. (2004). Using MODIS land surface temperature to evaluate forest fire risk of northeast China. IEEE Geoscience and Remote sensing letters, 1(2), 98-100.
17. Guo, A., Yang, J., Sun, W., Xiao, X., Cecilia, J. X., Jin, C., & Li, X. (2020). Impact of urban morphology and landscape characteristics on spatiotemporal heterogeneity of land surface temperature. Sustainable Cities and Society, 63, 102443.
18. Guo, L., Gong, H., Ke, Y., Zhu, L., Li, X., Lyu, M., & Zhang, K. (2021). Mechanism of land subsidence mutation in Beijing plain under the background of urban expansion. Remote Sensing, 13(16), 3086.
19. Guo, Z., Wang, S. D., Cheng, M. M., & Shu, Y. (2012). Assess the effect of different degrees of urbanization on land surface temperature using remote sensing images. Procedia Environmental Sciences, 13, 935-942.
20. Hashim, A. H., Jasim, O. Z., & Salih, M. M. (2021, April). Developing and establishing a geospatial database of the religious endowments in Hilla, Iraq. In IOP Conference Series: Earth and Environmental Science (Vol. 754, No. 1, p. 012026). IOP Publishing.
21. Jiménez-Muñoz, J. C., Sobrino, J. A., Skoković, D., Mattar, C., & Cristobal, J. (2014). Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geoscience and remote sensing letters, 11(10), 1840-1843.
22. Jwad, Z. A., & Hasson, S. T. (2018, October). An optimization approach for waste collection routes based on GIS in Hillah-Iraq. In 2018 International Conference on Advanced Science and Engineering (ICOASE) (pp. 60-63). IEEE.
23. Kafy, A. A., Rahman, A. F., Al Rakib, A., Akter, K. S., Raikwar, V., Jahir, D. M. A., ... & Kona, M. A. (2021). Assessment and prediction of seasonal land surface temperature change using multi-temporal Landsat images and their impacts on agricultural yields in Rajshahi, Bangladesh. Environmental Challenges, 4, 100147.
24. Kim, H. M., Kim, B. K., & You, K. S. (2005). A statistic correlation analysis algorithm between land surface temperature and vegetation index. Journal of Information Processing Systems, 1(1), 102-106.
25. Koch, M., Gaber, A., Darwish, N., Bateman, J., Gopal, S., & Helmi, M. (2019, July). Estimating Land Subsidence in Relation to Urban Expansion in Semarang City, Indonesia, Using InSAR and Optical Change Detection Methods. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 9686-9689). IEEE.
26. Krayenhoff, E. S., Moustaoui, M., Broadbent, A. M., Gupta, V., & Georgescu, M. (2018). Diurnal interaction between urban expansion, climate change and adaptation in US cities. Nature Climate Change, 8(12), 1097-1103.
27. Kumar, D., & Shekhar, S. (2015). Statistical analysis of land surface temperature–vegetation indexes relationship through thermal remote sensing. Ecotoxicology and environmental safety, 121, 39-44.
28. Lhissou, R., El Harti, A., Maimouni, S., & Adiri, Z. (2020). Assessment of the image-based atmospheric correction of multispectral satellite images for geological mapping in arid and semi-arid regions. Remote Sensing Applications: Society and Environment, 20, 100420.
29. Li, X., & Gong, P. (2016). Urban growth models: progress and perspective. Science bulletin, 61(21), 1637-1650.
30. Li, Z. L., Tang, B. H., Wu, H., Ren, H., Yan, G., Wan, Z., ... & Sobrino, J. A. (2013). Satellite-derived land surface temperature: Current status and perspectives. Remote sensing of environment, 131, 14-37.
31. Maleki, M., Ahmadi, Z., & Dosti, R. (2019). Kermanshah land surface temperature changes in during 1393-1397 periods. Geography and Human Relationships, 2(3), 309-319.
32. Maleki, M., Van Genderen, J. L., Tavakkoli-Sabour, S. M., Saleh, S. S., & Babaee, E. (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.
33. McDonald, R. I., Mansur, A. V., Ascensão, F., Crossman, K., Elmqvist, T., Gonzalez, A., ... & Ziter, C. (2020). Research gaps in knowledge of the impact of urban growth on biodiversity. Nature Sustainability, 3(1), 16-24.
34. Mo, Y., Xu, Y., Chen, H., & Zhu, S. (2021). A review of reconstructing remotely sensed land surface temperature under cloudy conditions. Remote Sensing, 13(14), 2838.
35. Muis, S., Güneralp, B., Jongman, B., Aerts, J. C., & Ward, P. J. (2015). Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data. Science of the Total Environment, 538, 445-457.
36. Neinavaz, E., Skidmore, A. K., & Darvishzadeh, R. (2020). Effects of prediction accuracy of the proportion of vegetation cover on land surface emissivity and temperature using the NDVI threshold method. International Journal of Applied Earth Observation and Geoinformation, 85, 101984.
37. Pech, L., & Lakes, T. (2017). The impact of armed conflict and forced migration on urban expansion in Goma: Introduction to a simple method of satellite-imagery analysis as a complement to field research. Applied geography, 88, 161-173.
38. Portela, C. I., Massi, K. G., Rodrigues, T., & Alcântara, E. (2020). Impact of urban and industrial features on land surface temperature: Evidences from satellite thermal indices. Sustainable Cities and Society, 56, 102100.
39. Reidsma, P., Tekelenburg, T., Van den Berg, M., & Alkemade, R. (2006). Impacts of land-use change on biodiversity: An assessment of agricultural biodiversity in the European :union:. Agriculture, ecosystems & environment, 114(1), 86-102.
40. Rimal, B., Sloan, S., Keshtkar, H., Sharma, R., Rijal, S., & Shrestha, U. B. (2020). Patterns of historical and future urban expansion in Nepal. Remote Sensing, 12(4), 628.
41. Singh, R. K., Sinha, V. S. P., Joshi, P. K., & Kumar, M. (2020). Modelling Agriculture, Forestry and Other Land Use (AFOLU) in response to climate change scenarios for the SAARC nations. Environmental Monitoring and Assessment, 192(4), 1-18.
42. Sruthi, S., & Aslam, M. M. (2015). Agricultural drought analysis using the NDVI and land surface temperature data; a case study of Raichur district. Aquatic Procedia, 4, 1258-1264.
43. Sun, Q., Wu, Z., & Tan, J. (2012). The relationship between land surface temperature and land use/land cover in Guangzhou, China. Environmental Earth Sciences, 65(6), 1687-1694.
44. Tiepolo, M., & Galligari, A. (2021). Urban expansion-flood damage nexus: evidence from the Dosso Region, Niger. Land Use Policy, 108, 105547.
45. Tran, D. X., Pla, F., Latorre-Carmona, P., Myint, S. W., Caetano, M., & Kieu, H. V. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119-132.
46. Valor, E., & Caselles, V. (1996). Mapping land surface emissivity from NDVI: Application to European, African, and South American areas. Remote sensing of Environment, 57(3), 167-184.
47. van Vliet, J. (2019). Direct and indirect loss of natural area from urban expansion. Nature Sustainability, 2(8), 755-763.
48. Vasanthawada, S. R. S., Puppala, H., & Prasad, P. R. C. (2022). Assessing impact of land-use changes on land surface temperature and modelling future scenarios of Surat, India. International Journal of Environmental Science and Technology, 1-14.
49. Wen, Y., Liu, X., Bai, Y., Sun, Y., Yang, J., Lin, K., ... & Yan, Y. (2019). Determining the impacts of climate change and urban expansion on terrestrial net primary production in China. Journal of environmental management, 240, 75-83.
50. Winckler, J., Lejeune, Q., Reick, C. H., & Pongratz, J. (2019). Nonlocal effects dominate the global mean surface temperature response to the biogeophysical effects of deforestation. Geophysical Research Letters, 46(2), 745-755.
51. Yang, J., Ren, J., Sun, D., Xiao, X., Xia, J. C., Jin, C., & Li, X. (2021). Understanding land surface temperature impact factors based on local climate zones. Sustainable Cities and Society, 69, 102818.
52. Zare Naghadehi, S., Asadi, M., Maleki, M., Tavakkoli-Sabour, S. M., Van Genderen, J. L., & Saleh, S. S. (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 Geo-Information, 10(8), 513.