Estimation Soil Adjusted Vegetation Index surface energy balance By analyzing their relationship through linear regression(Case Study: Nazarabad City)

Asghari Sarasekanrood, sayyad; Faal Naziri, Mehdi

[Home ] [Archive]

[ فارسی ]

Main Menu

Home

Journal Information

Articles archive

For Authors

For Reviewers

Registration

Contact us

Site Facilities

Search in website

Receive site information

Volume 22, Issue 77 (5-2022)

جغرافیایی 2022, 22(77): 15-34

Back to browse issues page

Estimation Soil Adjusted Vegetation Index surface energy balance By analyzing their relationship through linear regression(Case Study: Nazarabad City)

Sayyad Asghari Sarasekanrood ^*

¹, Mehdi Faal Naziri¹

1- University of Mohaghegh Ardabili

Abstract: (2747 Views)

Temperature is one of the main factors influencing urban planning because it guides the type of facilities available in cities and even determines the urban structure, shape and texture. On the other hand, increasing vegetation cover is one of the most effective strategies to reduce urban climate impacts. In the present study, the land energy balance algorithm was used to achieve land surface temperature and the soil vegetation index of Nazarabad city was used to estimate plant poisoning. For this purpose, Landsat satellite images (TM-OLI), years (2000-2019) were used. First, the relevant images were obtained and the necessary preparations were made. Then, the object-oriented classification was performed. Linear regression analysis was used to estimate the correlation between surface temperature and vegetation. Surface temperature results showed that vegetation areas such as agriculture and rangelands averaged 32 and 34 ° C for 2000 and 2019, respectively. However, during these years, vegetation-free areas such as urban and wilderness areas that were devoid of vegetation have averaged 36 and 39 degrees Celsius, indicating the effect of vegetation on surface temperatures. Also in estimating the correlation between vegetation and land surface temperature, it can be said that there is a strong correlation between the data. Independent variables have been explained which show high value and the model is significant with 0.95% confidence and is able to express changes based on available data so it can be concluded that this model has high accuracy for this study.

Keywords: Soil Adjusted Vegetation Index, surface energy balance, Linear regression, Object-oriented classification, Landsat images

Full-Text [PDF 1670 kb] (574 Downloads)

Type of Study: Research | Subject: Special
Received: 2019/11/14 | Accepted: 2019/12/18 | Published: 2022/05/23

References

1. Ahmadi, M., Ashour Lu, D., Narrangi Fard, M., (2015), "Temporal-spatial variations of thermal and utility patterns of Shiraz city using TM & ETM sensor data", Iranian Long Distance Measurement and GIS, 4: 55-68. ]In Persian[.

2. Allen, R., Tasumi, M., Trezza, R., Wim, B., (2002), "SEBAL: Surface energy balance Algorithms for land", Version 1.0, Funded by a NASA EOSDIS/Synergy Grant from the Raytheon Company through The Idaho Department of Water Resources. ]In[: https://www.academia.edu/20197535/Algoritmo_SEBAL.

3. Bannari, A., Morin, D., Bonn, F., Huete, A. R., (1995), "A review of vegetation indices", Journal of remote sensing Reviews, 13: 95-120. [DOI:10.1080/02757259509532298]

4. Bastiaanssen, W., Menenti, M., Feddes, R., Holtslag, A., (1998), "A remote sensing surface energy balance algorithm for land (SEBAL), 1 formulation", Journal of Hydrology, 212: 198-212. [DOI:10.1016/S0022-1694(98)00253-4]

5. Carlini, M., (2006), "Morphologie et hydrodynamique des plans d'eau: Le cas des étangs-lacs en Limousin", phd theses, Université de Limoge: Limoge.

6. Congalton, R. G., Green, K., (2009), "Assessing the accuracy of remotely sensed data principles and practices, CRC Press, Boca Raton: Florida, 131-139. [DOI:10.1201/9781420055139]

7. Ebrahimi, Hojat, G., Al-Madarsi, A., Ramasht, M., (2016), "Estimation of land surface temperature and Impact of vegetation on surface temperature using modis images (Case Study: Tuyserkan Basin)", Journal of Geography, 4: 128-149. ]In Persian[.

8. Farhadi Bansouleh, B., Karimi, A. R., Hesadi., H., (2016), "Estimation of ActualEvapotranspiration in Mahidasht using SEBS Algorithm and LANDSAT Images", Journal of Water and Soil, 30 (3(: 706-716. ]In Persian[.

9. Feizizadeh, J., Nazimfar-Bakhtiar, F., (2009), "The use of remote sensing data in detecting urban land use changes case study of tabriz green space", Journal of Fine Arts, 34: 17-24. ]In Persian[.

10. Huete, A. R., (1988), "A soil-adjusted vegetation index SAVI", Journal of Remote Sensing of Environment, 25: 295-309. [DOI:10.1016/0034-4257(88)90106-X]

11. Li, Y. Y., Zhang, H., Kainz, W., (2012), "Monitoring Patterns of Urban heat island of the fast - growing Shanghai metropolis, China: using time-series of Land sat TM/ETM+ data", International Journal of Applied Earth Observation and GeoInformation, 19: 127-138. [DOI:10.1016/j.jag.2012.05.001]

12. Lillesand, ‎T. M., Kiefer, ‎R. W., Chipman, J. W., (2008), "Remote sensing and Image Interpretation", New York: John Wiley & Sons, Inc., 6th Ed,PP. 791-812.

13. Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H., Sorooshian, S., (1994), "A modified soil adjusted vegetation index", Journal of Remote Sensing of Environment, 48: 119-126. [DOI:10.1016/0034-4257(94)90134-1]

14. Rezaei, B., Feizizadeh, M., Hashem, B., (2009), "Investigation and Evaluation of Trends in forest surface change using remote sensing and GIS case study of arasbaran forests 1987-2005", Geographical Research, 62: 143-159. ]In Persian[.

15. Richardson, A. J., Wieg, C. L., (1977)," Distinguishing vegetation from soil background information", Photogrammetric Engineering & Remote Sensing, 43: 154-168.

16. Ronald, C., Estoque, M., Yuji, M. S. W., (2018), "Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia", National Library of Medicine, U.S, 577 )15(: 349-359. [DOI:10.1016/j.scitotenv.2016.10.195]

17. Rondeaux, G., Steven, M., Baret, F., (1996), "Optimization of soil-adjusted vegetation indices" , Journal of Remote Sensing of Environment, 55: 95-107. [DOI:10.1016/0034-4257(95)00186-7]

18. Roshanak, D., Amin, H., Ebrahimi, M., (2008), "An estimate of the darsd of Pushash Ghayahi, the Khashk district, central Iran, using the pictures of Mahwara, i.e." Volume 2, Tehran: Samt. Pp. 25-38. ]in Persian[.

19. Sadeghian, S., Rajabi, A., Shadmanfar, M., (2021), "Bersi roshhai accounting demai sat zamin az tsawer mahwara i reading the suppliers of astan-qom, Geographical Space, 21: 141-154. ]In Persian[.

20. Zhang, Y., Chen, L., Wang, Y., Chen, L., Yao, F., Wu, P., Zhang, T., (2015), "Research on the contribution of urban land Surface moisture to the alleviation effect of urban land surface heat based on Land Sat 8 data", Remote Sensing, 8 (7(: 107-121. [DOI:10.3390/rs70810737]

21. Sobrino, J. A., (2004), "Single-channel and two-channel methods for land surface temperature retrieval from DAIS data and its application to the Barrax site", Int. J. Remotete Sensing, 25 (1): 215-230. [DOI:10.1080/0143116031000115210]

22. Valizadeh Kamran, Kh., Gholamnia, Kh., And Einali, G., Mousavi, S., (2017), "Estimation of surface temperature and extraction of thermal islands using separate window algorithm and multivariate regression analysis (Case study of Zanjan)", Urban Research and Planning, 30 (8): 35-50. ]In Persian[.

23. Zhang, Q., Ben, Y., (2015), "Evaluation of urban expansion and its impact on surface temperature in Beijing", China, Joint Urban remote Sensing Event munich, germani, 11-13: 357-360.

Send email to the article author

Add your comments about this article

‎ 20.1001.1.1735322.1401.22.77.4.1

Mendeley

Zotero

RefWorks

Asghari Sarasekanrood S, Faal Naziri M. Estimation Soil Adjusted Vegetation Index surface energy balance By analyzing their relationship through linear regression(Case Study: Nazarabad City). جغرافیایی 2022; 22 (77) :15-34
URL: http://geographical-space.iau-ahar.ac.ir/article-1-3572-en.html

Rights and permissions
	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Volume 22, Issue 77 (5-2022)

Back to browse issues page

Persian site map - English site map - Created in 0.19 seconds with 37 queries by YEKTAWEB 4657