Analysis on Thermal Islands Effectors in Ramadi City, Iraq Using Multi-temporal Landsat Images

Authors

  • Ismael Abbas Hurat unversity of anbar educatin college for women Department of geography

DOI:

https://doi.org/10.31973/aj.v1i135.983

Keywords:

Thermal Islands, Landsat, Spectral Indices, Remote Sensing, GIS

Abstract

This paper analyzes the effects of urban density, vegetation cover, and water body on thermal islands measured by land surface temperature in Al Anbar province, Iraq using multi-temporal Landsat images. Images from Landsat 7 ETM and Landsat 8 OLI for the years 2000, 2014, and 2018 were collected, pre-processed, and anal yzed. The results suggested that the strongest correlation was found between the Normalized Difference Built-up Index (NDBI) and the surface temperature. The correlation between the Normalized Difference Vegetation Index (NDVI) and the surface temperature was slightly weaker compared to that of NDBI. However, the weakest correlation was found between the Normalized Difference Water Index (NDWI) and the temperature. The results obtained in this research may help the decision makers to take actions to reduce the effects of thermal islands by looking at the details in the produced maps and the analyzed values of these spectral indices.

Downloads

Download data is not yet available.

References

Alexander, P. J., O’Dwyer, B., Brennan, M., Mills, G., & Lynch, P. (2017). Land surface temperature climatology over urban surfaces: A blended approach. In 2017 Joint Urban Remote Sensing Event (JURSE) (pp. 1–4). IEEE. doi:10.1109/JURSE.2017.7924599

Bernardo, N., Watanabe, F., Rodrigues, T., & Alcântara, E. (2017). Atmospheric correction issues for retrieving total suspended matter concentrations in inland waters using OLI/Landsat-8 image. Advances in Space Research, 59(9), 2335–2348. doi:10.1016/j.asr.2017.02.017

Centre for Geoinformatics & Planetary Studies, Dept. of Geology, Periyar University, Salem, Tamilnadu, India, S., A., C.R., P., & Centre for Geoinformatics & Planetary Studies, Dept. of Geology, Periyar University, Salem, Tamilnadu, India. (2016). Statistical Correlation between Land Surface Temperature (LST) and Vegetation Index (NDVI) using Multi-Temporal Landsat TM Data. International Journal of Advanced Earth Science and Engineering, 5(1), 333–346. doi:10.23953/cloud.ijaese.204

Comarazamy, D. E., Gonzalez, J. E., & Luvall, J. C. (2015). Quantification and mitigation of long-term impacts of urbanization and climate change in the tropical coastal city of San Juan, Puerto Rico. International Journal of Low-Carbon Technologies, 10(1), 87–97. doi:10.1093/ijlct/ctt059

He, C., Gao, B., Huang, Q., Ma, Q., & Dou, Y. (2017). Environmental degradation in the urban areas of China: Evidence from multi-source remote sensing data. Remote Sensing of Environment, 193, 65–75. doi:10.1016/j.rse.2017.02.027

Hilker, T. (2018). Surface reflectance/bidirectional reflectance distribution function. In Comprehensive Remote Sensing (Vol. 3, pp. 2–8). Elsevier. doi:10.1016/B978-0-12-409548-9.10347-1

Lavender, S., & Lavender, A. (2015). Practical handbook of remote sensing. CRC Press. doi:10.1201/b19044

Morrow, J. G., Huggins, D. R., & Reganold, J. P. (2017). Climate change predicted to negatively influence surface soil organic matter of dryland cropping systems in the inland pacific northwest, USA. Frontiers in Ecology and Evolution, 5. doi:10.3389/fevo.2017.00010

Zhang, M., Bai, L., Wu, Z., & Gong, Y. (2016). Bidirectional reflection distribution function modeling of material surface in different temperature. In 2016 11th International Symposium on Antennas, Propagation and EM Theory (ISAPE) (pp. 713–715). IEEE. doi:10.1109/ISAPE.2016.7834056

Zhu, Z., Woodcock, C. E., Holden, C., & Yang, Z. (2015). Generating synthetic Landsat images based on all available Landsat data: Predicting Landsat surface reflectance at any given time. Remote Sensing of Environment, 162, 67–83. doi:10.1016/j.rse.2015.02.009

Downloads

Published

2020-12-12

Issue

Section

Geography

How to Cite

Analysis on Thermal Islands Effectors in Ramadi City, Iraq Using Multi-temporal Landsat Images. (2020). Al-Adab Journal, 1(135), 67-78. https://doi.org/10.31973/aj.v1i135.983

Publication Dates

Similar Articles

1-10 of 72

You may also start an advanced similarity search for this article.