Journal of Geoscience and Environment Protection

Volume 6, Issue 1 (January 2018)

ISSN Print: 2327-4336   ISSN Online: 2327-4344

Google-based Impact Factor: 0.98  Citations  

Analysis of the Relationship between Land Surface Temperature and Vegetation and Built-Up Indices in Upper-Hill, Nairobi

HTML  XML Download Download as PDF (Size: 2874KB)  PP. 1-16  
DOI: 10.4236/gep.2018.61001    1,216 Downloads   2,482 Views   Citations

ABSTRACT

Designing “liveable” cities as climate change effects are felt all over the world has become a priority to city authorities as ways are sought to reduce rising temperatures in urban areas. Urban Heat Island (UHI) effect occurs when there is a difference in temperature between rural and urban areas. In urban areas, impervious surfaces absorb heat during the day and release it at night, making urban areas warmer compared to rural areas which cool faster at night. This Urban Heat Island effect is particularly noticeable at night. Noticeable negative effects of Urban Heat Islands include health problems, air pollution, water shortages and higher energy requirements. The main objective of this research paper was to analyze the spatial and temporal relationship between Land Surface Temperature (LST) and Normalized Density Vegetation Index (NDVI) and Built-Up Density Index (BDI) in Upper-Hill, Nairobi Kenya. The changes in land cover would be represented by analyzing the two indices NDVI and BDI. Results showed the greatest increase in temperature within Upper-Hill of up to 3.96°C between the years 2015 and 2017. There was also an increase in impervious surfaces as indicated by NDVI and BDI within Upper-Hill and its surroundings. The linear regression results showed a negative correlation between LST and NDVI and a positive correlation with BDI, which is a better predictor of Land Surface Temperature than NDVI. Data sets were analyzed from Landsat imagery for the periods 1987, 2002, 2015 and 2017 to determine changes in land surface temperatures over a 30 year period and it’s relation to land cover changes using indices. Visual comparisons between Temperature differences between the years revealed that temperatures decreased around the urban areas. Minimum and maximum temperatures showed an increase of 1.6°C and 3.65°C respectively between 1987 and 2017. The comparisons between LST, NDVI and BDI show the results to be significantly different. The use of NDVI and BDI to study changes in land cover due to urbanization, reduces the time taken to manually classify moderate resolution satellite imagery.

Cite this paper

Mwangi, P. , Karanja, F. and Kamau, P. (2018) Analysis of the Relationship between Land Surface Temperature and Vegetation and Built-Up Indices in Upper-Hill, Nairobi. Journal of Geoscience and Environment Protection, 6, 1-16. doi: 10.4236/gep.2018.61001.

Cited by

[1] Impact of urbanization and land surface temperature changes in a coastal town in Kerala, India
2020
[2] Extents of Predictors for Land Surface Temperature Using Multiple Regression Model
2020
[3] Longitudinal study of land surface temperature (LST) using mono-and split-window algorithms and its relationship with NDVI and NDBI over selected metro cities of …
2020
[4] Regional urban environmental quality assessment and spatial analysis
2020
[5] Impact of Urban Forms on 3d Built-Up Intensity Expansion Rate from Aerial Stereo-Imagery
2020
[6] The urban heat island in an urban context: a case study of Mashhad, Iran
2019
[7] Land cover changes and its Implications on Urban Heat Island in Nairobi County: A GIS and Remote Sensing Approach.
2019
[8] Comparison of urban heat island effect in Jakarta and Surabaya, Indonesia
2019
[9] Análise da relação entre NDVI ea temperatura da superfície terrestre como técnica no planejamento urbano dos municípios
2019
[10] Analyzing the Spatial Relationship between Building Volumes and Land Surface Temperature in Upper-Hill, Nairobi, Kenya
2018

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.