SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.


Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
Paper Publishing WeChat
Book Publishing WeChat

Article citations


Dash, P., Göttsche, F.-M., Olesen, F.-S. and Fischer, H. (2002) Land Surface Temperature and Emissivity Estimation from Passive Sensor Data: Theory and Practice-Current Trends. International Journal of Remote Sensing, 23, 2563-2594.

has been cited by the following article:

  • TITLE: Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Onitsha, South East Nigeria

    AUTHORS: Ademola Akinbobola

    KEYWORDS: Land Surface Temperature, Land Use/Land Cover, Landsat, Onisha

    JOURNAL NAME: Atmospheric and Climate Sciences, Vol.9 No.2, April 24, 2019

    ABSTRACT: The increasing urbanization generally is brought about by many eco-environmental problems, such as the drastic change of land use and development of urban heat island. This study identified the pattern of land cover changes in Onitsha, South East Nigeria, and assessed the trend in temperature over the area from 1986 to 2016, simulated the land cover changes for 2030 and 2044, and estimated their impacts on land surface temperature (LST). These were with the view to determining the effects of changes in land use/cover on the LST in the area. Primary and secondary data were used for the study. The primary data were coordinates of geographic features within the study area, collected through the use of global positioning system. The secondary data were minimum and maximum temperature data from the Nigerian Meteorological Agency (NIMET), high-resolution Quick-bird imagery, Landsat TM/ETM imageries for four epochs (1986, 2002, and 2016) with path and row of 189 and 56. Individual components (bare surface, built-up, vegetation and surface water bodies) in the study area were extracted from the images. Radiometric correction was first performed (for 2016 landsat imagery) to fill the line scan corrector (LSC) gaps using Focal Analysis tool in ERDAS Imagine 14.0. This was followed with clipping of the satellite imagery to extract only those portions that are within the boundary of the study area. Supervised image classification was done for the three series of remotely sensed imageries to extract the spatial pattern of land cover change. The results revealed that the study area has been growing to a relatively compact urban agglomeration. The concentration of built-up area at the western and the central part of the study area has been getting larger and more aggregated. Built-up area increased by 11.49% from 1986 to 2002 and 5.68% from 2002 to 2016 while vegetation decreased by 6.03% from 50.26% in 1986 to 44.23% in 2002. The decrease further continued from 44.23% in 2002 to 29.79% in 2016 (change of 14.44%). Expansion to spread into the sub-urban and rural communities bounding the metropolis, converting agricultural and green area to built-up areas. The land cover trend of the study area from the period of 1986-2016 shows dramatic changes for the dominant land cover types. The analyzed trend in temperature change shows that the central parts of the city have a temperature higher than the outlying parts. The results indicated that the average temperature of the study area increased from 24°C in 1986 to 28°C in 2016. The simulated land cover also showed a decreasing trend in vegetal cover. The study concluded that the increase in built-up area caused an annual increase in land surface temperature (0.31°C) over the study period.