In this project the student will explore the spectral signature of the solar irradiance within the tree canopy shade and the usage of the spectral information in understanding the canopy biophysical or chemical characteristics.
Department: Construction Management & Engineering
Supervised by: Dr. Stefan T. Smith
In the recent years the identification and mapping of vegetation towards the assessment of their ecosystem services, the dominant features of plant health and productivity and the structure of plant canopies is systematically conducted with the use of a diverse range of remote sensing sensors and platforms including satellites, UAVs and Lidars. However, remote sensing for vegetation monitoring can involve mixed pixels with contributions from vegetation and background surfaces, causing biases in signals and their interpretations, especially in low-density tree canopies. Compared to dense canopy forests, remote sensing applications in sparse conditions such as semi-arid forests and trees in urban areas need to consider multiple components within a pixel, e.g. shadows. This is seldom explicitly incorporated into remote sensing research and the contained spectral information is typically neglected. However, shadows might represent separate spectral signatures that could be used in image analysis. The student will use data collected during an experimental campaign in summer 2019 in the frame of the InfruTreeCity project, that studied the interactions between urban trees and the built environment. Seven containerized trees, representing urban trees, were placed in a controlled microenvironment at Hall Farm, University of Reading, in a circular arrangement and spectrometric measurements were conducted above the tree canopy and within the tree shade, along with measurements of surface temperature and canopy reflected irradiance. The student will investigate the spectral signature of the solar irradiance within the shade and will explore the usage of the spectral information in understanding the canopy biophysical or chemical characteristics.
A suggested time plan is given below. • review targeted sections of literature under supervisor’s guidance. (week 1). • Data analysis (weeks 2 to 5). • Writing of report and presenting the results at the research group meeting (week 6). The placement could comprise two periods, with the data analysis carried out in two blocks, the length of each block depending on how the project develops. In the first instance this could be considered as an equal split of 3 : 3 weeks.
Essential skills: • The student is expected to have a background in one or more of the following areas: environmental science/ mathematics/ physics/ meteorology/ engineering. • Competence with computers. • The student will need to be flexible, reliable and hardworking. • An understanding of the importance of the scientific method. • Willingness to attend the Energy and Environmental Engineering research group meetings. Desirable skills • A genuine interest and enthusiasm for the study of healthy indoor environments. • Previous experience of handling data and knowledge of statistics is desirable. • Previous experience in a computer programming language (e.g. Python, R, MATLAB)..
• The student will gain hands on experience in several stages of the research, including reviewing the literature, collecting and analyzing the data, using a model to further investigate the relevant processes, and presenting and writing up the results. • The supervisors will work with the student in meetings several times a week at all stages to provide training and expertise in each area. • General transferable skills to be developed include independent and team-working, computing and analytical skills, report writing and presentations skills.
Chancellors Building, flexible.
flexible
Thursday 01 June 2023 - Saturday 15 July 2023
The deadline to apply for this opportunity is Sunday 7th May 2023. Students should submit their CV and Cover Letter directly to the Project Supervisor (click on supervisor name at the top of the page for email). Successful candidates will be invited for an interview.