PhD Candidates
PhD Student for Research Project
Research Topic: Remote Sensing data fusion at different levels for applications within Digital Earth.
Overview:
In the beginning of next year the Institute of Geospatial Science and Technology (INSTeG), a COE of the Universiti Teknologi Malaysia will launch a new research project under the leadership of Prof. Dr.-Ing. Christine Pohl. For this project we are looking for a PhD candidate to pursue her/his PhD research within 2.5 – 3 years.
The PhD research will be embedded in a MOSTI and UTM funded project on the “Development of suitable image fusion techniques to increase the usability of RazakSAT-2”. Within this project the candidate will investigate the combination of optical and radar remote sensing data at three different fusion levels: 1. Pixel level, 2. Feature level, and 3. Information level.
Remote sensing imagery has become more and more useful for topographic map updating in the past decade. With the availability of higher resolution data in terms of spatial content of satellite images information extraction meets needs of larger scale mapping. A lot of attention is being paid to change detection for map updating using remote sensing data. In many cases images of sensors operating in the visible range of the electromagnetic spectrum are used to extract the relevant features. In the tropics, however, this is very difficult due to the persistent cloud cover that exists in these areas. Therefore the PhD candidate will study the means to integrate synthetic aperture radar (SAR) data in the fusion process. SAR sensors are capable of acquiring images independent of weather conditions and daylight since the microwaves penetrate clouds and provide information on surface texture, structure, soil moisture and other parameters that optical sensors are not able to obtain. The complementary characteristics of the two sensor types play a major role in the benefit of VIR/SAR fusion in remote sensing. The value adding is meant in terms of information extraction capability, reliability and increased accuracy. Successful image fusion produces data that results in other, better or additional information that cannot be extracted from each single image alone. Due to the different nature of the two sensor types all three fusion levels will be explored to obtain best results.
The Project will be launched early next year. Working language is English, the doctoral thesis will be written in English.
Requirements for Applicant:
- MSc in remote sensing, geosciences or related disciplines
- Experience with remote sensing digital image processing software, preferably ENVI, PCI Geomatics or ERDAS IMAGINE
- Programming skills
- Proficiency in English language, written and spoken
- Willingness to work in an international team
Compulsory Attachments for Application:
- Curriculum vitae
- Copy of university degree
- Letter of motivation
- Report on previous work in remote sensing
- Statement why the applicant wants to work within INSTeG
Contact for further questions and application:
Prof. Dr.-Ing. Christine Pohl
Institute of Geospatial Sciences and Technology (INSTeG)
Universiti Teknologi Malaysia
81310 UTM Johor Bahru, Malaysia
Phone: +6 (0) 14 2755021
Email: c.pohl@utm.my
Website: https://research.utm.my/insteg/coe-members/christine-biography/
Scopus ID: 7102763531
LinkedIn ID: 235792713
SkypeID: chrispo2013
