Imaging Science Thesis Defense: Towards Optimization of Imaging Spectrometer Specifications
Imaging Science Ph.D. Thesis Defense
Towards Optimization of Imaging Spectrometer Specifications: A Comprehensive Assessment of a Complex Ecosystem
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MANISHA DAS CHAITY
Imaging Science PhD Candidate
Rochester Institute of Technology
Abstract:
The Greater Cape Floristic Region (GCFR) is one of the world’s most biodiverse regions, yet its ecosystems face growing threats from habitat loss, invasive species, altered fire regimes, and climate change. Monitoring how biodiversity changes across this vast and highly diverse landscape is essential for conservation, but remains challenging with remote sensing because the signals captured by imaging systems are influenced by complex variation in plant species, structure, and biophysical properties across spatial and spectral scales. These challenges are particularly pronounced in the fynbos, a hyper-diverse ecosystem where hundreds of plant species interact with light in complex ways and where fire plays a central role in shaping ecosystem recovery.
This dissertation investigates how remote sensing can be used to better understand and monitor biodiversity and post-fire recovery in the fynbos. The research combines field measurements of plant traits, high-resolution unmanned aerial system (UAS) imagery, and physics-based radiative transfer modeling within the Digital Imaging and Remote Sensing Image Generation (DIRSIG) framework. It examines the ability of remote sensing to distinguish vegetation across post-fire ages, predict biodiversity, and capture the spectral and structural complexity of fynbos communities. Virtual fynbos environments are developed to investigate how species occupy spatial, structural, and spectral dimensions during post-fire recovery and to systematically evaluate how changes in spatial and spectral resolution affect our ability to detect biodiversity.
Intended Audience:
Beginners, undergraduates, graduates. Those with interest in the topic.
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