Magee, Aidan
(2023)
A Decision-level Multi-sensor Data Fusion approach
to Land Cover Classification.
PhD thesis, National University of Ireland Maynooth.
Abstract
In recent years there has been an increased demand for frequently updated Land Cover
Classification (LCC) products. With ever greater numbers of Earth Observation (EO)
and Remote Sensing (RS) platforms capturing data, the combined utilisation of data
from multiple platforms has the potential to improve both the accuracy and frequency
of LCC product updates through a process known as sensor fusion. This thesis examines
how the fusion of RS sensors with diverse imaging characteristics can overcome challenges
encountered when generating an annual LCC product. To undertake this examination,
the technical specifications for the Second Generation Corine Land Cover (CLC+) Backbone raster product and its application on the island of Ireland is used as a case study
for evaluating the use of mono-platform and sensor-fused RS datasets for LCC. A review
of Machine Learning (ML) techniques in this thesis highlighted key factors crucial to
achieving high-accuracy classification along with the proposal of a high-accuracy rapid
inference Light Fully Convolutional Neural Network (LFCNN) architecture. This review
also highlighted challenges when performing LCC on the island of Ireland, such as frequent cloud cover that can reduce the availability of optical satellite data, preventing
the widespread use of high-accuracy multi-temporal ML classification. In this thesis, the
application of a decision-level fusion approach is demonstrated as a means of mitigating
the issue of frequent cloud cover and ensuring full classification coverage while also increasing classification accuracy. The versatility of a decision-level fusion approach was
further demonstrated through the fusion of aerial and satellite RS data to improve LCC
in complex non-homogeneous regions such as urban environments. The findings of this
research have direct implications not only for performing LCC on the island of Ireland but
throughout Europe and beyond, with clear recommendations provided for the generation
of LCC products using EO and RS data.
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