OBJECT-BASED CHANGE DETECTION ON ACACIA XANTHOPHLOEA SPECIES DEGRADATION ALONG LAKE NAKURU RIPARIAN RESERVE

Automated mapping of heterogeneous riparian landscape is of high interest to assess our planet. Still, it remains a challenging task due to the occurrence of flooded vegetation. While both optical and radar images can be exploited, the latter has the advantage of being independent acquisition conditions. However, and despite their popularity, the threshold-based approaches commonly used present some drawbacks such as not taking into account the spatial context and providing mixed pixels within class boundaries. In this study, we propose a novel methodology to avoid such issues by using an object-based image analysis approach on polarimetric radar data. We use our workflow to map the degrading Acacia x. species along lake Nakuru Riparian reserve, and obtain highly-accurate results