Abstract
Abstract. Tree degradation in National Parks poses a serious risk to the birds and animals and to a larger extent the general ecosystem. The essence of Forest degradation mapping is to detect the extent of damage on the trees over time, hence providing stakeholders with a basis for forest rehabilitation and intervention. The study proposes a workflow for detection and classification of degrading acacia vegetation along Lake Nakuru riparian reserve. Inspired by previous research on the use of Dual Polarized Sentinel 1 Ground Range Detected (GRD) data for vegetation detection, a set of six Sentinel 1 GRD and Sentinel 2 MSI of corresponding dates (2018–2019) were used. Our study confirms the existing correlation between vegetation indices derived from optical sensors and the backscatter indices from S1 SAR image of the same land cover classes. Factors that were used in validating the results include some comparisons between pixelwise and object-based classification, with a focus on the underlying segmentation and classification algorithms, the polarimetric attributes (VV+VH intensity bands) and the reflectance bands (NIR, SWIR & GREEN), the Haralick features (GLCM) vs. some geometric attributes (area & moment of inertia). Classification carried out on the temporal datasets considering geometric attributes and the Random Forest classifier yielded the highest Overall Accuracy (OA) with 94.25 %, and a Kappa coefficient of 0.90.
Highlights
Wetlands are the most productive ecosystems hosting different types of insects, birds, and large mammals
Wetland classification falls under land cover mapping, classes related to riparian reserve and their product utility for various applications still remain uncertain (Krankina et al, 2010)
Our research aims at addressing the following knowledge gaps: 1. Identify a robust and reliable method that can be used in tree condition and health detection especially on Acacia Xanthophloea strands along Lake Nakuru riparian reserve
Summary
Wetlands are the most productive ecosystems hosting different types of insects, birds, and large mammals. On the shores of Lake Nakuru thrives Acacia Xanthophloea whose occurrence is associated with the high water table. The lake has been flooding its banks (Onywere et al, 2013) (Fig. 1), destroying the yellow barked Acacia whose leaves provide fodder for the Rothschild giraffe and it’s pod important feed for the Vervet monkeys in the Park. Since the acacia provides a buffer against siltation in the lake, their degradation could be one amongst other reasons behind the flooding lake. In order to monitor degrading wetlands, microwave sensors using Radar Technology are appealing since they capture ground information during the day and night independent of changing weather conditions (Woodhouse, 2006), to the optical based sensors. SAR-C polarimetric intensity bands (VV+VH) have been used in previous studies to map land use and land cover, and further in conjunction with Haralick features (Haralick et al, 1973) to map sea-ice-type (Liu et al, 2015) and in ice water discrimination (Zakhvatkina et al, 2017)
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