Change Detection in Coral Reef Environment Using High-Resolution Images: Comparison of Object-Based and Pixel-Based Paradigms

Abstract

Despite increases in the spatial resolution of satellite imagery prompting interest in object-based image analysis, few studies have used object-based methods for monitoring changes in coral reefs. This study proposes a high accuracy object-based change detection (OBCD) method intended for coral reef environment, which uses QuickBird and WorldView-2 images. The proposed methodological framework includes image fusion, multi-temporal image segmentation, image differencing, random forests models, and object-area-based accuracy assessment. For validation, we applied the method to images of four coral reef study sites in the South China Sea. We compared the proposed OBCD method with a conventional pixel-based change detection (PBCD) method by implementing both methods under the same conditions. The average overall accuracy of OBCD exceeded 90%, which was approximately 20% higher than PBCD. The OBCD method was free from salt-and-pepper effects and was less prone to images misregistration in terms of change detection accuracy and mapping results. The object-area-based accuracy assessment reached a higher overall accuracy and per-class accuracy than the object-number-based and pixel-number-based accuracy assessment. methods for coral reef change detection. However, because of the limitations of medium-resolution sensors such as Landsat and SPOT, it is difficult to distinguish coral reef geomorphological dynamics from sea level rise [10], and to detect changes on the scale of a few meters in coral reef habitats [11]. With continued refinement of the spatial resolution of satellite imagery, conventional per-pixel methods have been found susceptible to a number of challenges in relation to change detection, including image misregistration [6,12] and salt-and-pepper effects [13,14]. Coral reef images, lack of distinct and stable texture features, are difficult to be accurately registered to each other [15], which makes the traditional pixel-based approach less promising in coral reef change detection using high-resolution images.Recent years have seen an increase in the number of studies using object-based image analysis (OBIA) [13]. OBIA has also been applied in coral reef environment, from geomorphological mapping to benthic community discrimination [16][17][18]. OBIA represents an effective combination of both the contextual analysis of visual interpretation and the quantitative analysis of the pixel-based method [19]. It has been proven that image registration error greatly affects the per-pixel change detection accuracy while the object-based method is less sensitive to image misregistration [20,21]. However, to the best of our knowledge, few studies have used object-based change detection (OBCD) methods in coral reef change detection. Generally, there are two possible strategies for OBCD methods: post-classification comparison and multi-temporal image object analysis [22]. The essence of the post-classification comparison approach lies in the initial classification, i.e., images acquired at different times are classifi...

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