Leaf spot area index: A nondestructive mangrove leaf spot estimation technique

Abstract

Mangrove forests in the United Arab Emirates and the rest of the world hold a vital importance to the environment. For example, the Environmental Agency of Abu Dhabi has several programs in place for the preservation and protection of these forests due to their importance as breeding grounds for several sea species as well as the role they plan in preventing coastline erosion and reducing the impact of carbon emissions. Mangrove communities may exhibit defoliation, dieback, and death due to natural and man made reasons such as weather, insects and disease, nutrients, pollution, climate change, or population. A mechanism to assess the health level of the mangroves is important to help remedy the situation in its early stages. In this paper, we propose a nondestructive image processing technique to monitor and assess the health of mangrove populations by automatically estimating the ratio of the leaf spot area over the leaf area. The technique is based on processing images of mangrove leaves collected using a digital camera or a smart phone. The image of the leaf is analyzed to extract the contours of both the leaf and the spots within the leaf. Finally, we calculate what we propose as the Leaf Spot Area Index (LSAI). Estimating the index over a large and representative set of samples gives an improved estimation of the health of the mangrove ecosystem. Monitoring the index over time also helps in tracking the results of the programs in place to protect this important natural resource.