Globally, climatic and anthropogenic forcings are causing the catastrophic decline of coral reef ecosystems, which sustain a plethora of marine life and support the livelihoods of several millions of people. Lakshadweep–Maldives–Chagosarchipelago (LMC) forms one of the largest chains of atoll systems in the world, and due to remoteness from the mainland, its islands boast a unique set of flora and fauna. The coral reefs of these tropical islands are highly vulnerable to stressors such as climate change, overfishing, monsoon runoff, and ocean acidification. To understand and manage these sensitive ecosystems, knowledge about the existing coral cover and distribution patterns are essential. In the present study, habitat modelling of the two corals Acropora muricata (Linnaeus, 1758) and Porites lutea (Milne Edwards & Haime, 1851) were carried out using the Maximum Entropy (MaxEnt) model to predict the probability of occurrence using remotely sensed environmental variables as predictors. The average test AUC values of 0.980 and 0.974, respectively, for A. muricata and P. lutea as estimated by MaxEnt shows that the model performance for both the species is outstanding. The average uncertainty (standard deviation) was about 0.012 and 0.021 respectively. It is found that the bathymetry is the variable having the highest contribution followed by Calcite and Phosphate for the distribution of both the species. The results of this study throw light on the probable occurrence of coral reefs in many of the hitherto unknown areas, especially the submerged banks and seamounts in the region. Much of these areas are less explored and have strategic positional advantages in increasing the ecosystem connectivity of the region. Furthermore, the relationship between coral distribution and the environmental variables as predicted by this study will be valuable in future conservation activities and designing marine protected areas.

在全球范围内，气候和人为强迫正在导致珊瑚礁生态系统的灾难性衰退，该生态系统维持着大量的海洋生物并维持着数百万人的生计。Lakshadweep–Maldives–Chagosarchipelago（LMC）是世界上最大的环礁系统链之一，由于离大陆较远，其岛屿拥有一系列独特的动植物群。这些热带岛屿的珊瑚礁极易受到气候变化，过度捕捞，季风径流和海洋酸化等压力因素的影响。为了了解和管理这些敏感的生态系统，有关现有珊瑚覆盖和分布模式的知识至关重要。在本研究中，对两种珊瑚的Acropora muricata（Linnaeus，1758）和Porites lutea的栖息地建模（Milne Edwards＆Haime，1851）是使用最大熵（MaxEnt）模型进行的，以遥感环境变量作为预测因子来预测发生的可能性。A. muricata和P. lutea的平均测试AUC值分别为0.980和0.974MaxEnt估计，这两个物种的模型性能都很出色。平均不确定度（标准偏差）分别约为0.012和0.021。发现，对于这两种物质的分布，测深法是具有最大作用的变量，其次是方解石和磷酸盐。这项研究的结果揭示了迄今为止许多未知地区可能发生的珊瑚礁，特别是该地区的淹没河岸和海山。这些地区中的许多地区很少被开发，并且在增加该地区的生态系统连通性方面具有战略位置优势。此外，本研究预测的珊瑚分布与环境变量之间的关系在未来的保护活动和设计海洋保护区中将具有重要价值。