In this study, the effects of environmental conditions on the distribution and presence of mangrove species are examined within the geographic boundaries of latitude 14.25 \(^{\circ}\) N to 26.25 \(^{\circ}\) N and longitude 72.75 \(^{\circ}\) E to 88.75 \(^{\circ}\) E. Spatial analysis reveals that mangrove species exhibit higher photosynthetic rates in southern latitudes ( \(\sim \)  7.5 \(^{\circ}\) N) due to optimal warmer temperatures, while northern latitudes ( \(\sim \)  25 \(^{\circ}\) N) show lower rates, indicating less favorable growth conditions. Surface temperature analysis reveals clustering of higher temperatures in lower latitudes ( \(\sim \)  7.5 \(^{\circ}\) N–12.5 \(^{\circ}\) N), promoting mangrove growth, while cooler temperatures in northern latitudes ( \(\sim \)  25 \(^{\circ}\) N) limit their presence. Soil moisture analysis indicates favorable growth conditions in southern latitudes ( \(\sim \)  7.5 \(^{\circ}\) N) and western longitudes ( \(\sim \)  72 \(^{\circ}\) E), with spatial clustering confirmed by Moran’s I. Precipitation patterns also show spatial clustering, with higher levels in southern latitudes ( \(\sim \)  10 \(^{\circ}\) N) and western longitudes ( \(\sim \)  72 \(^{\circ}\) E), which are conducive to mangrove proliferation. Applying Moran’s I and Local Indicators of Spatial Association (LISA) identified significant clusters in environmental factors influencing mangrove distribution. The p-values from the permutation test (e.g., photosynthesis p = 0.334, precipitation p = 0.652) suggest a spatial correlation, indicating that mangrove occurrence is not random but influenced by clustered environmental factors. These findings suggest that incorporating spatial dependencies in predictive models can enhance the accuracy of mangrove distribution predictions.