Almahasheer, H., Serrano, O., & Duarte, C. M. (2019). Mangrove Colonization of a Newly Formed Intertidal Mudflat: The Red Sea as a Natural Laboratory. Frontiers in Marine Science, 6, 104.
Alongi, D. M. (2002). Present state and future of the world's mangrove forests. Environmental Conservation, 29(3), 331-349.
Alongi, D. M. (2008). Mangrove forests: resilience, protection from tsunamis, and responses to global climate change. Estuarine, Coastal and Shelf Science, 76(1), 1-13.
As-syakur, A. R., Sidik, A. S. M., & Wati, R. (2020). Performance of Object-Based Image Analysis Classification on Landsat Imagery in Detecting Mangrove Forest Changes in Probolinggo District, East Java Province, Indonesia. IOP Conference Series: Earth and Environmental Science, 459(1), 012001.
Barbier, E. B., et al. (2011). "The value of estuarine and coastal ecosystem services." Ecological Monographs, 81(2), 169-193.
Beer, C., & Weber, G. E. (2019). Remote sensing of leaf area index and chlorophyll content for improved ecosystem characterization: a review. ISPRS Journal of Photogrammetry and Remote Sensing, 157, 1-13.
Chen, S., Kovacs, J. M., Yang, Y., Liu, H., Ye, Y., & Luo, Y. (2021). Spatiotemporal dynamics of mangrove forests and their responses to environmental change in the Red River Delta, Vietnam, from 1990 to 2020. Science of the Total Environment, 771, 144993.
Chen, Z., Li, J., Chen, S., Chen, Q., Wang, H., & Gong, P. (2021). Discrimination of mangrove species and estimation of mangrove forest structural parameters using an unmanned aerial vehicle. International Journal of Applied Earth Observation and Geoinformation, 104, 102439.
Donato, D. C., et al. (2011). "Mangroves among the most carbon-rich forests in the tropics." Nature Geoscience, 4(5), 293-297.
Fatoyinbo, T. E., Simard, M., Washington-Allen, R. A., Shugart, H. H., & Adler, P. R. (2019). Landscape-scale extent, height, biomass, and carbon estimation of Mozambique's mangrove forests with Landsat ETM+ and Shuttle Radar Topography Mission elevation data. Remote Sensing of Environment, 231, 111221.
Ghosh, S., Chatterjee, R. S., & Das, P. (2020). Remote Sensing Based Mangrove Vegetation Vitality Assessment: A Case Study on the Indian Sundarbans. Journal of the Indian Society of Remote Sensing, 48(3), 517-528.
Giri, C., Ochieng, E., Tieszen, L. L., Zhu, Z., Singh, A., Loveland, T., ... & Duke, N. (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography, 20(1), 154-159.
Guo, H., & Wang, Z. (2021). Mapping of mangrove zonation and health status using multi-source remote sensing data in the Mai Po Nature Reserve, China. Ecological Indicators, 121, 107-193.
Guo, T., & Wang, X. (2021). Integrating Sentinel-2 and Landsat-8 imagery for mangrove classification using a novel deep learning network. Remote Sensing, 13(1), 140.
Huete, A. R., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002). Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83(1-2), 195-213.
Kathiresan, K., & Bingham, B. L. (2001). "Biology of mangroves and mangrove ecosystems." Advances in Marine Biology, 40, 81-251.
Khairunnisa, H., Mujahid, A., Yuhui, W., & Aulia, H. (2021). Integrating of Sentinel-2 and Sentinel-1 imagery for mangrove forest classification using random forest algorithm. Environmental Engineering and Sustainable Development, 3(2), 100032.
Khairunnisa, T., Muttaqin, M. Z., & Sakinah, E. N. (2021). Mangrove health assessment using remote sensing-based vegetation indices in Wakatobi National Park, Indonesia. IOP Conference Series: Earth and Environmental Science, 752(1), 012008.
Kovacs, J. M., Flores-Verdugo, F., Zou, X., Liu, H., Yang, S., Ye, Y., & Liu, H. (2021). Developing a Mangrove Vitality Index for Assessing Restoration Success in Coastal Wetlands: A Case Study in Southeast China. Sustainability, 13(7), 3871.
Kumar, M., & Mutanga, O. (2019). Mapping aboveground biomass in a tropical mangrove forest in the Red Sea coast using very high resolution airborne multispectral imagery. Remote Sensing, 11(21), 2515.
Li, Y., Ye, Y., Cui, L., Li, C., Yu, Y., & Zhang, X. (2020). Identifying potential areas for restoration of mangrove species in China’s coastal provinces using a comprehensive index based on satellite imagery. Ecological Indicators, 119, 106857.
Liu, Y., Kovacs, J. M., Zou, X., Ye, Y., & Liu, H. (2021). Monitoring mangrove health in Southeast China using Sentinel-2 and Landsat 8 imagery. Remote Sensing Applications: Society and Environment, 24, 100540.
Lotze, H. K., Tittensor, D. P., Bryndum-Buchholz, A., Eddy, T. D., Cheung, W., Galbraith, E. D., ... & Worm, B. (2019). Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proceedings of the National Academy of Sciences, 116(26), 12907-12912.
Nagelkerken, I., et al. (2008). "The habitat function of mangroves for terrestrial and marine fauna: A review." Aquatic Botany, 89(2), 155-185.
Roy, D. P., Wulder, M. A., Loveland, T. R., Woodcock, C. E., Allen, R. G., Anderson, M. C., ... & Scambos, T. A. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145, 154-172.
Schmidt, J. M., & Dafforn, K. A. (2019). A global analysis of urban and industrial impacts on mangrove habitats. Journal of Environmental Management, 232, 479-487.
Shamseldin, A. Y., Al-Amri, N. S., Al-Mukhtar, M., & Shamseldin, Y. A. (2020). Mapping and Monitoring Mangrove Distribution and Changes in Saudi Arabia: A Case Study of the Eastern Red Sea Coast Using Remote Sensing. Remote Sensing, 12(16), 2614.
Xue, J., & Su, B. (2017). Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications. Journal of Sensors, 1-17.