A mangrove is defined by the Smithsonian Museum of Natural History as
“a woody tree or shrub that lives along sheltered coastlines within the tropic or subtropic latitudes” (Teutli-Hernández et al. 2020).
Specifically, a mangrove is an amphibious ecosystem that acts like a bridge between the ocean and land, which makes it an intertidal forest, adapted to high salinity and water saturation (Teutli-Hernández et al. 2020). These plants are characterized by the ability to survive in flooded areas and soils high in salinity, like the ones found along the ocean coastline (Feller 2018). The concept mangrove can also define a community or an ecosystem that consist of the structure of the mangrove, like the leaves and roots, and other species whose survival depend on it (Feller 2018).
“They grown in 75% of the tropical and subtropical coasts worldwide and provide valuable ecosystem services with a global economic value estimated at 2.7 trillion dollars per year” (Teutli-Hernández et al. 2020).
Mangroves can adapt to survive in the coastal conditions of salty, flooded and oxygen-poor soil. Some adaptations are salt excreting through the leaves, which causes the formation of salt crystals, and root aeration, meaning the roots grow upwards toward the sky (Figure 1).
These impressive strategies are exclusive to the species (Feller 2018). On the other hand, mangroves are impacted by both, the sea and land. They are affected by sea level rise, erosion and storms from the sea, survive human-induced stressors like wildfires, deforestation and agriculture (Teutli-Hernández et al. 2020). Climate change poses yet another issue: with an increase in temperatures and sea level, mangroves are expanding their distribution ranges outside the equator and are becoming invasive species in islands like Hawaii and Tahiti (Feller 2018).
“Mangroves are among the most productive and biologically complex ecosystems on Earth” (Feller 2018).

Mangrove plants play a crucial role in the interactions of the ecosystem. They are a feeding place for several species and sustain a richly diverse food web. Crabs and insects directly consume the leaves, others, such as decomposers, take advantage of the dropped foliage and feed on the decaying matter (Castillero et al. 2023). Microbes and fungi residing in the mangrove roots utilize this decomposed material as a source of energy, and aid in the recycling of essential nutrients like nitrogen, phosphorus, sulfur and iron for the mangroves. Additionally, various organisms depend on the intricate structures formed by the branching trees and roots for habitat; monkeys, birds, insects and other flora inhabit the mangrove branches, some birds also make their nests here, alligators enjoy the still water, and sponges, snails, worms and barnacles attach themselves to the roots (Figure 2) (Castillero et al. 2023).
Mangroves are often called the nursery of the seas because, besides providing food for several species, they also provide protection from predators for crabs, shrimp and fish. These organisms spend their life’s early stages in mangroves before migrating to the open ocean as adults (Castillero et al. 2023).

Mangrove forests significantly contribute to the surrounding environment by modifying and supporting it. Their complex root systems mitigate the strength of waves, facilitate the accumulation of sand, soil and silt. They retain sediments, filter the water and reduce erosion. By absorbing nutrients from runoff, mangroves prevent harmful algal blooms offshore, benefiting adjacent ecosystems such as coral reefs and seagrass beds (Castillero et al. 2023).
Additionally, mangrove forests sequester high amounts of carbon from the atmosphere. When the trees grow, they utilize carbon dioxide to build their leaves, roots and branches (Kristensen et al. 2008). Also, with the shedding leaves and general decay, these trees transport stored carbon to the seafloor, contributing to the phenomenon known as "blue carbon" because it stores carbon underwater in ecosystems such as mangrove forests, seagrass beds and salt marshes. Despite occupying less than 2 per cent of marine environments, mangroves are responsible for 10 to 15 per cent of global carbon burial (Kristensen et al. 2008).
“One acre of mangrove forest can store about 1,450 pounds of carbon per year (163 g carbon per square meter per year)—roughly the same amount emitted by a car driving straight across the United States and back (5,875 miles)” (Feller 2018).
Since mangroves absorb the strength of waves, they are natural barriers from storms and tsunamis which protect people’s lives and homes. Specifically, mangroves possess natural resilience to daily water influxes and are capable of handling increased flooding during storms. Furthermore, they provide seafood, fruit, medicine, wood and other fibers essential to people's livelihoods (Debrot et al. 2022; Kathiresan and Rajendran 2005). By stabilizing shores through sediment trapping and land building, they contribute to shoreline protection (Kathiresan and Rajendran 2005). Additionally, mangroves enhance water quality because they act like filters of contaminated water, and as mentioned before they play a crucial role in climate protection by absorbing carbon dioxide and reducing greenhouse gas levels in the atmosphere. Overall, researchers estimate that the services provided by the world's mangrove forests are worth billions of dollars to human communities (Feller 2018; Kathiresan and Rajendran 2005).
The global economic value of mangroves is estimated to be 1.648 trillion US dollars. Mangrove wood is commonly used for constructing structures such as stilt houses, furniture, fences, bridges, fishing gear, canoes, rafts and boats (Feller 2018). In Japan, charcoal derived from mangroves is highly valued. Additionally, mangrove products find application in industries producing soaps, cosmetics, perfumes and insecticides. The medicinal uses of mangroves include pain relief, anti-inflammatory effects, diabetes treatment, anti-tumor properties, parasite elimination, antiseptic qualities and others (Thatoi, Samantaray, and Das 2016).

What risks are mangroves exposed to?
Mangroves are one of the most threatened tropical ecosystems. They face natural (storms and erosion) and human-driven threats. The main driver of mangrove transformation is human activity such as tourism infrastructure development and aquaculture expansion (Figure 3) (Teutli-Hernández et al. 2020). These activities, among others, are causing a rapid decline in mangrove populations worldwide (Castillero et al. 2023). Specifically, aquaculture, coastal urbanization, rice and palm oil cultivation, and industrial operations are replacing these resilient trees and the ecosystems they sustain at an alarming rate (Lee et al. 2014; Castillero et al. 2023).
Shrimp farming poses the most significant threat to mangroves, accounting for at least 35 per cent of the overall loss of these forests because this activity requires the creation of ponds or enclosures within the mangrove structure, thus removing vegetation. It creates an additional nutrient input because of the shrimps’ feeding requirement, leading to water pollution (Riascos, Cantera, and Blanco-Libreros 2018). Additionally, the escalating sea levels driven by global temperature increases, presents a serious challenge to mangroves worldwide. Historically, mangroves have been able to migrate further inland during sea level fluctuations, but human development now often acts as a barrier, limiting their ability to adapt and survive. Furthermore, recent occurrences of the El Niño Southern Oscillation (ENSO) in the Pacific Basin have demonstrated that sea levels can also drop dramatically, leading to severe impacts on mangrove ecosystems (Riascos, Cantera, and Blanco-Libreros 2018).

What is mangrove ecological restoration?
To understand what mangrove restoration is, we must firstly define ecological restoration.
Ecological restoration is the “process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed, it seeks to initiate or accelerate ecosystem recovery following damage, degradation, or destruction” (SER 2024).
It involves the recovery of mangrove plants that have been lost and their functions for the ecosystem with the purpose of targeting challenges like climate change mitigation, improving services for human well-being, and conserving biodiversity (Teutli-Hernández et al. 2020).
As has been demonstrated in several projects, mangrove restoration is similar to reforesting terrestrial forests (Teutli-Hernández et al. 2020). This typically involves cultivating mangrove seedlings in controlled environments like greenhouses and afterwards transplanting them into mudflats along the coastline. However, this method often proves ineffective (López-Portillo et al. 2017). Achieving successful restoration of mangrove ecosystems necessitates a comprehensive strategy that encompasses social, economic, ecological and scientific-technical considerations. Failure to address any of these aspects has frequently resulted in the failure of restoration projects (Teutli-Hernández et al. 2020; Su, Friess, and Gasparatos 2021).
Effective mangrove ecological restoration relies on a thorough assessment of site conditions and the selection of restoration actions based on the ecology of the species (Teutli-Hernández et al. 2020). These actions may involve hydrological rehabilitation to promote natural regeneration or reforestation, depending on the initial assessment of the system, and also, it needs an understanding of the ecosystem's ecology, including the interactions between geomorphology, hydrology, and the structural and functional characteristics of mangrove ecosystems across various spatial and temporal scales (Teutli-Hernández et al. 2020; López-Portillo et al. 2017).
Furthermore, ensuring the participation and representation of all stakeholders during the restoration process is crucial. This includes involvement of local communities, academic experts, economic stakeholders, regulatory bodies such as government and local authorities, as well as funding entities (Teutli-Hernández et al. 2020; López-Portillo et al. 2017).
Restoring mangrove ecosystems includes the below listed activities (Teutli-Hernández et al. 2020):
- Choose the participants to create a technical workgroup;
- Delimiting the boundaries of the site to be restored;
- Conducting a diagnosis and “forensic ecology” analysis of the site;
- Formulating the restoration plan and actions;
- Monitoring the progress and success of restoration actions;
- Establishing linkages and socialization.
What is the role of space technologies in mangrove restoration and monitoring?
Space technologies play an important role in several the above-mentioned stages of ecological restoration projects. For instance, for the delimitation of the site it is important to understand variables such as accessibility, water quality, disturbance level, historical geomorphological and hydrological conditions, topography, hydrology, physical-chemical characteristics of (surface and interstitial) water, physical-chemical characteristics of sediments, vegetation and others (Teutli-Hernández et al. 2020). Furthermore, aerial photography, satellite images and radar can observe and map mangroves or other features of interest (Howard et al. 2023).
Examples of some of the satellite sensors commonly used to monitor mangrove forests are:
- Landsat Program: this program provides moderate-resolution imagery for monitoring large-scale changes in mangrove forests over time. Landsat sensors, such as Landsat Thematic Mapper (TM) - Landsat 4; Landsat Thematic Mapper (TM) - Landsat 5; Enhanced Thematic Mapper Plus (ETM+) – Landsat 7; and Operational Land Imager (OLI) – Landsat 8, show data that can be used to assess vegetation health, land cover changes and mangrove extent (Otero et al. 2019);
- Sentinel-2: These satellites are part of the European Union Copernicus program. They provide multispectral imagery at high spatial resolution that shows mangrove distribution, monitoring changes in land cover, identification of individual trees, delineation of forest boundaries, and assessing habitat quality (Farzanmanesh et al. 2024; Tran, Reef, and Zhu 2022);
- Moderate Resolution Imaging Spectroradiometer (MODIS): MODIS sensors are found in National Aeronautics and Space Administration (NASA) Terra and Aqua satellites. They provide data at moderate spatial resolution of vegetation dynamics such as fragmentation, changes in mangrove forests' greenness, productivity, and phenology (Tran, Reef, and Zhu 2022; Rahman et al. 2013);
- Synthetic Aperture Radar (SAR) sensors: These sensors can be found in the European Space Agency Sentinel-1 satellites and NASA RADARSAT series. They are particularly useful for mangrove monitoring because they see through clouds and vegetation canopy, they provide data about forest structure, topography, biomass, types of mangroves, aboveground biomass and carbon density, and changes in inundation patterns (Flores et al. 2019; NASA Earth Science Data Systems 2020; Hu et al. 2020);
- Hyperspectral sensors: These sensors can be found in the Hyperion Instrument on NASA EO-1 satellite, and they are special because they produce imagery with hundreds of narrow spectral bands. Hyperspectral data provides information about species composition, health and stress levels. (Pandey, Anand, and Srivastava 2019; Hati et al. 2021).
For instance, figure 5 illustrates mangrove regeneration in Senegal Casamance River (NASA Earth Observatory 2018). The map was created based on an analysis of a Landsat 7 — ETM+ satellite observations of the Normalized Difference Vegetation Index (NDVI). Figure 6 is a satellite image taken by the Operational Land Imager (OLI) on Landsat 8 (NASA Earth Observatory 2018).


Another relevant instrument for mangrove mapping alongside the above-mentioned satellite sensors is Light Detection and Ranging (LiDAR). LiDAR instruments are not mounted on satellites. They collect data from airborne or terrestrial platforms, and provide three-dimensional information about topography, mangrove canopy structure, height and biomass (Ustin and Middleton 2021; NASA Earth Science Data Systems 2020; Maurya, Mahajan, and Chaube 2021).
A comparison of satellite sensors, their resolution, the information that can be derived from them and the algorithms and indices useful for mangrove restoration is provided below in Table 1:
Satellite sensor | Landsat Program | Sentinel-2 | Moderate Resolution Imaging Spectroradiometer (MODIS) | Synthetic Aperture Radar (SAR) sensors | Hyperspectral sensors |
Sensor | TM, ETM+, OLI | Sentinel-2 satellites | MODIS sensors | Sentinel-1, RADARSAT satellites | Hyperion on NASA EO-1 satellite |
Information derived | Mangrove extent, land cover changes, vegetation health | Mangrove distribution, changes in land cover, habitat quality | Vegetation dynamics, mangrove forests' greenness, productivity, and phenology | Forest structure, topography, biomass, types of mangroves, aboveground biomass and carbon density, and changes in inundation patterns | Mangrove species composition, health, and stress levels |
Algorithms and indices | Normalized Difference Vegetation Index (NDVI), Modified Soil-Adjusted Vegetation Index (MSAVI), Tasseled Cap Transformation | Normalized Difference Vegetation Index (NDVI), Mangrove Vegetation Index, Red edge NDVI, Plant Senescence Reflectance Index, Normalized Difference Red Edge Index, Red-edge Chlorophyll Index, Normalized Difference Moisture Index | Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Fraction of Photosynthetically Active Radiation (FPAR) | Radar Vegetation Index (RVI), Radar Forest Degradation Index (RFDI), Backscatter Coefficient, Polarimetric Decomposition | Normalized Difference Vegetation Index (NDVI), Spectral Angle Mapper (SAM), Enhanced Vegetation Index (EVI), Green Leaf Area Index, Canopy Chlorophyll Density, Forest Leaf Area Index |
Resolution | 30 m | 10-20 m | 250-500 m | 10-30 m | 10-30 m |
Sources | (Otero et al. 2019; Dan et al. 2016; Cissell et al. 2018; Tran, Reef, and Zhu 2022) | (Tran, Reef, and Zhu 2022; Farzanmanesh et al. 2024; Zhang et al. 2022) | (Tran, Reef, and Zhu 2022; Rahman et al. 2013; Phan and Stive 2022) | (Hu et al. 2020; Flores et al. 2019; NASA Earth Science Data Systems 2020) | (Pandey, Anand, and Srivastava 2019; Hati et al. 2021; Broge and Leblanc 2001; Gong et al. 2003) |
Other tools for mangrove restoration
According to the Mangrove Ecological Restoration Guide by Teutli-Hernández et al. (2020), the mangrove potential restoration map “provides a useful tool for selecting and prioritizing sites to be restored based on their potential provision of ecosystem services and other features” (Teutli-Hernández et al. 2020). Mapping ocean wealth offers a global model and map designed for identifying priority areas for mangrove restoration and to provide support and encouragement for such projects worldwide. The model considers the current and historical distribution of mangrove forests, as well as local drivers contributing to mangrove loss and degradation, such as urbanization, industrial development, agricultural and aquacultural expansion, deforestation, altered freshwater flows, pollution, and coastal erosion (The Nature Conservancy 2023). These factors may vary in their extent and severity depending on the specific region. Moreover, environmental elements like wave energy and tides, along with social factors such as population density and demographics, are considered in the model. Future projections of sea level rise, urbanization trends and weather patterns are also included (The Nature Conservancy 2023).
“Model results can be viewed in an online mapping and decision-support tool that can be used by environmental groups to show the extent of degraded mangroves, how much land is available for restoration, identify priority restoration areas, and kick-start opportunities for implementing restoration projects. The project will also result in modeled ecosystem service values for restored sites” (The Nature Conservancy 2023).
Another tool available is the Global Mangrove Watch (GMW). This online platform offers remote sensing data and monitoring tools for mangroves. It grants global access to the location and alterations in mangroves worldwide. By providing detailed information on topography, soil conditions, and hydrology, the Global Mangrove Watch equips coastal resource managers, policymakers and practitioners with essential evidence to address changes in mangrove coverage, identify local causes of mangrove loss, and monitor the progress of restoration efforts (Howard et al. 2023). Other resources such as Google Earth and Planet help remote mapping of current land use and visualizing historical trends of gain or loss of mangrove area over time in the project site and its surrounding areas (Howard et al. 2023).
The Google Earth Engine Mangrove Mapping Methodology (GEM) offers an intuitive, user-friendly, and reproducible tool tailored for a broad audience of coastal managers and decision-makers without specialized expertise. GEM is specifically designed to map mangrove distributions across multiple dates and quantify their dynamics worldwide (Howard et al. 2023). Although it does not require advanced proficiency in remote sensing, geospatial analysis, or coding, the tool is structured assuming users possess basic computer skills and familiarity with key procedures for mangrove mapping and dynamics assessment (Howard et al. 2023).

Case studies around the world
Space technologies also play a crucial role in monitoring the progress and success of restoration actions. Monitoring determines the results of any restoration project. Regardless of the frequency of monitoring or the number of indicators to be evaluated, conducting monitoring tasks typically demands technical proficiency, fieldwork, and sustained commitment over time (Howard et al. 2023). Addressing these challenges can involve various approaches, such as utilizing remote sensing data to track changes in metrics like extent, structure (e.g., height and potentially species composition), and condition of the mangrove (Howard et al. 2023).
In several cases, satellite technology is employed to monitor changes in mangrove ecosystems over time, as well as to model disasters and map vulnerable areas for disaster management, and recovery (The Commonwealth 2021). In Trinidad and Tobago, scientists from the Institute of Marine Affairs (IMA) integrated layers of data to learn sustainable mangrove management and investigate its function as a carbon storage system (The Commonwealth 2021). The IMA has utilized a combination of aerial and satellite images, Google Earth data , Landsat data provided by NASA, and other sources to monitor mangrove ecosystems in Trinidad and Tobago for a period of over 25 years. Additionally, datasets from 3-D laser scans, physical measurements of mangroves, soil analysis, and carbon testing are employed to quantify the carbon stored within mangrove forests, both above and below ground level (The Commonwealth 2021).
Another study analyzed the carbon capture of different strategies for protecting mangrove ecosystems using “Aboveground and Belowground Biomass Carbon Density” (Song et al. 2023). “The aboveground biomass map integrates land-cover specific, remotely sensed maps of woody, grassland, cropland, and tundra biomass at a 300-m spatial resolution” (Spawn and Gibbs 2020). Aboveground living biomass carbon density refers to the amount of carbon stored in living plant parts situated above the Earth's surface, such as stems, bark, branches and twigs. This measurement excludes leaf litter or coarse woody debris that was formerly attached to living plants but has since fallen and is no longer living. On the other hand, belowground living biomass carbon density refers to the carbon stored in living plant tissues beneath the Earth's surface, specifically in roots (Spawn and Gibbs 2020).
Similarly, a team of scientists in China developed a remote sensing-based Mangrove Restoration Effectiveness Index (MREI) to evaluate mangrove restoration effectiveness using Landsat timeseries images by considering the change in mangrove area and the Normalized Difference Vegetation Index (NDVI) from the start year to the end year of each ecological restoration phase. Results indicate that this index effectively represents the changes of mangrove restoration and is consistent with space images (Wang et al. 2023).
Conclusion
Mangroves are highly valuable ecosystems to people and Earth’s systems that exist along tropical and subtropical coastlines. They provide important ecosystem services worth millions of dollars annually and their role as a buffer zone between terrestrial and marine and aquatic ecosystems transforms harsh coastal conditions and makes them indispensable components of coastal ecosystems worldwide. Mangroves are known as the nurseries of marine life, they contribute to shoreline protection, improve water quality, and sequester carbon. They offer relevant benefits in the attempt at tackling climate change and supporting biodiversity. Some of the ecosystem services mangroves provide include storm protection, provision of food and medicine, livelihood support, and economic opportunities through various industries. Despite their importance, mangroves face several threats from human activities such as aquaculture expansion, urbanization and climate change-induced sea level rise.
Mangrove restoration is an important strategy for mitigating the loss and degradation of mangrove ecosystems. Successful restoration efforts require a comprehensive approach that integrates social, economic, ecological and scientific considerations, as well as active involvement from stakeholders.
Space technologies, including satellite imagery and remote sensing, play relevant roles in various stages of mangrove restoration projects, from site selection and monitoring to assessing restoration effectiveness. These technologies enhance the efficiency and effectiveness of restoration efforts by providing valuable data and real-time information. Continued research, investment and collaboration are essential to address the hazards threatening mangrove ecosystems and scale up successful restoration efforts globally. Harnessing the power of space technologies alongside interdisciplinary approaches will be crucial in safeguarding these invaluable coastal habitats for future generations.
Broge, N. H, and E Leblanc. 2001. “Comparing Prediction Power and Stability of Broadband and Hyperspectral Vegetation Indices for Estimation of Green Leaf Area Index and Canopy Chlorophyll Density.” Remote Sensing of Environment 76 (2): 156–72. https://doi.org/10.1016/S0034-4257(00)00197-8.
Castillero, Rosa G., Angel Javier Vega, Yolani A. Robles, and Jaime Rivera. 2023. “CARACTERIZACIÓN GEOMORFOLÓGICA, FLORISTICA Y ESTRUCTURAL DEL MANGLAR EN LA COSTA DE PIXVAE, GOLFO DE CHIRIQUÍ, PACÍFICO DE PANAMÁ.” Tecnociencia 25 (1): 209–29.
Cissell, Jordan R., Alysa M. Delgado, Brenna M. Sweetman, and Michael K. Steinberg. 2018. “Monitoring Mangrove Forest Dynamics in Campeche, Mexico, Using Landsat Satellite Data.” Remote Sensing Applications: Society and Environment 9 (January): 60–68. https://doi.org/10.1016/j.rsase.2017.12.001.
Dan, T. T., C. F. Chen, S. H. Chiang, and S. Ogawa. 2016. “MAPPING AND CHANGE ANALYSIS IN MANGROVE FOREST BY USING LANDSAT IMAGERY.” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences III–8 (June): 109–16. https://doi.org/10.5194/isprs-annals-III-8-109-2016.
Debrot, Adolphe O., Sri Rejeki, Rudhi Pribadi, and M. Nazrul Islam. 2022. “Options for Mangrove-Friendly Alternativelivelihoods in the Mangrove Ecosystem (Opsi Mata Pencaharian Alternatif Di Ekosistem Mangrove Yang RamahLinggunkan).” C075/22. IJmuiden: Wageningen Marine Research. https://library.wur.nl/WebQuery/wurpubs/605583.
Farzanmanesh, Raheleh, Kourosh Khoshelham, Liubov Volkova, Sebastian Thomas, Jaona Ravelonjatovo, and Christopher J. Weston. 2024. “Temporal Analysis of Mangrove Forest Extent in Restoration Initiatives: A Remote Sensing Approach Using Sentinel-2 Imagery.” Forests 15 (3): 399. https://doi.org/10.3390/f15030399.
Feller, Candy. 2018. “Mangroves | Smithsonian Ocean.” Smithsonian National Museum of Natural History. April 30, 2018. https://ocean.si.edu/ocean-life/plants-algae/mangroves.
Flores, Africa, K. Herndon, Rajesh Thapa, and Emil Cherrington. 2019. “Synthetic Aperture Radar (SAR) Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation.” https://doi.org/10.25966/NR2C-S697.
Gong, Peng, Ruiliang Pu, G.S. Biging, and M.R. Larrieu. 2003. “Estimation of Forest Leaf Area Index Using Vegetation Indices Derived from Hyperion Hyperspectral Data.” IEEE Transactions on Geoscience and Remote Sensing 41 (6): 1355–62. https://doi.org/10.1109/TGRS.2003.812910.
Hati, Jyoti Prakash, Swagata Goswami, Sourav Samanta, Niloy Pramanick, Sayani Datta Majumdar, Nilima Rani Chaube, Arundhati Misra, and Sugata Hazra. 2021. “Estimation of Vegetation Stress in the Mangrove Forest Using AVIRIS-NG Airborne Hyperspectral Data.” Modeling Earth Systems and Environment 7 (3): 1877–89. https://doi.org/10.1007/s40808-020-00916-5.
Howard, Jennifer, Catherine Loveloc, Mark Beeston, Clint Cameron, James Sippo, Valerie Hagger, Celine van Bijsterveldt, Pieter van Eijk, and Femke H. Tonneijck. 2023. Best Practice Guidelines for Mangrove Restoration. Global Mangrove Alliance and the Blue Carbon Initiative. https://www.mangrovealliance.org/best-practice-guidelines-for-mangrove-….
Hu, Luojia, Wei Yao, Zhitong Yu, and Lei Wang. 2020. “National-Scale Mangrove Forest Mapping by Using Sentinel-1 SAR and Sentinel-2 MSI Imagery on the Google Earth Engine Platform.” March 23, 2020. https://doi.org/10.5194/egusphere-egu2020-5305.
Kathiresan, Kandasamy, and Narayanasamy Rajendran. 2005. “Coastal Mangrove Forests Mitigated Tsunami.” Estuarine, Coastal and Shelf Science 65 (3): 601–6. https://doi.org/10.1016/j.ecss.2005.06.022.
Kristensen, Erik, Steven Bouillon, Thorsten Dittmar, and Cyril Marchand. 2008. “Organic Carbon Dynamics in Mangrove Ecosystems: A Review.” Aquatic Botany, Mangrove Ecology – Applications in Forestry and Costal Zone Management, 89 (2): 201–19. https://doi.org/10.1016/j.aquabot.2007.12.005.
Lee, Janice Ser Huay, Sinan Abood, Jaboury Ghazoul, Baba Barus, Krystof Obidzinski, and Lian Pin Koh. 2014. “Environmental Impacts of Large-Scale Oil Palm Enterprises Exceed That of Smallholdings in Indonesia.” Conservation Letters 7 (1): 25–33. https://doi.org/10.1111/conl.12039.
López-Portillo, Jorge, Roy R. Lewis, Peter Saenger, André Rovai, Nico Koedam, Farid Dahdouh-Guebas, Claudia Agraz-Hernández, and Victor H. Rivera-Monroy. 2017. “Mangrove Forest Restoration and Rehabilitation.” In Mangrove Ecosystems: A Global Biogeographic Perspective: Structure, Function, and Services, edited by Victor H. Rivera-Monroy, Shing Yip Lee, Erik Kristensen, and Robert R. Twilley, 301–45. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-62206-4_10.
Maurya, Khushbu, Seema Mahajan, and Nilima Chaube. 2021. “Remote Sensing Techniques: Mapping and Monitoring of Mangrove Ecosystem—a Review.” Complex & Intelligent Systems 7 (6): 2797–2818. https://doi.org/10.1007/s40747-021-00457-z.
Merzdorf, Jessica. 2020. “NASA Study Maps the Roots of Global Mangrove Loss.” NASA Climate Change: Vital Signs of the Planet. 2020. https://climate.nasa.gov/news/3009/nasa-study-maps-the-roots-of-global-….
Muffin Creatives. 2021. Photo of boat in mangrove in Pexels.com. Photograph. https://www.pexels.com/es-es/foto/barca-mangle-embarcacion-cuerpo-de-ag….
NASA Earth Observatory. 2018. The Spread of Mangroves in Senegal. Satellite image. NASA Earth Observatory. https://earthobservatory.nasa.gov/images/91867/the-spread-of-mangroves-….
NASA Earth Science Data Systems. 2020. “Using Satellites to Measure the Size and Shape of Mangroves | Earthdata.” Earth Science Data Systems, NASA. July 1, 2020. https://www.earthdata.nasa.gov/learn/articles/measuring-mangroves.
Otero, Viviana, Ruben Van De Kerchove, Behara Satyanarayana, Husain Mohd-Lokman, Richard Lucas, and Farid Dahdouh-Guebas. 2019. “An Analysis of the Early Regeneration of Mangrove Forests Using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia.” Remote Sensing 11 (7): 774. https://doi.org/10.3390/rs11070774.
Pandey, Prem Chandra, Akash Anand, and Prashant K. Srivastava. 2019. “Spatial Distribution of Mangrove Forest Species and Biomass Assessment Using Field Inventory and Earth Observation Hyperspectral Data.” Biodiversity and Conservation 28 (8): 2143–62. https://doi.org/10.1007/s10531-019-01698-8.
Parra, Diego. 2023. Photography of Diego F. Parra in Pexels.com. Photograph. https://www.pexels.com/es-es/foto/pajaro-agua-sentado-rama-18426922/.
Phan, Manh Hung, and Marcel J. F. Stive. 2022. “Managing Mangroves and Coastal Land Cover in the Mekong Delta.” Ocean & Coastal Management 219 (March): 106013. https://doi.org/10.1016/j.ocecoaman.2021.106013.
Rahman, Abdullah F., Danilo Dragoni, Kamel Didan, Armando Barreto-Munoz, and Joseph A. Hutabarat. 2013. “Detecting Large Scale Conversion of Mangroves to Aquaculture with Change Point and Mixed-Pixel Analyses of High-Fidelity MODIS Data.” Remote Sensing of Environment 130 (March): 96–107. https://doi.org/10.1016/j.rse.2012.11.014.
Riascos, José M., Jaime R. Cantera, and Juan F. Blanco-Libreros. 2018. “Growth and Mortality of Mangrove Seedlings in the Wettest Neotropical Mangrove Forests during ENSO: Implications for Vulnerability to Climate Change.” Aquatic Botany 147 (June): 34–42. https://doi.org/10.1016/j.aquabot.2018.03.002.
SER. 2024. “Restoration Resource Center - What Is Ecological Restoration?” Society for Ecological Restoration. 2024. https://ser-rrc.org/what-is-ecological-restoration/.
Smithsonian Ocean. 2018. Mangroves | Smithsonian Ocean. Photograph. https://ocean.si.edu/ocean-life/plants-algae/mangroves.
Song, Shanshan, Yali Ding, Wei Li, Yuchen Meng, Jian Zhou, Ruikun Gou, Conghe Zhang, et al. 2023. “Mangrove Reforestation Provides Greater Blue Carbon Benefit than Afforestation for Mitigating Global Climate Change.” Nature Communications 14 (1): 756. https://doi.org/10.1038/s41467-023-36477-1.
Spawn, S.A., and H.K. Gibbs. 2020. “Vegetation Collection Global Aboveground and Belowground Biomass Carbon Density Maps for the Year 2010.” GTiff, 9810.740697000001 MB. https://doi.org/10.3334/ORNLDAAC/1763.
Su, Jie, Daniel A. Friess, and Alexandros Gasparatos. 2021. “A Meta-Analysis of the Ecological and Economic Outcomes of Mangrove Restoration.” Nature Communications 12 (1): 5050. https://doi.org/10.1038/s41467-021-25349-1.
Teutli-Hernández, C, J.A. Herrera-Silveira, D.J. Cisneros-de la Cruz, and R. Román-Cuesta. 2020. Mangrove Ecological Restoration Guide: Lessons Learned. Mainstreaming Wetlands into the Climate Agenda: A Multilevel Approach (SWAMP). CIFOR/CINVESTAV-IPN/UNAM-Sisal/PMC.
Thatoi, Hrudayanath, Dibyajyoti Samantaray, and Swagat Kumar Das. 2016. “The Genus Avicennia, a Pioneer Group of Dominant Mangrove Plant Species with Potential Medicinal Values: A Review.” Frontiers in Life Science 9 (4): 267–91. https://doi.org/10.1080/21553769.2016.1235619.
The Commonwealth. 2021. “How Space Tech Is Aiding Mangrove Conservation in the Commonwealth.” Commonwealth. 2021. https://thecommonwealth.org/news/how-space-tech-aiding-mangrove-conserv….
The European Space Agency. 2017. Irrawaddy Delta, Myanmar. Satellite image. https://www.esa.int/ESA_Multimedia/Images/2017/07/Irrawaddy_Delta_Myanm….
The Nature Conservancy. 2023. “Mangrove Restoration Potential | Mapping Ocean Wealth.” 2023. https://oceanwealth.org/applications/mangrove-restoration/.
Tran, Thuong V., Ruth Reef, and Xuan Zhu. 2022. “A Review of Spectral Indices for Mangrove Remote Sensing.” Remote Sensing 14 (19): 4868. https://doi.org/10.3390/rs14194868.
Ustin, Susan L., and Elizabeth M. Middleton. 2021. “Current and Near-Term Advances in Earth Observation for Ecological Applications.” Ecological Processes 10 (1): 1. https://doi.org/10.1186/s13717-020-00255-4.
Wang, Yuhang, Xifei Wang, Shahbaz Khan, Demin Zhou, and Yinghai Ke. 2023. “Evaluation of Mangrove Restoration Effectiveness Using Remote Sensing Indices - a Case Study in Guangxi Shankou Mangrove National Natural Reserve, China.” Frontiers in Marine Science 10 (November). https://doi.org/10.3389/fmars.2023.1280373.
Zhang, Rong, Mingming Jia, Zongming Wang, Yaming Zhou, Dehua Mao, Chunying Ren, Chuanpeng Zhao, and Xianzhao Liu. 2022. “Tracking Annual Dynamics of Mangrove Forests in Mangrove National Nature Reserves of China Based on Time Series Sentinel-2 Imagery during 2016–2020.” International Journal of Applied Earth Observation and Geoinformation 112 (August): 102918. https://doi.org/10.1016/j.jag.2022.102918.