Mapping seagrasses on the basis of Sentinel-2 images under tidal change

Approaches, potential, and challenges in the use of remote sensing to study mangrove and other tropical wetland forests

“…Over time, the remote sensing approach was applied to the study of mangroves in many tropical regions of the world (e.g., Pasqualini et al 1999, Saito et al 2003, Kovacs et al 2005, Satyanarayana et al 2011, with theoretical and technological tools providing higher-quality information on the status of vegetation at each locality (Zhang et al 2023). More recently, community structural attributes of wetland forests (e.g., aboveground biomass, canopy height) have been explored using mathematical modeling (Couteron et al 2005, Kayitakire et al 2006Owers et al 2018, Pereira et al 2018, Koma et al 2021, although wetland forest mapping and monitoring continue to prevail (e.g., Sulong et al 2002, Saito et al 2003, Adam et al 2010, Barbier et al 2011, Alsaaideh et al 2013, Jones et al 2016, Chatziantoniou et al 2017, Guo et al 2017, Yevugah et al 2017, Li et al 2023, Steenvoorden et al 2023; Figure 3A).…”

“…The platforms for acquiring satellite imagery are classified as passive sensors because they use solar radiation to capture terrain details. Other types of sensors are known as active because they emit energy and record its reflection, rendering them independent from physical and weather conditions at image acquisition, such as illumination, cloudiness, and water bodies (Aschbacher et al 1995, Green et al 1998a, Chinea 2002, Kovacs et al 2008, Kuenzer et al 2011, Li et al 2023. Interestingly, recognizing the advantages of contrasting sensor types led to their combined use (Held et al 2003, Asner et al 2008, Simard et al 2008, Aslan et al 2016, increasing the capacity and efficacy to detect, differentiate and estimate wetland forest structure (Ramsey III et al 1998, Kayitakire et al 2006, Aslan et al 2016, Wang et al 2019, De Luca et al 2022, Steenvoorden et al 2023.…”

“…Among the many existing indices, the most used in wetland forests studies are the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the Normalized Difference Water Index (NDWI) (McFeeters 1996, Gao 1998, Kovacs et al 2005, Alsaaideh et al 2013, Kafy et al 2023, Shafi et al 2023. By minimizing the effects of factors linked to biophysical terrain parameters, vegetation indices provide reliable multi-temporal information on the conservation status and the functionality of these systems (Gao 1996, Huete et al 1997, Gao 1998, Saito et al 2003, Wang et al 2004, Nasiri et al 2022, Li et al 2023.…”