Tance inside the near-infrared and consequently impact the assessment of your
Tance within the near-infrared and consequently influence the assessment of your vegetation state (NDVI); and (2) automatic classification or semi-automatic classification, calibration of your UAV pictures, that will be crucial to avoid misclassification and reduce lens distortion, as indicated by Myers et al. (2018) [66]. Hence, further research is necessary to define algorithms and rules for the UAVs pictures classification. However, coastal management, ecological monitoring and marsh restoration strategies rely on the developments of new technologies and methodologies for high-resolution temporal and spatial scale. five. Conclusions This work highlights how an integrated method combining vegetation characterization surveying along with the acquisition of aerial imageries by UAV can be Compound 48/80 Epigenetic Reader Domain effectively applied inside the field of coastal monitoring and restoration interventions. The incredibly higher spatial resolution from the final orthomosaic and NDVI maps, especially if further combined using a high temporal resolution in terms of small-time lapse Combretastatin A-1 site amongst survey repetitions, can lead to effective and reputable final results. Additionally, the vegetation qualities data are practicallyRemote Sens. 2021, 13,16 ofcontinuous on account of the quite smaller pixel size of your final NDVI solutions, if in comparison to a classic and time-consuming vegetation survey. Further survey repetitions by UAV within the future will present additional information to accurately assess the behavior of the Cell 1B method and permit managers much better tools to assess ecological characterization in marsh restoration projects. Accessibility of affordable UAVs will allow us to raise the temporal and spatial resolution of aerial photogrammetry and datasets. High frequency information will let scientists to quantify important coastal processes affecting wetlands, which are presently analyzed primarily via field-based monitoring. Numerical models of wetland morphodynamics should integrate these new higher resolution remote sensing solutions.Author Contributions: Conceptualization W.N., Y.T., M.Q. and also a.P.; methodology, W.N., Y.T., M.Q. plus a.P.; software, W.N., Y.T., M.Q., G.F. along with a.P.; validation, W.N., I.V., C.C., M.Q. and L.W.S.; formal evaluation, W.N., Y.T., M.Q. and a.P.; investigation, W.N., Y.T., M.Q. along with a.P.; sources, W.N., G.F., L.W.S. and also a.P.; data curation, W.N., I.V., C.C., M.Q., G.F. and L.W.S.; writing–original draft preparation, Y.T. and W.N.; writing–review and editing, W.N., Y.T., M.Q., I.V., G.F., A.P. and L.W.S.; visualization, W.N., Y.T. and M.Q.; supervision, W.N.; project administration, W.N. and L.W.S.; funding acquisition, W.N., G.F., L.W.S. as well as a.P. All authors have read and agreed for the published version in the manuscript. Funding: This investigation was funded by (i) University of Maryland; and (ii) Salisbury University (Faculty Mini rant entitled Image Acquisition by Drone to Model Coastal Regions in Chesapeake Bay). Institutional Evaluation Board Statement: Not Applicable. Informed Consent Statement: Not Applicable. Information Availability Statement: Not Applicable. Acknowledgments: The authors are grateful to the University of Maryland Center for Environmental Science–Horn Point Laboratory, to the Maryland Environmental Service, Maryland Department of Transportation Maryland Port Administration and towards the U.S. Army Corps of Engineers–Baltimore District for making achievable and funding this applied research project. Partial monetary assistance for this investigation was supplied by the Maryland Division of Transport.