Using Object-Oriented Classification for Coastal Management in the East Central Coast of Florida: A Quantitative Comparison between UAV, Satellite, and Aerial Data

High resolution mapping of coastal habitats is invaluable for resource inventory, change detection, and inventory of aquaculture applications. However, coastal areas, especially the interior of mangroves, are often difficult to access. An Unmanned Aerial Vehicle (UAV), equipped with a multispectral sensor, affords an opportunity to improve upon satellite imagery for coastal management because of the very high spatial resolution, multispectral capability, and opportunity to collect real-time observations. Despite the recent and rapid development of UAV mapping applications, few articles have quantitatively compared how much improvement there is of UAV multispectral mapping methods compared to more conventional remote sensing data such as satellite imagery. The objective of this paper is to quantitatively demonstrate the improvements of a multispectral UAV mapping technique for higher resolution images used for advanced mapping and assessing coastal land cover. We performed multispectral UAV mapping fieldwork trials over Indian River Lagoon along the central Atlantic coast of Florida. Ground Control Points (GCPs) were collected to generate a rigorous geo-referenced dataset of UAV imagery and support comparison to geo-referenced satellite and aerial imagery. Multi-spectral satellite imagery (Sentinel-2) was also acquired to map land cover for the same region. NDVI and object-oriented classification methods were used for comparison between UAV and satellite mapping capabilities. Compared with aerial images acquired from Florida Department of Environmental Protection, the UAV multi-spectral mapping method used in this study provided advanced information of the physical conditions of the study area, an improved land feature delineation, and a significantly better mapping product than satellite imagery with coarser resolution. The study demonstrates a replicable UAV multi-spectral mapping method useful for study sites that lack high quality data

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challengespublishersversionPeer reviewe

Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences

The aim of the Special Issue “Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences” was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of papers in various fields of environmental sciences—geology/mineral exploration, digital soil mapping, mapping and characterization of vegetation, and sensing of water bodies (including under-ice and underwater applications). In addition, there are two rather methodically/technically-oriented contributions dealing with the optimized processing of UAV data and on the design and test of a multi-channel optical receiver for ground-based applications. All in all, this compilation documents that HSI is a multi-faceted research topic and will remain so in the future

UNMANNED AERIAL VEHICLE (UAV) SURVEY-ASSISTED 3D MANGROVE TREE MODELING

3D visualization is a tool that supports geospatial analysis through the application of scientific information. It enhances the quality of standard photography and can be used in many applications. Through this study, a 3D mangrove tree model is generated, as assisted by a tree crown derived from UAV images. The researchers explored different platforms namely: MeshLab, SketchUp (with 3D Tree Maker extension), and Clara.io, to come up with a more realistic three-dimensional (3D) model of a mangrove tree. From an Unmanned Aerial Vehicle (UAV) derived Digital Surface Model (DSM), an isolated tree crown was selected which was then used as an assisting tool in creating the final 3D mangrove tree model. A default tree object was modified according to the characteristics as described by the DSM. Additional branches and leaves were added to the existing tree object, and its shape was modified to conform to the tree crown. The resulting model may be used to more accurately depict objects in the area to be visualized, however an automation procedure is recommended for an easier and more effective generation of multiple tree models expected in an area

Unmanned Aerial Remote Sensing of Coastal Vegetation: A Review

Coastal wetlands contribute greatly to our coasts economically and ecologically. The utility of coastal wetland vegetation, along with the multitude of dynamic forces they encounter, suggests the need of regular monitoring for sustainable management. While traditional in situ survey methods and remote sensing from space and manned platforms have provided means to monitor and study the coastal zone thus far, the recent developments of small unmanned aerial systems (sUAS) fill a small void between traditional in situ survey methods and the high spatial resolution of manned aircraft imagery. As an on-demand personal remote sensing device, an sUAS can be deployed over coastal regions at a low cost and with very fine spatial resolution (i.e. 1-10 cm) imagery and corresponding spatial accuracy. Though an sUAS provides many benefits, recent literature documents several shortcomings and limitations to using them for coastal wetland vegetation research, including changing tides, lighting conditions and legal restrictions on flying. This study reviewed all coastal wetland vegetation-related studies that included an sUAS as a mapping tool to document the current state of the field. Current practices, successes, and limitations are described, and future directions for the field are discussed. Coastal managers and researchers alike will be able use this comprehensive review to determine how to best approach future studies of diverse coastal vegetation

On the Use of Unmanned Aerial Systems for Environmental Monitoring

[EN] Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small-and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air-and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.The present work has been funded by the COST Action CA16219 "HARMONIOUS-Harmonization of UAS techniques for agricultural and natural ecosystems monitoring". B. Toth acknowledges financial support by the Hungarian National Research, Development and Innovation Office (NRDI) under grant KH124765. J. Millerovd was supported by projects GA17-13998S and RVO67985939. Isabel and Jodo de Lima were supported by project HIRT (PTDC/ECM-HID/4259/2014-POCI-0145-FEDER016668).Manfreda, S.; Mccabe, MF.; Miller, PE.; Lucas, R.; Pajuelo Madrigal, V.; Mallinis, G.; Ben Dor, E.... (2018). On the Use of Unmanned Aerial Systems for Environmental Monitoring. Remote Sensing. 10(4):1-28. https://doi.org/10.3390/rs10040641S12810

Remote sensing for cost-effective blue carbon accounting

Blue carbon ecosystems (BCE) include mangrove forests, tidal marshes, and seagrass meadows, all of which are currently under threat, putting their contribution to mitigating climate change at risk. Although certain challenges and trade-offs exist, remote sensing offers a promising avenue for transparent, replicable, and cost-effective accounting of many BCE at unprecedented temporal and spatial scales. The United Nations Framework Convention on Climate Change (UNFCCC) has issued guidelines for developing blue carbon inventories to incorporate into Nationally Determined Contributions (NDCs). Yet, there is little guidance on remote sensing techniques for monitoring, reporting, and verifying blue carbon assets. This review constructs a unified roadmap for applying remote sensing technologies to develop cost-effective carbon inventories for BCE – from local to global scales. We summarise and discuss (1) current standard guidelines for blue carbon inventories; (2) traditional and cutting-edge remote sensing technologies for mapping blue carbon habitats; (3) methods for translating habitat maps into carbon estimates; and (4) a decision tree to assist users in determining the most suitable approach depending on their areas of interest, budget, and required accuracy of blue carbon assessment. We designed this work to support UNFCCC-approved IPCC guidelines with specific recommendations on remote sensing techniques for GHG inventories. Overall, remote sensing technologies are robust and cost-effective tools for monitoring, reporting, and verifying blue carbon assets and projects. Increased appreciation of these techniques can promote a technological shift towards greater policy and industry uptake, enhancing the scalability of blue carbon as a Natural Climate Solution worldwide

Data and resolution requirements in mapping vegetation in spatially heterogeneous landscapes

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