Remote Sensing of Submerged Aquatic Vegetation in a Shallow Non-Turbid River Using an Unmanned Aerial Vehicle

Flynn, Kyle F.; Chapra, Steven C.

doi:10.3390/rs61212815

Cited by 136 publications

(99 citation statements)

References 58 publications

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“…This paper explores a novel method to delineate four beach zones based on UAS hyperspatial RGB (Red, Green, and Blue) imagery and textures. On the one hand, the RGB true-color imagery has been used for mapping aquatic vegetation with the object-based image analysis [14] and adaptive cosine estimator and spectral angle mapper algorithm [15]. The RGB wide band images acquired by typical off-the-shelf cameras, such as those found in small UAS remote sensing units, limits the use of conventional remote sensing spectral indexes, however, the UAS hyperspatial imagery allows geometric properties such as textures to be used with classification algorithms.…”

Section: Introductionmentioning

confidence: 99%

Using UAS Hyperspatial RGB Imagery for Identifying Beach Zones along the South Texas Coast

Gibeaut

2017

Remote Sensing

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Shoreline information is fundamental for understanding coastal dynamics and for implementing environmental policy. The analysis of shoreline variability usually uses a group of shoreline indicators visibly discernible in coastal imagery, such as the seaward vegetation line, wet beach/dry beach line, and instantaneous water line. These indicators partition a beach into four zones: vegetated land, dry sand or debris, wet sand, and water. Unmanned aircraft system (UAS) remote sensing that can acquire imagery with sub-decimeter pixel size provides opportunities to map these four beach zones. This paper attempts to delineate four beach zones based on UAS hyperspatial RGB (Red, Green, and Blue) imagery, namely imagery of sub-decimeter pixel size, and feature textures. Besides the RGB images, this paper also uses USGS (the United States Geological Survey) Munsell HSV (Hue, Saturation, and Value) and CIELUV (the CIE 1976 (L*, u*, v*) color space) images transformed from an RGB image. The four beach zones are identified based on the Gray Level Co-Occurrence Matrix (GLCM) and Local Binary Pattern (LBP) textures. Experiments were conducted with South Padre Island photos acquired by a Nikon D80 camera mounted on the US-16 UAS during March 2014. The results show that USGS Munsell hue can separate land and water reliably. GLCM and LBP textures can slightly improve classification accuracies by both unsupervised and supervised classification techniques. The experiments also indicate that we could reach acceptable results on different photos while using training data from another photo for site-specific UAS remote sensing. The findings imply that parallel processing of classification is feasible.

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Section: Introductionmentioning

confidence: 99%

Using UAS Hyperspatial RGB Imagery for Identifying Beach Zones along the South Texas Coast

Gibeaut

2017

Remote Sensing

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“…Potential examples include sediment concentration, chlorophyll distribution, blooming algae status, submerged vegetation mapping, bathymetry, and chemical and organic waste contaminations [153,154].…”

Section: Flow Monitoringmentioning

confidence: 99%

On the Use of Unmanned Aerial Systems for Environmental Monitoring

et al. 2018

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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.

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“…derived a variety of data products from UAS imagery of a river system, including digitized vegetation maps, digital elevation models (DEMs), and bathymetric maps. Flynn and Chapra (2014) describe methods for collecting and classifying imagery of submerged aquatic vegetation in a shallow river using an off-the-shelf multirotor system. Further such case studies are summarized by Birdsong et al (2015).…”

Section: Wetland Riparian and Coastal Habitatsmentioning

confidence: 99%

Wildlife research and management methods in the 21st century: Where do unmanned aircraft fit in?

Chabot

Bird

2015

J. Unmanned Veh. Sys.

205

183

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Since the turn of the century, emerging unmanned aircraft systems (UAS) have found increasingly diverse applications in wildlife science as convenient, very highresolution remote sensing devices. Achieved or conceptualized applications include optical surveying and observation of animals, autonomous wildlife telemetry tracking, and habitat research and monitoring. As the technology continues to progress and interest from the wildlife science community grows, there may yet be much untapped potential for UAS to contribute to the discipline. We present a review of the published primary literature on the application of UAS in wildlife science and related fields. This is followed by a systematic review of the broader wildlife science literature published since the turn of the century to assess where UAS are likely to make important contributions going forward based on the trends that have emerged thus far. UAS, in particular small lightweight models, are generally well suited for collecting data at an intermediate spatial scale between what is easily coverable on the ground and what is economically coverable with conventional aircraft. They are particularly useful for monitoring wildlife and habitats in places that are difficult to access or navigate from the ground, as well as approaching sensitive or aggressive species.Key words: aerial survey, conservation, remotely piloted aircraft system, unmanned aerial vehicle, drone, wildlife monitoring.Résumé : Depuis le début du siècle, les nouveaux systèmes d'aéronefs sans pilote (UAS), en tant qu'appareils de télédétection de haute résolution pratiques, ont donné lieu à de plus en plus d'applications diverses en science de la faune. Les applications réalisées ou conceptualisées comprennent l'inventaire et l'observation optiques des animaux, la localisation autonome de la faune par télémétrie et la recherche et la surveillance des habitats. À mesure que la technologie continue de progresser et que l'intérêt de la part du milieu scientifique du domaine de la faune croît, la contribution des UAS à la discipline pourra augmenter, car il peut y avoir encore beaucoup de potentiel à exploiter. Nous présentons un examen de la littérature primaire publiée portant sur l'application des UAS dans les domaines de la science de la faune et connexes. Un examen systématique de l'ensemble de la littérature de la science de la faune publiée depuis le début du siècle s'ensuit dans le but d'évaluer, d'après les tendances qui ont émergé jusqu'à maintenant, où les UAS vont possiblement faire des contributions à l'avenir. Les UAS, en particulier les petits modèles légers, sont bien adaptés à la collecte de données à une échelle spatiale intermédiaire entre ce qui est facilement saisi sur le terrain et ce qui est saisi à l'aide d'un aéronef traditionnel. Ils sont particulièrement utiles pour la surveillance de la faune et des habitats dans les endroits difficiles à accéder ou à naviguer à partir du sol, ainsi que pour s'approcher des espèces sensibles ou agressives.

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Remote Sensing of Submerged Aquatic Vegetation in a Shallow Non-Turbid River Using an Unmanned Aerial Vehicle

Cited by 136 publications

References 58 publications

Using UAS Hyperspatial RGB Imagery for Identifying Beach Zones along the South Texas Coast

Using UAS Hyperspatial RGB Imagery for Identifying Beach Zones along the South Texas Coast

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Wildlife research and management methods in the 21st century: Where do unmanned aircraft fit in?

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