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UAV Based Monitoring of a Living Weir in Thailand
Abstract
Unmanned aerial vehicles (UAVs) have become the state of the art remote sensing measuring methodology in many engineering fields. The systems are becoming increasingly autonomous, and have a growing number of potential applications with decreasing costs. This makes UAV-based data acquisition a efficient and effective tool for surveying hydrosystems such as riverine ecosystems. In this work, we present our use of a lightweight multi-camera system specially designed for UAVs, generating total spatial coverage spectral imagery in reference reaches in Thailand. High resolution maps of the Normalized Differenced Vegetation Index (NDVI) are generated using near infrared (NIR) imagery gathered by the multi camera system. This hybrid approach can provide the necessary input data for detailed studies of the interaction between hydromorphological conditions and terrestrial vegetation caused by a living weir structure. In addition, digital surface models (DSM) are produced with the structure from motion (SfM) method, were the most effective models are made from a combination of imagery from high resolution aerial photography, supported by the inclusion of terrestrial photography. In this work, we show how the UAV-base aerial imagery and image processing workflow can be leveraged to enable the creation of a detailed quantitative metrics which can then be used in the analysis of ecologically complex monitoring sites.
... Figure 4. Left: NIR orthoimage of the nature-based living weir (red box) and surrounding vegetation with 5 cm/px resolution. Plants with higher activity are bright red, low activity green, and the river are shown in graduated grayscale [6] Figure 5. (a) A high-resolution ortho image was used in conjunction with standard terrestrial mapping methods to produce a substrate map. (b) An automated, object-based image classification method produces nearly identical results, with the added advantage of including regions not taken into account using the standard substrate mapping method [10] IAHR the high-resolution vegetation map generated from these images. ...
... UAS image positions as well as the reference ground control points are also shown. The final model used a total of 284 multi-spectral (RGB, NIR) images[6] ...
Rivers are best viewed from above, and unmanned aerial systems (UAS) provide an excellent means to collect digital imagery and data in challenging environments. UAS are now commonly used in archaeology, geography, mining, and civil engineering. The measurement and mapping of hydrosystems using UASs is both lean and agile, with the added advantage of increased safety for the surveying crew. Here we provide an overview of how UAS can be used to create new sources of digital information, ushering in the age of what we refer to as Rivers, 2.0.
Geomorphological change in riverine systems occurs across a wide range of temporal scales. Modeling change with high frequency could capture the complex behavior of the interactive dynamics between engineered structures in riverine systems. The objective of this work is to demonstrate the capability of SUAV’s imagery for monitoring large scale structural projects interjected into riverine systems. The objective of this research is to capture and process imagery that could classify bank armoring structures as either successful or stable in potentially hazardous locations. In addition to capturing the structural integrity of the structures it is also proposed that this research could aid in monitoring habitat used by adult and juvenile salmonids. sUAV’s provide an inexpensive way to capture large scale structural implementation and for restoration projects, bank protection methodologies, as well as general habitat monitoring.
Background
Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement.
Results
We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield.
Conclusion
This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed.
We tried more precise mapping of vegetation using UAV (unmanned aerial vehicle), as a new method of creating vegetation maps, and we objected to be clearly the efficient mapping of vegetation using the UAV method by comparing vegetation maps created by analysing aerial photographs taken by a UAV and an aircraft (manned flight). The aerial photography using UAV was conducted in the Niita River estuary (the secondary river flowing into South-Soma City in Fuku-shima Prefecture, Japan). The photography period was in August 2013. We analysed the aerial photographs using ArcGis 9 (Esri Japan Corporation, Tokyo, Japan). The aerial photographs of the main plant communities (Phragmites australis, Typha domingensis, and Miscanthus sacchariflorus) taken by the UAV could clearly discriminate each plant community at the 1/50 scale. Moreover, it could clearly discriminate the shape of a plant at the 1/10 scale. We compared the vegetation maps by analysing the aerial photos taken by a UAV (2013 shooting) and an aircraft (2011 shooting). As a result, the vegetation map created by the UAV method could clearly discriminate community distributions. We conclude that vegetation surveys using UAV are possible and are capable of a highly precise community division in places where field reconnaissance is difficult. The UAV method is effective and will contribute to the improvement of research methods in the future; this method may reduce research costs associated with a reduction in field survey days and manpower .
Small unmanned aircraft systems (UASs) are often suited to applications where the cost, resolution, and (or) operational inflexibility of conventional remote sensing platforms is limiting. Remote sensing with small UASs is still relatively new, and there is limited understanding of how the data are acquired and used for scientific purposes and decision making. This paper provides practical guidance about the opportunities and limitations of small UAS-based remote sensing by highlighting a small sample of scientific and commercial case studies. Case studies span four themes: (i) mapping, which includes case studies to measure aggregate stockpile volumes and map river habitat; (ii) feature detection, which includes case studies on grassland image classification and detection of agricultural crop infection; (iii) wildlife and animal enumeration, with case studies describing the detection of fish concentrations during a major salmon spawning event, and cattle enumeration at a concentrated animal feeding operation; (iv) landscape dynamics with a case study of arctic glacier change. Collectively, these case studies only represent a fraction of possible remote sensing applications using small UASs, but they provide insight into potential challenges and outcomes, and help clarify the opportunities and limitations that UAS technology offers for remote sensing of the environment.
We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.
Unmanned aerial vehicle (UAV) platforms are nowadays a valuable source of data for inspection, surveillance, mapping, and 3D modeling issues. As UAVs can be considered as a low-cost alternative to the classical manned aerial photogrammetry, new applications in the short- and close-range domain are introduced. Rotary or fixed-wing UAVs, capable of performing the photogrammetric data acquisition with amateur or SLR digital cameras, can fly in manual, semiautomated, and autonomous modes. Following a typical photogrammetric workflow, 3D results like digital surface or terrain models, contours, textured 3D models, vector information, etc. can be produced, even on large areas. The paper reports the state of the art of UAV for geomatics applications, giving an overview of different UAV platforms, applications, and case studies, showing also the latest developments of UAV image processing. New perspectives are also addressed.
Fine-scale (submeter) resolution digital elevation models (DEMs) created from high precision (subcentimeter) instruments (e.g., total station, rtkGPS, and laser scanning) have become ubiquitous in the field of fluvial geomorphology. They permit a diverse range of spatially explicit analyses including hydraulic modeling, habitat modeling, and geomorphic change detection. While previous studies have assessed the quality of specific topographic survey methods at individual sites or across a limited number of sites, an intercomparison of survey technologies across a diverse range of wadeable streams could help clarify which techniques are feasible, as well as which work best under what circumstances and for what purposes. Although a wealth of existing studies and protocols explain how to undertake each individual technique, in this study we seek to provide guidance on what techniques to use in which circumstances. We quantified the relative quality and the amount of effort spent collecting data to derive bare earth topography from an array of ground-based and airborne survey techniques. We used topographic survey data collected over the summer of 2010 from six sample reaches of varying complexity in the Lemhi River basin, Idaho, USA. We attempted to conduct complete, replicate surveys at each site using total station (TS), real-time kinematic (rtk) GPS, discrete return terrestrial laser scanner (TLS), and airborne LiDaR surveys (ALS). We evaluated the precision and accuracy of derived bare earth DEMs relative to the higher precision total station point data. Discrepancies between pairwise techniques were calculated using propagated DEM errors thresholded at a 95% confidence interval. Mean discrepancies between total station and rtkGPS DEMs were relatively low (≤ 0.05 m), yet TS data collection time was up to 2.4 times longer than rtkGPS. The ALS DEMs had lower accuracy than TS or rtkGPS DEMs, but the aerial coverage and floodplain context of the ALS data set was superior to all other techniques. The TLS bare earth DEM accuracy and precision were lower than any other technique because of vegetation returns misinterpreted as ground returns. Our results are helpful for understanding the strengths and weaknesses of different approaches.
This study explores the use of structure from motion (SfM), a computer vision
technique, to model vine canopy structure at a study vineyard in the Texas Hill Country.
Using an unmanned aerial vehicle (UAV) and a digital camera, 201 aerial images (nadir
and oblique) were collected and used to create a SfM point cloud. All points were
classified as ground or non-ground points. Non-ground points, presumably representing
vegetation and other above ground objects, were used to create visualizations of the study
vineyard blocks. Further, the relationship between non-ground points in close proximity to
67 sample vines and collected leaf area index (LAI) measurements for those same vines
was also explored. Points near sampled vines were extracted from which several metrics
were calculated and input into a stepwise regression model to attempt to predict LAI. This
analysis resulted in a moderate R2 value of 0.567, accounting for 57 percent of the
variation of LAISQRT using six predictor variables. These results provide further
justification for SfM datasets to provide three-dimensional datasets necessary for
vegetation structure visualization and biophysical modeling over areas of smaller extent.
Additionally, SfM datasets can provide an increased temporal resolution compared to
traditional three-dimensional datasets like those captured by light detection and
ranging (lidar).
In this paper, we assess the capabilities of an unmanned/uninhabited aerial vehicle (UAV) to characterize the channel morphology and hydraulic habitat of a 1-km reach of the Elbow River, Alberta, Canada, with the goal of identifying the advantages and challenges of this technology for river research and management. Using a small quadcopter UAV to acquire overlapping images and softcopy photogrammetry, we constructed a 5-cm resolution orthomosaic image and digital elevation model (DEM). The orthomosaic was used to map the distribution of geomorphic and aquatic habitat features, including bathymetry, grain sizes, undercut banks, forested channel margins, and large wood. The DEM was used to initialize and run River2D, a two-dimensional hydrodynamic model, and resulting depth and velocity distributions were combined with the mapped physical habitat features to produce refined estimates of available habitat in terms of weighted usable area. Based on 297 checkpoints, the vertical root-mean-squared error of the DEM was 8.8 cm in exposed areas and 11.9 cm in submerged areas following correction of the DEM for overprediction of elevations as a result of the refractive effects of water. Overall, we find several advantages of UAV-based imagery including low cost, high efficiency, operational flexibility, high vertical accuracy, and centimetre-scale resolution. We also identify some challenges, including vegetation obstructions of the ground surface, turbidity, which can limit bathymetry extraction, and an immature regulatory landscape, which may slow the adoption of this technology for operational measurements. However, by enabling dynamic linkages between geomorphic processes and aquatic habitat to be established, we believe that the advantages of UAVs make them ideally suited to river research and management. Copyright © 2014 John Wiley & Sons, Ltd.
Unmanned aerial vehicle (UAV) photogrammetry has been used in a growing number of diverse applications across different scientific disciplines. Early applications of UAVs included cultural heritage and archaeology, mainly for the documentation and modelling of monuments, buildings and landscapes. In this paper, the focus is on the application of UAVs for documenting archaeological excavations. As excavating is a dynamic process and the objects to be acquired can change significantly within a few hours, UAVs can provide a suitable alternative to traditional measurement methods such as measuring tapes and tachymeters. Nevertheless, the image processing steps have to be automated, as a large number of resulting materials, usually sketches, maps, ortho-images and 3D models, need to be available quickly. In order to accelerate the processing workflow, an interface between the UAV ground control software and various photogrammetric software packages was developed at ETH Zurich, which allows for an efficient management and transfer of orientation, trajectory and sensor data for rapid project set up.
2: scientific and commercial applications
2: scientific and commercial applications," J. Unmanned Veh. Syst., vol. 02, no. 03, pp. 86-102, Jul. 2014.