High resolution aerial imagery from an unmanned helicopter for mapping fluvial substrate size in Chile
Shortcut URL: https://serc.carleton.edu/68943
Continent: South America
UTM coordinates and datum: none
This research presents some initial outputs of an on-going study which aims to map fluvial substrate size distributions on the San Pedro River in Chile using very high resolution remote sensing imagery, collected from a remote controlled helicopter or 'unmanned aerial system.' The size and distribution of substrate within fluvial environments plays a key role in the quality of aquatic habitats, yet current methods of characterising substrate are time consuming and labour intensive. Remote sensing approaches have the potential to provide a rapid and more objective alternative. The characterisation of physical habitat parameters such as substrate is increasingly important in Chilean rivers due to the mounting pressures to construct hydropower dams.
The high gradient and powerful hydraulic nature of rivers in Chile makes them well suited for the development of hydroelectric power dams. Currently there is a move to increase the number of such dams in Chile in order to meet growing energy demands. This has led to significant concerns about the impact of such constructions on natural river habitats (Vince 2010). The flow regulations which follow dam construction modify the natural river flow, thereby affecting the habitat quality downstream (Garcia et al., 2011). Chilean rivers are home to unique native fish populations about which relatively little is known. Such species are likely to be highly affected by the construction of dams and their subsequent impact on river flow (Habit et al., 2007).
As a result of these concerns, research has been aiming to characterise the current fluvial environments prior to dam construction, in order to better understand the requirements of the little studied native fish species. It is hoped that this will help to inform the nature and location of dam construction and the subsequent flow regulations in a way which will allow the maintenance of suitable habitats.
Some research has been carried out by the EULA Centre (European-Latin American International University Center for Environmental Research) at the University of Concepcion. They have been working on the San Pedro River in central Chile, selected as the location for construction of a large hydropower dam. A specific area of interest here (the 'Piedra Blanca' site – Figure 1) comprises a narrow shelf section along the right bank of the San Pedro measuring approximately 170m x 20m. Research at this location has been focussed on assessing flow velocities, water depth, substrate size and distribution as key factors influencing fish habitat.Substrate size has been mapped at sampling points spaced every 1-2m using a differential GPS (Global Positioning System – Figure 2) (Habit 2012, pers. comm.). At each location, dominant substrate size was assessed visually and categorised according to an established scale (see Wentworth 1922). This method of measuring substrate size is time consuming, labour intensive and quite subjective.
The aim of this research therefore is to work with the EULA Centre to investigate whether a high resolution remote sensing approach can provide similar substrate size data, in a faster, less laborious and more objective way which provides continuous data coverage.
The use of remote sensing approaches to quantify fluvial substrate size distributions is not a new concept, and has seen significant advancement in recent years. The majority of existing studies have used optical imagery and one of two main approaches:
(1) The 'photo-sieving' technique – uses very high resolution imagery collected at very close range and analyses it manually or using automated processes. This technique provides very high spatial resolution data concerning substrate size (millimetre level) but has limited spatial coverage (a few square metres) (Graham et al., 2005a, 2005b).(2) The image textural analysis approach – extracts image texture variables to develop a predictive relationship between these variables and the observed substrate sizes within an image. This approach has the advantage of covering large spatial areas (up to 80km stretches of river) but its spatial resolution has so far been limited to c.1m2 at best (Carbonneau et al., 2004, 2005, Lane and Carbonneau 2007).
Aim of this research
The work presented here aims to contribute to this growing body of research by assessing the use of very high resolution imagery (c.1-2cm) acquired from an unmanned aerial vehicle for estimating substrate size for habitat-mapping purposes at the Piedra Blanca site. The scale of this study is neither as detailed as the photo-sieving approach, nor as broad as the image texture analysis methods. Instead, it aims to assess substrate distribution at the scale of the relevant habitat unit, as identified by on-going research along a shallow river shelf section at the Piedra Blanca field site.
Data collection & processing
Very high resolution optical imagery was collected of the shallow shelf section at the Piedra Blanca site using a remote-controlled unmanned helicopter known as the Draganflyer X6 (Figure 3). This is a small, lightweight system capable of carrying a 0.5kg optical digital camera.
Artificial ground control points (GCPs) were set-up at the site and their position recorded using a differential GPS. These are important for subsequent image rectification. About a day's work was required in total to collect the imagery and GCPs - which included site set-up, collection of >200 images, 7 flights, and time for quality checking in between flights.
The images were subjected to strict selection criteria to ensure only the best quality images are used in subsequent analysis of substrate size. Only those free from blurring, those collected vertically and at the correct flying altitude (to maintain consistent image resolution) were selected for further analysis.
The selected images were then processed in a 3D image stitching software package called PhotoScan Pro (Agisoft LLC). This software uses 'Structure from Motion' (SfM) algorithms and the GCPs to generate a high resolution orthophotograph (stitched image which has been corrected for geometric and vertical distortions) and a digital elevation model (DEM) from a series of overlapping aerial images. These two output products for the shallow shelf section at the Piedra Blanca site are shown in Figures 4 and 5.
The next step for this research is to analyse the orthophoto and DEM using image processing software to map substrate sizes at the Piedra Blanca site. It is hoped that this high resolution remote sensing approach has the potential to provide a faster, more objective method for mapping fluvial substrate sizes than current methods. Such research has a great deal to offer sites such as the San Pedro River, where the current pressure for energy production is threatening natural river habitats.
The field assistance and contributions of Dr Ian Maddock, Prof Evelyn Habit, Caroline Wallis, Felipe Breton, James Atkins and other colleagues at the University of Worcester and the University of Concepcion are gratefully acknowledged. Financial support for fieldwork was provided by the British Society for Geomorphology, the Institute of Science and Environment at the University of Worcester and the EULA Center in Chile.
- Carbonneau, P.E., Lane, S.N. and Bergeron, N. (2004) 'Catchment-scale mapping of surface grain size in gravel bed rivers using airborne digital imagery' Water Resources Research 40, W07202, doi:10.1029/2003WR002759
- Carbonneau, P.E., Bergeron, N. and Lane, S.N. (2005) 'Automated grain size measurements form airborne remote sensing for long profile measurements of fluvial grain sizes' Water Resources Research 41, W11426, doi:10.1029/2005WR003994
- Garcia, A., Jorde, K., Habit, E., Caamano, D., and Parro, O. (2011) 'Downstream environmental effects of dam operations: changes in habitat quality for native fish species' River Research and Applications 27: 312-327
- Graham, D.J., Reid, I. and Rice, S.P. (2005a) 'Automated sizing of coarse-grained sediments: image-processing procedures' Mathematical Geology 37(1): 1-28
- Graham, D.J., Rice, S.P. and Reid, I. (2005b) 'A transferable method for the automated grain sizing of river gravels' Water Resources Research 41, W07020, doi: 10.1029/2004WR003868
- Habit, E., Belk, M.C., and Parra, O. (2007) 'Response of the riverine fish community to the construction and operation of a diversion hydropower plant in central Chile' Aquatic Conservation: Marine and Freshwater Ecosystems 17: 37-49
- Lane, S. and Carbonneau, P. (2007) 'High resolution remote sensing for understanding instream habitat' in Wood, P.J., Hannah, D.M. and Sadler, J.P. (Eds) Hydroecology and Ecohydrology: Past, Present and Future John Wiley and Sons, Chichester
- Vince, G. (2010) 'Dams for Patagonia' Science 329: 382-385
- Wentworth, C.K. (1922) 'A scale of grade and class terms for clastic sediments' Journal of Geology 30: 377-392
See also associated vignettes concerning the use of remote sensing for geomorphology.