Validation of a high-resolution, remotely operated aerial remote-sensing system for the identiﬁcation of herbaceous plant species

Applied Vegetation Science 15 (2012) 383–389

Validation of a high-resolution, remotely operated
aerial remote-sensing system for the identification of
herbaceous plant species
Fumiko Ishihama, Yasuyuki Watabe & Hiroyuki Oguma

Keywords Abstract
High positioning accuracy; Non-destructive
survey; Portable remote-sensing system; Question: Is a high-resolution remote-sensing system based on a radio-
Radio-controlled helicopter; Wetland controlled helicopter (the ‘Falcon-PARS system’) an effective tool to obtain
images that can be used to identify herbaceous species?
Abbreviations
IMU = Inertial measurement unit; GCP = Location: Watarase wetland, Japan.
Ground control point
Methods: We applied the remote-sensing system to a wetland composed
Nomenclature
mainly of Phragmites australis and Miscanthus sacchariflorus. The aerial observation
BG Plants Japanese-name-scientific-name Index was performed in a 100 9 200 m area at a flying height of 30 m. From the
(YList), http://bean.bio.chiba-u.jp/bgplants/ obtained images, we tried to identify P. australis and M. sacchariflorus through
ylist_main.html (accessed 30 November 2011) visual interpretation.

Received 15 July 2010 Results: We obtained images with a high spatial resolution (1 cm) and a posi-
Revised 30 November 2011 tioning accuracy of finer than 1 m using this small and lightweight system, and
Accepted 20 December 2011 confirmed that we could identify the above two species from the obtained
Co-ordinating Editor: Aaron Moody
images.
Conclusion: Such a high-resolution system can be used to directly identify her-
Ishihama, F. (corresponding author, baceous species, and as a non-destructive alternative to ground surveys. This
ishihama@nies.go.jp) & Oguma, H.
lightweight system can be carried to sites such as a high-altitude bog that cannot
(oguma@nies.go.jp): National Institute for
Environmental Studies, Onogawa, Tsukuba,
be reached by a motor vehicle. Because of the low flying height (below cloud
Ibaraki 305-8506, Japan level), aerial observation is possible even on cloudy days, thereby permitting
Watabe, Y. (y_watabe@ists.co.jp): observations in all seasons.
Information & Science Techno-System Co.,
Ltd., Takezono, Tsukuba, Ibaraki 305-0032,
Japan

type in detail, fine-scale remote sensing with a resolution
Introduction
of 1 cm would be required.
Remote sensing is a convenient tool for efficient, non- Although there is an inevitable trade-off between reso-
destructive mapping of vegetation over wide spatial scales. lution and observation speed, a high-resolution remote-
Satellite and aircraft remote sensing is widely used to sensing system capable of distinguishing among detailed
obtain distribution maps of vegetation classification (De- vegetation types or identifying small plant species has
Fries 2008; Xie et al. 2008; Hill et al. 2010) and habitat advantages that outweigh its reduced speed. The first is
maps of species (Kerr Ostrovsky 2003), and to estimate that it permits non-destructive observation. Ground sur-
biomass (e.g. Boudreau et al. 2008) and plant phenology veys sometimes cause substantial damage to the vegeta-
(Verbesselt et al. 2010; Reed et al. 2009). Although these tion, particularly at fragile sites such as bogs. Although
remote-sensing systems are effective for such observations, long-term monitoring is required to examine changes in
they are only useful for relatively large targets, such as tall biodiversity and to plan effective conservation measures
trees, or for rough classification of vegetation types. This is (Marsh Trenham 2008), damage to vegetation during
because the resolution of these systems is relatively low monitoring on foot can be especially serious when
(5 cm at best for aircraft remote sensing). To identify her- repeated surveys are required. Remote sensing with suffi-
baceous or small woody species or to classify vegetation ciently high resolution would be a valuable alternative to

Applied Vegetation Science
Doi: 10.1111/j.1654-109X.2012.01184.x © 2012 International Association for Vegetation Science 383

High resolution remote-sensing system F. Ishihama et al.

ground surveys because it would reduce or eliminate dam- veys that require resolutions ranging from several meters
age to vegetation. A second advantage is the ability to to several tens of centimeters has been reported (Davis
obtain detailed observations of sites that are difficult for Johnson 1991; Gerard et al. 1997; Johnson et al. 2004;
humans to approach, such as cliff faces and the canopies of Miyamoto et al. 2004; Sugiura et al. 2005; Berni et al.
tall trees. Third, even if the speed is relatively limited, 2009; Artigas Pechmann 2010). However, some of these
high-resolution remote sensing still provides a faster tool systems are not suitable to capture georeferenced high-
for mapping individual plants than is possible in surveys resolution images at resolutions of 1 cm or finer in a non-
conducted on foot. destructive way. A balloon system is very vulnerable to
The criteria for a remote-sensing system suitable for wind, and it is difficult to control its position, especially in
high-resolution observation include high positioning accu- high-resolution surveys, which require delicate position-
racy, a robust ability to work under a range of weather ing control with accuracy finer than a few meters. Because
conditions, and portability (light weight). High positioning tethered balloon systems need to be towed by a human for
accuracy is essential to allow comparison of images from positioning control, they can cause damage to vegetation
different times so that researchers can monitor temporal in study sites susceptible to trampling. In addition, balloon
changes in vegetation and can overlay images with other systems require containers of pressurized, lighter-than-air
geographical information, such as elevation. Robustness gas, which cannot be carried by humans over long dis-
under a range of weather conditions is required to permit tances to reach remote sites. Although fixed-wing aircraft
surveys in all seasons. Phenological changes represent have superior positioning control and robustness against
information that can be used to distinguish plant species, wind, their high flight speed can cause serious problems;
and multi-seasonal observations capable of detecting phe- obtaining high-resolution images with sufficiently high
nological changes are an effective way to distinguish plant positioning accuracy faces many specific problems (e.g.
species or vegetation types (Gilmore et al. 2008). Remote motion blur in the images due to a combination of insuffi-
sensing from piloted aircraft is possible only under a lim- cient light and an insufficiently high camera shutter
ited range of weather conditions (i.e. clear days) because speed). These problems can be solved by flying more
the piloted aircraft fly as high as 2000 m, and their sensors slowly or by hovering, if the aircraft has a low level of
may be blocked by low cloud. Obtaining a cloud-free vibration (Appendix S1). In addition, a fixed-wing aircraft
image is also an important problem for satellite remote often requires flight strips for takeoff and landing, and
sensing (Xie et al. 2008; Wang et al. 2009). Such limita- these are rarely available in survey areas.
tions often make it difficult to perform surveys in certain To solve these problems, we chose a lightweight
seasons. Portable systems would be required at study sites remote-sensing system capable of hovering and with
such as those at high altitudes, wetlands and oceanic low vibration. To meet these criteria, we chose a heli-
islands, which are usually inaccessible to ground vehicles. copter (AscTec Falcon 8; Ascending Technologies GmbH,
Remote sensing using a radio-controlled helicopter, Krailling, Germany; Fig. 1a) that can hover at the
fixed-wing aircraft and balloon is a potential candidate for assigned coordinates (using an autopilot function) and
high-resolution remote sensing because such vehicles can obtain photographs by automatically activating the cam-
fly at much lower altitudes than piloted aircraft. The effec- era shutter. It is only in the last few years that light-
tiveness of these systems for ecological or agricultural sur- weight radio-controlled remote-sensing systems with an

(a) (b)

Fig. 1. (a) The helicopter (AscTec Falcon 8; Ascending Technologies GmbH, Krailling, Germany) and (b) camera used in the high-resolution remote sensing
system.

384 Doi: 10.1111/j.1654-109X.2012.01184.x © 2012 International Association for Vegetation Science

F. Ishihama et al. High resolution remote-sensing system

autopilot function became available. The autopilot func- We have named this system (helicopter, digital camera
tion allows the aircraft to fly along a predefined course and Cartomaton software) the ‘Falcon- photogrammetry
and obtain photographs automatically at preset coordi- and remote-sensing (PARS)’ system.
nates, and it is therefore an essential function for easy
and speedy image acquisition. Such systems have been
Study site for the aerial observation of vegetation
developed mainly for military (Newcome 2004) or geo-
graphical use (e.g. Delacourt et al. 2009), so their appli- We tested the Falcon-PARS system in the Watarase wet-
cability to plant surveys has rarely been evaluated (but land of central Japan (139°41′ E, 36°14′ N, 14 m a.s.l.;
see Rango et al. 2009). Fig. 2a). The Watarase wetland is a floodplain wetland that
In this study, we aimed to validate the use of a remote- covers about 1500 ha, and its vegetation is mainly com-
sensing system based on a radio-controlled helicopter to posed of Phragmites australis (Cav.) Trin. ex Steud. and
examine whether it could satisfy our criteria (high resolu- Miscanthus sacchariflorus (Maxim.) Benth. Because these
tion, positioning accuracy, robustness across a range of species form dense vegetation that reaches a maximum
weather conditions, and portability) for monitoring of her- height of 4 m in July, ground surveys are impractical, and
baceous plants. We tested whether we could use images remote sensing is therefore an essential monitoring tool.
obtained by this system to distinguish among herbaceous Although a previous study reported successful detection of
plants species in the Watarase wetland, Japan. expansion of pure stands of P. australis using a balloon sys-
tem with 12-cm spatial resolution (Artigas Pechmann
Methods 2010), the species forms extremely mixed stands with
M. sacchariflorus in the Watarase wetland, and finer spatial
The radio-controlled helicopter system
resolution is required for distinguishing these two species
The helicopter usedinthisstudyissmall (85 9 80 9 15 cm) in this wetland.
and light (1.6 kg, including its battery). Because the helicop-
ter has a small payload capacity (500 g), we used a
Conditions during aerial observations of the vegetation
lightweight compact digital camera (GX200; Ricoh, Tokyo,
Japan; Fig. 1b) as the image sensor. The continuous flight We performed the aerial observations on 10 July 2009. The
time is 20 min.Thehorizontal flight rangeiswithin 1 km of weather was cloudy. We set the digital camera’s focal
the operator due to radio control limitation, and maximum length at 24 mm, shutter speed at 1/500 s, diaphragm at
flight height is 300 m. The radio frequency of the control F5.1 and ISO setting at 200. The camera has an effective res-
system is 2.4 GHz. The helicopter includes an onboard olution of 12.1 megapixels. Our preliminary survey
GPS(LEA; u-blox,Thalwil,Switzerland). revealed that a maximum flying height of 30 m was needed
Although this small helicopter is suitable for high- to distinguish between P. australis and M. sacchariflorus
resolution photography, it is difficult to obtain high posi- (F. Ishihama et al., unpublished data) using these camera
tional accuracy using only the onboard GPS. To obtain settings, so we performed the survey at this height. Image
highly accurate georeferencing capability and to allow us resolution is a function of the flying height, effective pixel
to combine multiple digital pictures into one mosaic image, resolution and focal length. Given the above-mentioned
we used the Cartomaton software (Information Science settings, the spatial resolution of our images was 1 cm and
Techno-System Co., Ltd., Tsukuba, Japan). Cartomaton the areal footprint of each image was 30 9 40 m.
generates simple ortho-images (i.e. images corrected for We performed aerial observations in a 100 9 200-m
distortion caused by changes in flight attitude of an aircraft area. To cover this area, we took 99 photographs to allow
and by chromatic and spherical aberration resulting from for overlap between adjacent images within a given flight
the camera’s lens). This software estimates the external line and side-lap between adjacent flight lines. The Car-
orientation (three-dimensional position and angle) of the tomaton software requires 60% overlap and 30% side-lap
camera when the photos are taken. After performing geo- to combine the photographs into a single mosaic image; in
metric corrections based on those angles, the software pro- our study, we used 75% overlap and 30% side-lap.
jects the photographs onto a plane that is assumed to
represent the ground surface, and then combines all the
Study site for testing positional accuracy
photographs into a single georeferenced mosaic image.
During this processing sequence, it uses side-by-side pairs To test the positional accuracy of the ortho-mosaic image
of photos to calculate an external orientation; thus, it does and digital surface map (DSM) generated by the Falcon-
not require an inertial measurement unit (IMU) or ground PARS system, we conducted aerial observations in a
control points (GCP) to achieve precise corrections of research field at the National Institute for Environmental
distortion. Studies (140°4′41″ E, 36°3′3″ N). We chose this field as a



(a) (b)

(c) (d)

Fig. 2. (a) Location of the study site, the Watarase wetland, in Japan. (b) A simple ortho-image obtained by the radio-controlled helicopter remote-sensing
system. (c) A sample magnified image [location marked by light blue box in (b)]. (d) The resulting map of the species distribution identified from visual
interpretation of the magnified images.

study site because it was difficult to establish a sufficient GPS (Geodetic IV; Ashtech, Carquefou, France). The stan-
number of GCPs throughout the survey area in the dard deviations of the positioning accuracies of all GCPs
Watarase wetland due to the extremely dense and tall obtained with the GPS were 1 cm. The flight covered a
vegetation; this vegetation made it nearly impossible to walk 70 9 50-m area and we obtained 20 photographs (five
at the study site, which is why high-resolution remote- photographs per course).
sensing observations are required for monitoring of this site. After the photography, we performed baseline analysis
using the raw data from the onboard GPS. By using these
photographs and the analysed GPS data, we generated a
Conditions for testing positional accuracy
true ortho-mosaic image and DSM; we did not use any
We performed the aerial observations on 23 February GCP data to create these mosaic images.
2011. The camera settings, flying height and overlap and
side-lap settings were the same as those used in our obser-
Test of repeatability of the classification of plant species
vations of the wetland vegetation.
from the aerial image
We established ten 10 9 10-cm plates as GCPs, and
used these GCPs to evaluate the position accuracy of To test the repeatability of species classification based on
mosaic images. The coordinates of the ground control the mosaic image obtained from the aerial observation in
points were obtained using a two-carrier-wave-frequency Watarase wetland, we performed classification of plant



species by means of visual interpretation using three photo Table 1. Repeatability of the classification of plant species from aerial
interpreters. The three photo interpreters had different images. The numbers of image areas in which the three different interpret-
ers agreed or disagreed on species are shown.
experience in vegetation research: one was an experienced
plant ecologist, the second was a remote-sensing Pattern of classification by three interpreters Number of
researcher with little experience in vegetation surveys, image areas
and the third was a non-researcher who had experience Three interpreters classified as 39
assisting in vegetation surveys. Before the test, we taught Phragmites australis
the photo interpreters the criteria they should use to distin- Two interpreters classified as 6
guish among the three categories. Appendix S2 shows the P. australis, one as Miscanthus sacchariflorus
tutorial materials that were used. One interpreter classified as 10
P. australis, two as M. sacchariflorus
As samples of a classification test, we first selected 200
Three interpreters classified as M. sacchariflorus 45
random 30 9 30-cm test image areas within the image.
Then we omitted test image areas that meet at least one of
of image areas in which the three different interpreters
the following four criteria: (1) the image did not include
agreed or disagreed on species are shown in Table 1. When
either P. australis or M. sacchariflorus; (2) the image
we compared the classification by the two non-expert
included both P. australis and M. sacchariflorus; (3) the
photo interpreters to that of the experienced plant ecolo-
image was too dark because the area is composed of low
gist, the rates of correct answers were 90.0% and 93.0%,
plants shaded by surrounding tall plants; and (4) the image
respectively.
was blurred due to movement of leaves by wind. We omit-
ted the image that matched criteria 1 and 2 because such
areas require classification categories such as ‘other plants’ Discussion
and ‘both P. australis and M. sacchariflorus’ in the test. Set-
Because we used a helicopter that can hover above a
ting such categories can inflate repeatability of classifica-
desired position, we did not experience any of the prob-
tion, because it is expected that photo interpreters tend to
lems described in the Appendix S1: we obtained clear
choose these categories when they are not sure.
images with sufficient overlap to create a mosaic image.
Finally, we used 100 image areas for classification tests.
From the high-resolution mosaic image generated from
We asked each photo interpreter to classify the species of
the simple ortho-images (Fig. 2b,c) we could distinguish
the plant at the test areas using two categories: P. australis
both P. australis and M. sacchariflorus (also see Appendix S2
and M. sacchariflorus.
for ground images of these species) through visual inter-
pretation, with high repeatability among photo interpret-
Results
ers of different experience in vegetation research. An
Aerial observations of vegetation in the Watarase example of classification by the experienced photo inter-
wetland preter is shown in Fig. 2d. Because the resolution was
much higher than could be obtained using conventional
To obtain an image of the whole 100 9 200-m study area
aerial photographs (Table 2), the photo interpreters could
from a flying height of 30 m, it took only 11 min and 10 s.
use both colour differences and differences in form of the
We obtained clear images with sufficient overlap and side-
leaves and structure of the plant bodies as clues to assist in
lap, and were able to create a high-resolution mosaic
the identification of the two species. Because the colour
image from the simple ortho-images (Fig. 2 b,c).
depends on weather conditions (e.g. light intensity and
quality) and season (e.g. summer vs autumn leaves)
Test of positional accuracy
Table 2. Comparison of the characteristics of a remote-sensing system
We calculated the root-mean-square errors (RMSEs) for with a piloted aircraft and the radio-controlled helicopter system validated
the positions measured in the field at the National Institute in this study (the Falcon-PARS system).
for Environmental Studies. The RMSEs were 0.974 and Ordinary aerial Falcon-PARS
0.360 m for the horizontal and ellipsoidal body height photographs system (30-m
positioning errors, respectively. from a piloted aircraft flying height)

Highest resolution 5 cm 1 cm*
Area photographed in 1 h Several km2 ca. 0.06 km2
Repeatability of the classification of plant species from
Minimum weather Clear day Bright cloudy day
the aerial images conditions
The rate of agreement of the species classification among *Finer resolution is possible at a lower flying height, but this decreases the
the three photo interpreters was 84.0%, and the numbers area that can be photographed per hour.



during the aerial observations, the form of the plants is a record the status of vegetation. This is important for
more reliable clue to identify species. researchers because some vegetation changes its state so
We confirmed the ability of our system to provide a res- quickly that ground surveys cannot be performed suffi-
olution of ca. 1 cm while imaging natural herbaceous veg- ciently rapidly to cover the whole study area before it
etation. Although many studies (e.g. Lelong et al. 2008; changes (e.g. the state of flushing of spring ephemerals
Berni et al. 2009) have used unmanned aerial vehicles changes within a few days). In addition, this approach per-
(UAVs), few of these systems have attained a spatial reso- mits non-destructive surveys, which is very useful at frag-
lution finer than 5 cm. The only system we are aware of ile sites such as bogs. The approach also makes it possible
that provides 1-cm resolution is a helicopter-based UAV to monitor sites such as tree canopies or cliff faces that
system used for observation of coastal areas (Delacourt would be difficult or impossible to study in any other way.
et al. 2009). The other system attained resolutions of ca. The system’s portability (small size and light weight) is an
5 cm and was used to observe rangeland (Rango et al. additional advantage for use in such places.
2009). Previous UAV systems that attained a high spatial The studied species at the study site were relatively large
resolution (ranging from 1 to 5 cm) were large (1.0– grasses, making the plant characteristics easy to distin-
1.8 m) and heavy (10–11 kg, excluding image sensors) guish, but application to smaller herbs should be possible
and were therefore difficult to transport without ground using a lower flying height. Although observation speed
vehicles. Although such systems have some merits (larger decreases at a lower height, better resolution will be attain-
battery capacity and pay-load than the Falcon-PARS sys- able in the near future using a camera with a larger num-
tem), it would be difficult to take them to many study sites, ber of pixels without reducing flying height. We used a
such as alpine sites. Our system is only 1.6 kg including common compact digital camera with a relatively small
the battery (1.8 kg including the camera) and can there- number of effective pixels, but the remarkable speed of
fore be transported by a single person to almost all possible development of digital cameras suggests that higher image
study sites. Moreover, our system does not need any exter- quality will soon provide the same image resolution from a
nal orientation to obtain georeferenced images. This char- greater flying height (i.e. will allow observation of a larger
acteristic further reduces difficulties in field surveys; this area per unit time). In addition to high-resolution cameras,
system does not require setting GCPs in tall and dense veg- researchers can also use other sensors such as near-
etation where it is difficult to walk or in fragile bogs, or car- infrared cameras, which can be used to measure plant pho-
rying a heavy two-way GPS to sites that are difficult for tosynthetic activity. The only limitation of the system is
humans to approach with heavy baggage, such as alpine that the sensor must be light enough to mount on to the
sites. The main drawbacks of our system are small battery radio-controlled helicopter.
capacity (ca. 20 min of continuous flight time) and small The Falcon-PARS system is a promising tool for efficient,
payload (ca. 500 g), but its portability outweighs these non-destructive surveys of herbaceous vegetation.
drawbacks for sites such as bogs that are difficult to reach Although we identified plant species by eye in the present
with a vehicle and too fragile to survey on foot. It should study, the development of image analysis techniques to
also be noted that although the imagery has a spatial reso- automatically identify species will further improve the
lution of 1 cm, which allows for fine-scale image interpre- applicability of this system in the near future.
tation, the positional accuracy of ca. 1 m limits the
resolution of vegetation classification to larger areas in
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Validation of a high-resolution, remotely operated aerial remote-sensing system for the identiﬁcation of herbaceous plant species