validation of a high-resolution, remotely operated aerial remote-sensing system for the...

Applied Vegetation Science 15 (2012) 383–389

Validation of a high-resolution, remotely operatedaerial remote-sensing system for the identification ofherbaceous plant species

Fumiko Ishihama, Yasuyuki Watabe & Hiroyuki Oguma

Keywords

High positioning accuracy; Non-destructive

survey; Portable remote-sensing system;

Radio-controlled helicopter; Wetland

Abbreviations

IMU = Inertial measurement unit; GCP =

Ground control point

Nomenclature

BG Plants Japanese-name-scientific-name Index

(YList), http://bean.bio.chiba-u.jp/bgplants/

ylist_main.html (accessed 30 November 2011)

Received 15 July 2010

Revised 30 November 2011

Accepted 20 December 2011

Co-ordinating Editor: Aaron Moody

Ishihama, F. (corresponding author,

[email protected]) &Oguma, H.

([email protected]): National Institute for

Environmental Studies, Onogawa, Tsukuba,

Ibaraki 305-8506, Japan

Watabe, Y. ([email protected]):

Information & Science Techno-System Co.,

Ltd., Takezono, Tsukuba, Ibaraki 305-0032,

Japan

Abstract

Question: Is a high-resolution remote-sensing system based on a radio-

controlled helicopter (the ‘Falcon-PARS system’) an effective tool to obtain

images that can be used to identify herbaceous species?

Location:Watarase wetland, Japan.

Methods: We applied the remote-sensing system to a wetland composed

mainly of Phragmites australis andMiscanthus sacchariflorus. The aerial observation

was performed in a 100 9 200 m area at a flying height of 30 m. From the

obtained images, we tried to identify P. australis and M. sacchariflorus through

visual interpretation.

Results: We obtained images with a high spatial resolution (1 cm) and a posi-

tioning accuracy of finer than 1 m using this small and lightweight system, and

confirmed that we could identify the above two species from the obtained

images.

Conclusion: Such a high-resolution system can be used to directly identify her-

baceous species, and as a non-destructive alternative to ground surveys. This

lightweight system can be carried to sites such as a high-altitude bog that cannot

be reached by a motor vehicle. Because of the low flying height (below cloud

level), aerial observation is possible even on cloudy days, thereby permitting

observations in all seasons.

Introduction

Remote sensing is a convenient tool for efficient, non-

destructive mapping of vegetation over wide spatial scales.

Satellite and aircraft remote sensing is widely used to

obtain distribution maps of vegetation classification (De-

Fries 2008; Xie et al. 2008; Hill et al. 2010) and habitat

maps of species (Kerr & Ostrovsky 2003), and to estimate

biomass (e.g. Boudreau et al. 2008) and plant phenology

(Verbesselt et al. 2010; Reed et al. 2009). Although these

remote-sensing systems are effective for such observations,

they are only useful for relatively large targets, such as tall

trees, or for rough classification of vegetation types. This is

because the resolution of these systems is relatively low

(5 cm at best for aircraft remote sensing). To identify her-

baceous or small woody species or to classify vegetation

type in detail, fine-scale remote sensing with a resolution

of � 1 cmwould be required.

Although there is an inevitable trade-off between reso-

lution and observation speed, a high-resolution remote-

sensing system capable of distinguishing among detailed

vegetation types or identifying small plant species has

advantages that outweigh its reduced speed. The first is

that it permits non-destructive observation. Ground sur-

veys sometimes cause substantial damage to the vegeta-

tion, particularly at fragile sites such as bogs. Although

long-term monitoring is required to examine changes in

biodiversity and to plan effective conservation measures

(Marsh & Trenham 2008), damage to vegetation during

monitoring on foot can be especially serious when

repeated surveys are required. Remote sensing with suffi-

ciently high resolution would be a valuable alternative to

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

ground surveys because it would reduce or eliminate dam-

age to vegetation. A second advantage is the ability to

obtain detailed observations of sites that are difficult for

humans to approach, such as cliff faces and the canopies of

tall trees. Third, even if the speed is relatively limited,

high-resolution remote sensing still provides a faster tool

for mapping individual plants than is possible in surveys

conducted on foot.

The criteria for a remote-sensing system suitable for

high-resolution observation include high positioning accu-

racy, a robust ability to work under a range of weather

conditions, and portability (light weight). High positioning

accuracy is essential to allow comparison of images from

different times so that researchers can monitor temporal

changes in vegetation and can overlay images with other

geographical information, such as elevation. Robustness

under a range of weather conditions is required to permit

surveys in all seasons. Phenological changes represent

information that can be used to distinguish plant species,

and multi-seasonal observations capable of detecting phe-

nological changes are an effective way to distinguish plant

species or vegetation types (Gilmore et al. 2008). Remote

sensing from piloted aircraft is possible only under a lim-

ited range of weather conditions (i.e. clear days) because

the piloted aircraft fly as high as 2000 m, and their sensors

may be blocked by low cloud. Obtaining a cloud-free

image is also an important problem for satellite remote

sensing (Xie et al. 2008; Wang et al. 2009). Such limita-

tions often make it difficult to perform surveys in certain

seasons. Portable systems would be required at study sites

such as those at high altitudes, wetlands and oceanic

islands, which are usually inaccessible to ground vehicles.

Remote sensing using a radio-controlled helicopter,

fixed-wing aircraft and balloon is a potential candidate for

high-resolution remote sensing because such vehicles can

fly at much lower altitudes than piloted aircraft. The effec-

tiveness of these systems for ecological or agricultural sur-

veys that require resolutions ranging from several meters

to several tens of centimeters has been reported (Davis &

Johnson 1991; Gerard et al. 1997; Johnson et al. 2004;

Miyamoto et al. 2004; Sugiura et al. 2005; Berni et al.

2009; Artigas & Pechmann 2010). However, some of these

systems are not suitable to capture georeferenced high-

resolution images at resolutions of 1 cm or finer in a non-

destructive way. A balloon system is very vulnerable to

wind, and it is difficult to control its position, especially in

high-resolution surveys, which require delicate position-

ing control with accuracy finer than a fewmeters. Because

tethered balloon systems need to be towed by a human for

positioning control, they can cause damage to vegetation

in study sites susceptible to trampling. In addition, balloon

systems require containers of pressurized, lighter-than-air

gas, which cannot be carried by humans over long dis-

tances to reach remote sites. Although fixed-wing aircraft

have superior positioning control and robustness against

wind, their high flight speed can cause serious problems;

obtaining high-resolution images with sufficiently high

positioning accuracy faces many specific problems (e.g.

motion blur in the images due to a combination of insuffi-

cient light and an insufficiently high camera shutter

speed). These problems can be solved by flying more

slowly or by hovering, if the aircraft has a low level of

vibration (Appendix S1). In addition, a fixed-wing aircraft

often requires flight strips for takeoff and landing, and

these are rarely available in survey areas.

To solve these problems, we chose a lightweight

remote-sensing system capable of hovering and with

low vibration. To meet these criteria, we chose a heli-

copter (AscTec Falcon 8; Ascending Technologies GmbH,

Krailling, Germany; Fig. 1a) that can hover at the

assigned coordinates (using an autopilot function) and

obtain photographs by automatically activating the cam-

era shutter. It is only in the last few years that light-

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.

Applied Vegetation Science384 Doi: 10.1111/j.1654-109X.2012.01184.x© 2012 International Association for Vegetation Science

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

autopilot function became available. The autopilot func-

tion allows the aircraft to fly along a predefined course

and obtain photographs automatically at preset coordi-

nates, and it is therefore an essential function for easy

and speedy image acquisition. Such systems have been

developed mainly for military (Newcome 2004) or geo-

graphical use (e.g. Delacourt et al. 2009), so their appli-

cability to plant surveys has rarely been evaluated (but

see Rango et al. 2009).

In this study, we aimed to validate the use of a remote-

sensing system based on a radio-controlled helicopter to

examine whether it could satisfy our criteria (high resolu-

tion, positioning accuracy, robustness across a range of

weather conditions, and portability) for monitoring of her-

baceous plants. We tested whether we could use images

obtained by this system to distinguish among herbaceous

plants species in theWatarase wetland, Japan.

Methods

The radio-controlled helicopter system

Thehelicopterusedinthisstudyissmall(85 9 80 9 15 cm)

andlight(1.6 kg, including itsbattery).Becausethehelicop-

ter has a small payload capacity (500 g), we used a

lightweight compact digital camera (GX200; Ricoh, Tokyo,

Japan; Fig. 1b) as the image sensor. The continuous flight

timeis<20 min.Thehorizontalflightrangeiswithin1 kmof

the operator due to radio control limitation, andmaximum

flight height is 300 m. The radio frequency of the control

system is 2.4 GHz. The helicopter includes an onboard

GPS(LEA;u-blox,Thalwil,Switzerland).

Although this small helicopter is suitable for high-

resolution photography, it is difficult to obtain high posi-

tional accuracy using only the onboard GPS. To obtain

highly accurate georeferencing capability and to allow us

to combinemultiple digital pictures into onemosaic image,

we used the Cartomaton software (Information & Science

Techno-System Co., Ltd., Tsukuba, Japan). Cartomaton

generates simple ortho-images (i.e. images corrected for

distortion caused by changes in flight attitude of an aircraft

and by chromatic and spherical aberration resulting from

the camera’s lens). This software estimates the external

orientation (three-dimensional position and angle) of the

camera when the photos are taken. After performing geo-

metric corrections based on those angles, the software pro-

jects the photographs onto a plane that is assumed to

represent the ground surface, and then combines all the

photographs into a single georeferenced mosaic image.

During this processing sequence, it uses side-by-side pairs

of photos to calculate an external orientation; thus, it does

not require an inertial measurement unit (IMU) or ground

control points (GCP) to achieve precise corrections of

distortion.

We have named this system (helicopter, digital camera

and Cartomaton software) the ‘Falcon- photogrammetry

and remote-sensing (PARS)’ system.

Study site for the aerial observation of vegetation

We tested the Falcon-PARS system in the Watarase wet-

land of central Japan (139°41′ E, 36°14′ N, 14 m a.s.l.;

Fig. 2a). TheWatarasewetland is a floodplain wetland that

covers about 1500 ha, and its vegetation is mainly com-

posed of Phragmites australis (Cav.) Trin. ex Steud. and

Miscanthus sacchariflorus (Maxim.) Benth. Because these

species form dense vegetation that reaches a maximum

height of 4 m in July, ground surveys are impractical, and

remote sensing is therefore an essential monitoring tool.

Although a previous study reported successful detection of

expansion of pure stands of P. australis using a balloon sys-

tem with 12-cm spatial resolution (Artigas & Pechmann

2010), the species forms extremely mixed stands with

M. sacchariflorus in the Watarase wetland, and finer spatial

resolution is required for distinguishing these two species

in this wetland.

Conditions during aerial observations of the vegetation

We performed the aerial observations on 10 July 2009. The

weather was cloudy. We set the digital camera’s focal

length at 24 mm, shutter speed at 1/500 s, diaphragm at

F5.1 and ISO setting at 200. The camerahas an effective res-

olution of 12.1 megapixels. Our preliminary survey

revealed that amaximumflyingheight of 30 mwasneeded

to distinguish between P. australis and M. sacchariflorus

(F. Ishihama et al., unpublished data) using these camera

settings, so we performed the survey at this height. Image

resolution is a function of the flying height, effective pixel

resolution and focal length. Given the above-mentioned

settings, the spatial resolution of our images was 1 cm and

the areal footprint of each imagewas 30 9 40 m.

We performed aerial observations in a 100 9 200-m

area. To cover this area, we took 99 photographs to allow

for overlap between adjacent images within a given flight

line and side-lap between adjacent flight lines. The Car-

tomaton software requires 60% overlap and 30% side-lap

to combine the photographs into a single mosaic image; in

our study, we used 75% overlap and 30% side-lap.

Study site for testing positional accuracy

To test the positional accuracy of the ortho-mosaic image

and digital surface map (DSM) generated by the Falcon-

PARS system, we conducted aerial observations in a

research field at the National Institute for Environmental

Studies (140°4′41″ E, 36°3′3″ N). We chose this field as a


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

study site because it was difficult to establish a sufficient

number of GCPs throughout the survey area in the

Watarase wetland due to the extremely dense and tall

vegetation; thisvegetationmadeitnearly impossible towalk

at the study site, which is why high-resolution remote-

sensingobservationsare required formonitoringof this site.

Conditions for testing positional accuracy

We performed the aerial observations on 23 February

2011. The camera settings, flying height and overlap and

side-lap settings were the same as those used in our obser-

vations of the wetland vegetation.

We established ten 10 9 10-cm plates as GCPs, and

used these GCPs to evaluate the position accuracy of

mosaic images. The coordinates of the ground control

points were obtained using a two-carrier-wave-frequency

GPS (Geodetic IV; Ashtech, Carquefou, France). The stan-

dard deviations of the positioning accuracies of all GCPs

obtained with the GPS were <1 cm. The flight covered a

70 9 50-m area and we obtained 20 photographs (five

photographs per course).

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

true ortho-mosaic image and DSM; we did not use any

GCP data to create these mosaic images.

Test of repeatability of the classification of plant species

from the aerial image

To test the repeatability of species classification based on

the mosaic image obtained from the aerial observation in

Watarase wetland, we performed classification of plant

(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.



species by means of visual interpretation using three photo

interpreters. The three photo interpreters had different

experience in vegetation research: one was an experienced

plant ecologist, the second was a remote-sensing

researcher with little experience in vegetation surveys,

and the third was a non-researcher who had experience

assisting in vegetation surveys. Before the test, we taught

the photo interpreters the criteria they should use to distin-

guish among the three categories. Appendix S2 shows the

tutorial materials that were used.

As samples of a classification test, we first selected 200

random 30 9 30-cm test image areas within the image.

Then we omitted test image areas that meet at least one of

the following four criteria: (1) the image did not include

either P. australis or M. sacchariflorus; (2) the image

included both P. australis and M. sacchariflorus; (3) the

image was too dark because the area is composed of low

plants shaded by surrounding tall plants; and (4) the image

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’

and ‘both P. australis and M. sacchariflorus’ in the test. Set-

ting such categories can inflate repeatability of classifica-

tion, because it is expected that photo interpreters tend to

choose these categories when they are not sure.

Finally, we used 100 image areas for classification tests.

We asked each photo interpreter to classify the species of

the plant at the test areas using two categories: P. australis

andM. sacchariflorus.

Results

Aerial observations of vegetation in theWatarase

wetland

To obtain an image of the whole 100 9 200-m study area

from a flying height of 30 m, it took only 11 min and 10 s.

We obtained clear images with sufficient overlap and side-

lap, and were able to create a high-resolution mosaic

image from the simple ortho-images (Fig. 2 b,c).

Test of positional accuracy

We calculated the root-mean-square errors (RMSEs) for

the positions measured in the field at the National Institute

for Environmental Studies. The RMSEs were 0.974 and

0.360 m for the horizontal and ellipsoidal body height

positioning errors, respectively.

Repeatability of the classification of plant species from

the aerial images

The rate of agreement of the species classification among

the three photo interpreters was 84.0%, and the numbers

of image areas in which the three different interpreters

agreed or disagreed on species are shown in Table 1.When

we compared the classification by the two non-expert

photo interpreters to that of the experienced plant ecolo-

gist, the rates of correct answers were 90.0% and 93.0%,

respectively.

Discussion

Because we used a helicopter that can hover above a

desired position, we did not experience any of the prob-

lems described in the Appendix S1: we obtained clear

images with sufficient overlap to create a mosaic image.

From the high-resolution mosaic image generated from

the simple ortho-images (Fig. 2b,c) we could distinguish

both P. australis andM. sacchariflorus (also see Appendix S2

for ground images of these species) through visual inter-

pretation, with high repeatability among photo interpret-

ers of different experience in vegetation research. An

example of classification by the experienced photo inter-

preter is shown in Fig. 2d. Because the resolution was

much higher than could be obtained using conventional

aerial photographs (Table 2), the photo interpreters could

use both colour differences and differences in form of the

leaves and structure of the plant bodies as clues to assist in

the identification of the two species. Because the colour

depends on weather conditions (e.g. light intensity and

quality) and season (e.g. summer vs autumn leaves)

Table 1. Repeatability of the classification of plant species from aerial

images. The numbers of image areas in which the three different interpret-

ers agreed or disagreed on species are shown.

Pattern of classification by three interpreters Number of

image areas

Three interpreters classified as

Phragmites australis

39

Two interpreters classified as

P. australis, one asMiscanthus sacchariflorus

6

One interpreter classified as

P. australis, two asM. sacchariflorus

10

Three interpreters classified asM. sacchariflorus 45

Table 2. Comparison of the characteristics of a remote-sensing system

with a piloted aircraft and the radio-controlled helicopter system validated

in this study (the Falcon-PARS system).

Ordinary aerial

photographs

from a piloted aircraft

Falcon-PARS

system (30-m

flying height)

Highest resolution 5 cm 1 cm*

Area photographed in 1 h Several km2 ca. 0.06 km2

Minimumweather

conditions

Clear day Bright cloudy day

*Finer resolution is possible at a lower flying height, but this decreases the

area that can be photographed per hour.



during the aerial observations, the form of the plants is a

more reliable clue to identify species.

We confirmed the ability of our system to provide a res-

olution of ca. 1 cm while imaging natural herbaceous veg-

etation. Although many studies (e.g. Lelong et al. 2008;

Berni et al. 2009) have used unmanned aerial vehicles

(UAVs), few of these systems have attained a spatial reso-

lution finer than 5 cm. The only system we are aware of

that provides 1-cm resolution is a helicopter-based UAV

system used for observation of coastal areas (Delacourt

et al. 2009). The other system attained resolutions of ca.

5 cm and was used to observe rangeland (Rango et al.

2009). Previous UAV systems that attained a high spatial

resolution (ranging from 1 to 5 cm) were large (1.0–

1.8 m) and heavy (10–11 kg, excluding image sensors)

and were therefore difficult to transport without ground

vehicles. Although such systems have some merits (larger

battery capacity and pay-load than the Falcon-PARS sys-

tem), it would be difficult to take them tomany study sites,

such as alpine sites. Our system is only 1.6 kg including

the battery (1.8 kg including the camera) and can there-

fore be transported by a single person to almost all possible

study sites. Moreover, our system does not need any exter-

nal orientation to obtain georeferenced images. This char-

acteristic further reduces difficulties in field surveys; this

system does not require setting GCPs in tall and dense veg-

etationwhere it is difficult to walk or in fragile bogs, or car-

rying a heavy two-way GPS to sites that are difficult for

humans to approach with heavy baggage, such as alpine

sites. The main drawbacks of our system are small battery

capacity (ca. 20 min of continuous flight time) and small

payload (ca. 500 g), but its portability outweighs these

drawbacks for sites such as bogs that are difficult to reach

with a vehicle and too fragile to survey on foot. It should

also be noted that although the imagery has a spatial reso-

lution of 1 cm, which allows for fine-scale image interpre-

tation, the positional accuracy of ca. 1 m limits the

resolution of vegetation classification to larger areas in

which the positional error is negligible.

It took only 11 min and 10 s to obtain an image of the

entire 100 9 200-m study area from a flying height of

30 m. A survey performed at this speed covers a much

smaller area than would be covered by conventional aerial

remote sensing with a piloted aircraft (Table 2) because of

the inevitable trade-off between image resolution and fly-

ing speed. However, this was still remarkably faster than

would have been possible by means of a ground survey.

Even though additional time is required to process the data

to produce the true ortho-image (5–6 h per 100 photo-

graphs, although this time varies depending on perfor-

mance of a personal computer) and classify the vegetation

types from the image, we were nonetheless able to rapidly

record the status of vegetation. This is important for

researchers because some vegetation changes its state so

quickly that ground surveys cannot be performed suffi-

ciently rapidly to cover the whole study area before it

changes (e.g. the state of flushing of spring ephemerals

changes within a few days). In addition, this approach per-

mits non-destructive surveys, which is very useful at frag-

ile sites such as bogs. The approach also makes it possible

to monitor sites such as tree canopies or cliff faces that

would be difficult or impossible to study in any other way.

The system’s portability (small size and light weight) is an

additional advantage for use in such places.

The studied species at the study site were relatively large

grasses, making the plant characteristics easy to distin-

guish, but application to smaller herbs should be possible

using a lower flying height. Although observation speed

decreases at a lower height, better resolutionwill be attain-

able in the near future using a camera with a larger num-

ber of pixels without reducing flying height. We used a

common compact digital camera with a relatively small

number of effective pixels, but the remarkable speed of

development of digital cameras suggests that higher image

quality will soon provide the same image resolution from a

greater flying height (i.e. will allow observation of a larger

area per unit time). In addition to high-resolution cameras,

researchers can also use other sensors such as near-

infrared cameras, which can be used tomeasure plant pho-

tosynthetic activity. The only limitation of the system is

that the sensor must be light enough to mount on to the

radio-controlled helicopter.

The Falcon-PARS system is a promising tool for efficient,

non-destructive surveys of herbaceous vegetation.

Although we identified plant species by eye in the present

study, the development of image analysis techniques to

automatically identify species will further improve the

applicability of this system in the near future.

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Supporting Information

Additional supporting information may be found in the

online version of this article:

Appendix S1. Possible problems in high-resolution

remote sensing (with resolution finer than 1 cm) and

solutions.

Appendix S2. Ground-level photographs of the

leaves and plant bodies of (a,c) Phragmites australis and

(b,d) Miscanthus sacchariflorus. The remote-sensing

images magnified from Fig. 1(c,d): (e) P. australis and (f)

M. sacchariflorus.

Please note: Wiley-Blackwell are not responsible for

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validation of a high-resolution, remotely operated aerial remote-sensing system for the...

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