The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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1.1 (Ultra) High-Resolution Remote Sensing in 
Agriculture 
In the past, the majority of remote sensing applications in 
agriculture were either satellite- or ground-based. Over the last 
few years we have seen a rapid increase in airborne remote 
sensing due to the proliferation of multispectral digital airborne 
sensors (Biihler et al., 2007), (Petrie and Walker, 2007). 
Table 1 gives an overview of the different remote sensing 
platforms with the typical spatial resolution of their 
multispectral channels and with their typical fields-of-view 
(FOV). This overview illustrates the current resolution gap at 
the cm to dm level which could ideally be filled by miniature 
UAVs. 
Remote Sensing 
Platform 
Typical Spatial 
Resolution (MS) 
Typical Field- 
of-View (FOV) 
Satellite 
2-15 m 
10-50 km 
Aircraft (piloted) 
0.2-2 m 
2-5 km 
Miniature UA V ? 
1-20 cm 
50-500 m 
Ground-based 
< 1 cm 
< 2 m 
Table 1: Typical spatial resolutions and fields-of-view of 
different remote sensing platforms - with a spatial resolution 
gap between 1 and 10 cm which could be filled by miniature 
UAVs. 
The trend towards very high-resolution airborne remote sensing 
with spatial resolutions in the range of centimetre to decimetre 
is driven by agronomical research, management of speciality 
crops and investigations of within-field variability in general. 
The shift towards precision, or site-specific, crop management, 
and the resulting interest in within-field variability, for example, 
has been identified as the most significant change in agriculture 
over the last ten to fifteen years (Pinter et al., 2003). Further 
potential application areas of very high-resolution UAV-based 
remote sensing might be the detection and mapping of plant 
diseases such as fire blight or the investigation contaminated 
sites. 
In the following we will primarily focus on the application area 
of agronomical research. However, most of the characteristics, 
requirements and conclusions also apply to the management of 
specialty crops. The term specialty crops includes fruits, 
vegetables, tree nuts, dried fruits, and nursery crops (including 
floriculture) (USDA, 2004) as well as grapevines, which were 
used in the subsequent investigations. 
The characteristics and the subsequent remote sensing 
requirements of field tests sites can be summarised as follows: 
• very small plot sizes down to one square metre resulting in 
a ground sampling distance (GSD) in the order of 5-10 cm 
in order to ensure statistically reliable results for each test 
plot 
• regular frequent observations at weekly intervals and at 
short notice in order to observe different phenological 
developments or other rapidly evolving phenomena 
• the manifold of plant species at a test site and the desire to 
find a single solution capable for all vegetation types 
• relatively simple, robust and rapid processing procedures 
with a high level of automation 
1.2 Miniature UAVs as Remote Sensing Platforms 
Over the last few years we have seen a tremendous 
development of UAV technologies at all conceivable sizes, 
from business jet sized UAVs right down to artificial 'flying 
insects'. There is also an increasing number of projects with the 
aim of using UAVs for remote sensing purposes. These UAV 
platforms for civilian remote sensing purposes range from large 
UAVs (Coronado et al., 2003), (Herwitz et al., 2002) through 
mini UAVs (Johnson et al., 2003), (Eisenbeiss, 2004), (Annen 
et al., 2007) to micro UAVs presented in this paper (see Table 
2). 
Due to the rapid development and the ever increasing number 
of new UAV concepts and technologies, it has become a 
necessity to try and establish a certain classification for UAVs. 
The European Association of Unmanned Vehicle Systems 
(EUROUVS) has drawn up such classification of UAV systems, 
which we will adhere to in this paper. A good overview and 
state-of-the-art of UAV systems which is based on the 
EUROUVS classification can be found in (Bento, 2008). 
Category 
Max. 
Take Off 
Weight 
Max. 
Flight 
Altitude 
Endurance 
Data 
Link 
Range 
Micro 
< 5kg 
250m 
lh 
< 10km 
Mini 
< 30kg 
150-300m 
<2h 
< 10km 
Table 2: Classification mini- and micro UAV systems 
Since our UAV-based remote sensing platform is to be 
transportable and to be operated locally under minimal legal 
restrictions, candidate platforms are limited to the categories of 
mini and micro UAVs (see Table 2). Most mini or micro UAV 
systems available today integrate a flight control system, which 
autonomously stabilises the platform and supports remotely 
controlled navigation. Several systems additionally integrate an 
autopilot, which permits autonomous flights based on 
predefined waypoints - often in combination with 
programmable image acquisition. These flight control systems 
are typically based on MEMS (Micro-Electro-Mechanical 
System) IMU systems, navigation-grade GPS receivers, 
barometers, and magnetic compasses. The different sensor 
observations are usually integrated to an optimal flight state 
using an EKF (Extended Kalman Filter), which is subsequently 
used in the flight controller. For mapping applications, it is also 
possible to use this flight control data to geo-register the 
captured payload sensor data like still images or video streams. 
However, as a result of the utilisation of low weight and low 
cost flight control sensors, the achievable direct geo-referencing 
accuracy is limited to approx. 5-10 metres (Eugster and Nebiker, 
2008). 
1.3 Low-weight Remote Sensing Payloads 
The use of mini or micro UAVs for remote sensing purposes 
introduces a number of constraints on the imaging payloads, 
namely limitations in terms of weight, power, and space. In 
case of micro UAVs there are also very limited possibilities for 
payload stabilisation or for the highly accurate direct sensor 
georeferencing. Typical weight limitations for imaging 
payloads are approx. 20-30% of total weight of the system, e.g. 
approximately 300g in case of 1kg micro UAVs and around 5kg 
in case of 25-30 kg mini UAVs. While there are an increasing 
number of light-weight imaging sensors for the visible spectrum 
and for thermal infrared, the situation is completely different in