The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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Phase I - Remote Sensing vs. Ground Truth (Row 3, 2006) 
Li 
Remotely S«nsadR«sults (NOVI) 
Ground Tr oth (Damaged Leaves (%]) J 
Figure 4: Percentage of damaged leaves - Remotely sensed 
results (solid green line) and reference data (red dashed line). 
3. MSMS - PROJECT PHASE II 
After project phase I had shown very encouraging and robust 
results, despite the use of an improvised and unfavourable 
sensor constellation it was decided to develop a prototype of a 
low-cost light-weight airborne multispectral sensor, which 
could ideally be flown on the latest generation of rotary or fixed 
wing mini or even micro UAVs. 
3.1 Sensor Platforms: Micro UAV and Mini UAV 
The latest generation of quadcopter micro UAVs with vertical 
take-off and landing (VTOL) capability and with maximum 
payloads currently in the range of 200g and expected to be in a 
range of 1kg could provide ideal remote sensing platforms for 
local applications such as agronomical field tests and the 
management of specialty crops. In our case, the micro UAV 
'microdrones md4-200' (see Figure 5) served as target platform 
for the MSMS sensor. The md4-200 is an electrically powered, 
GPS/INS-equipped quadcopter with an official maximum 
payload of 200g, an unofficial maximum payload of approx. 
350g, and a maximum flying time of approx. 20 minutes. 
Figure 5: Quadcopter micro UAV 'microdrones md4-200' 
with the prototype MSMS multispectral sensor. 
3.2 The MSMS Sensor 
Based on the earlier results and on the availability of sensor 
hardware components at the start of the development, the 
design decisions for a low-cost, low-weight MSMS sensor were 
as follows: a modular multi-camera concept (see Introduction) 
with one camera per band to be sensed - initially limited to the 
two bands Red and NIR with the option to extend the number of 
channels by incorporating additional camera heads; 
panchromatic full frame sensor elements (with the option to 
upgrade to higher resolution sensor elements as they become 
available); identical, high-grade but low-weight lenses for all 
sensor heads; interference filters for the selection of the desired 
spectral bands; use of a programmable camera controller with 
support for on-board storage of the acquired imagery. The main 
features of the current MSMS prototype sensor are: 
• two cameras with full frame CMOS sensor elements 
(sensor heads MT9V022m integrated into CanCam), 752 * 
480 pixels per channel with global shutter (Company: 
Feith Sensor to Image) 
• CanCam controller with CPU Motorola Coldfire MCF5272 
66 MHz and pCLinux (Feith) 
• Light-weight C-mount lenses, focal length 8.0mm, F1.3, 
interference filters with central wavelengths of 650 nm (R) 
and 880 nm (NIR) and a full width-half maximum (FWHM) 
of 80 nm and 50 nm respectively 
• total weight of the MSMS prototype: 350 g (including 
controllers, sensor heads, and the custom-built light-weight 
camera frame; sensor powered by UAV battery) 
3.3 Field Test Campaign 
Due to supply difficulties and an approaching end of the 
vegetation season only one test flight campaign could be carried 
out so far with the described combination of the MSMS sensor 
and the md4-200 platform (17 th of August 2007). The test flight 
was again carried out over a grapevine field at the Syngenta test 
field in Stein. Since the current sensor exceeds the official 
payload limit and since the unofficial payload communicated 
by the manufacturer of the UAV turned out to be too optimistic, 
data acquisition was only possible in the absence of any wind 
and the acquired imagery was limited to a part of the field only. 
Figure 6: One of the first MSMS scenes (part) with radiometric 
calibration targets (large) and ground control points (small). 
3.4 Preliminary Results 
Due to the mentioned difficulties in acquiring the first imagery, 
there were again a number of challenges in processing the data. 
However, these challenges were mainly caused by the very 
irregular constellation of the acquired imagery covering only 
parts of the area of investigation. Due to the use of a multi 
camera payload, the processing chain can principally be 
simplified in comparison to the processing steps used in phase I. 
Namely the step of a true orthoimage production will no longer 
be needed. Early results support the findings from phase I and 
again show a strong correlation between plant health status 
obtained via remote sensing with the MSMS prototype and the 
ground-truth data from the traditional bonification process.