Characterization of rice paddies by a uav mounted miniature hyperspectral sensor system zebros ieee

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CHARACTERIZATION OF RICE PADDIES BY A UAV-

MOUNTED MINIATURE HYPERSPECTRAL SENSOR

SYSTEM

ABSTRACT

The hyper spectral sensor system, equipped with a 256-band hyper spectral

sensor covering a spectral range from 340–763 nm, a GPS and a data logger, is 400 g in

total weight. A low-cost, small, lightweight hyperspectral sensor system that can be

loaded onto small unmanned autonomous vehicle (UAV) platforms has been developed

for the acquisition of aerial hyperspectral data. Safe and easy observation is possible

under unstable illumination conditions by using lightweight and autonomous cruising.

The acquisition period for each sampling, 768 bytes, is 100 ms. the aerial hyper spectral

data of rice paddies are collected under cloudy weather. The flight altitude from the

ground is 10 m, and the cruising speed is 2 m/s. The high-accuracy estimation of the

chlorophyll densities is confirmed, even under unstable illumination conditions, by

frequent monitoring of the illumination level and the chlorophyll indices, based on the

red-edge (RE) and near infrared (NIR) spectral ranges.

EXISTING SYSTEM

In our previous research, a hyper spectral array sensor system (spectral range:

400–1000 nm, 121 bands, spectral resolution: 5 nm, spatial dimension: 484 pixel, weight:

11 kg) was bottom-mounted onto an unmanned radio-controlled helicopter RMAX 18

(Yamaha Co., vehicle mass: 64 kg, payload: 30 kg). The helicopter’s flight altitude and

speed were 20 m and 15 km/h, respectively. The field of view (FOV) was 15, and the

frame rate (FPS) was 30; thus the spatial resolution of the acquired data was 0.14 m

(flight direction) 0.022 m (swath width). The chlorophyll concentration level was

demonstrated to be estimated with high accuracy, based on the hyper spectral images of

a paddy field. Zarco-Tejada et al. estimated the water stress level in a citrus orchard

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using spectral vegetation indices based on an aerial hyper spectral image. The hyper

spectral image was acquired by a micro-hyper spectral camera (spectral range: 400–885

nm, 260 bands, spectral resolution: 1.85 nm, weight: less than 3 kg) mounted onto a

UAV with a 5-m wingspan fixed-wing platform (Quanta Lab, IAS-CSIC, Spain, vehicle

mass: 13.5 kg, payload: 3 kg).

In the current Japanese agricultural field, the number of unmanned helicopters

for chemical crop dusting is over 2,400, and the number of licensed operators has

reached 14,000. These readily available helicopters could be powerful tools as platforms

of hyper spectral sensors. However, there are some obstacles to exploiting these

helicopters as a platform for hyper spectral observation: i) only a small number of

specially trained operators are permitted to control the helicopters for aerial observation

purposes, and ii) a helicopter crash would be a serious issue because of the heavy mass

and high power of the helicopter.

PROPOSED SYSTEM

Remotely sensed spectral maps are widely used for vegetation monitoring. In

flooded rice paddies are identified by the relationship between the land surface water

index (LSWI) and the enhanced vegetation index (EVI), which is based on the MODIS

image galleries. In agriculture, spectral information is also an important aid for land

management in precision farming because the spectral profiles of remotely sensed

vegetation are determined by the combination of pigment absorption and volume

scattering.

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BLOCK DIAGRAM

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By using ground-based hyper spectral acquisition systems, the acquisition of

spatially high-resolution hyperspectral images free from atmospheric absorption and

scattering is possible. A spatially wide range of area is covered in an aerial

hyperspectral image by an airborne sensor system.

We introduce a newly developed, low-cost, lightweight hyperspectral sensor

system. The developed sensor system, equipped with a 256-band hyperspectral

sensor with a spectral range from 340 to 763 nm, a GPS, and a data logger, is 400

g in total weight.

Chlorophyll densities are estimated based on the low altitude aerial

hyperspectral data of rice paddies captured by the developed UAV-mounted

hyperspectral sensor system.

The estimation results are compared with the ground truth values, i.e., SPAD

readings of the contact transparent leaf-color monitoring device SPAD, together

with the estimation accuracies of the spectral chlorophyll indices, to evaluate the

quality of the acquired data.

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We developed a miniature hyperspectral sensor system, which is composed of the

following elements: 1) a hyper spectral sensor, 2) a GPS sensor, 3) a data logger, 4) a

LCD display and control switches, and 5) a power supply... The gross weight of the

hyperspectral sensor system is 400 g.

ADVANTAGE

Low power

Low cost

Good efficiency

Less noise

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0th Review 1st Review

Abstract Existing System Disadvantages Proposed System Advantages Objective System Requirements System Architecture

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Characterization of rice paddies by a uav mounted miniature hyperspectral sensor system zebros ieee