Mr. Fevzi Ametov Profile

Fevzi Ametov

at Drone.UA

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 18 October 2018 Presentation + Paper

COTS UAV-borne multispectral system for vegetation monitoring

Taras Kazantsev, Viktor Shevchenko, Oksana Bondarenko, Mykhailo Furier, Andre Samberg, Fevzi Ametov, Valerii Iakovenko

Proceedings Volume 10783, 107830A (2018) https://doi.org/10.1117/12.2501859

KEYWORDS: Near infrared, Vegetation, Sensors, RGB color model, Multispectral imaging, Satellites, Digital cameras, Unmanned aerial vehicles, Satellite imaging, Cameras

Read Abstract +

This paper describes the results of the work, which was divided into three parts: 1) the proof-of-concept of lightweight low cost UAV-borne multispectral NIR (shortwave infrared) sensor, 2) the evaluation of performances of airborne tailored NIR sensor vs. consumer-grade RGB digital camera, and 3) the feasibility study and the comparison of NIR multispectral data vs. Sentinel-2A high-resolution satellite multispectral imagery. The moderated cost-efficient UAV-borne imaging remote sensing solution was requested by the agricultural sector in Ukraine. The existing solutions did not meet the requirements of the end user neither suitable high-resolution satellite multispectral imagery was available too. The designed system integrated consumer-grade RGB digital camera and NIR sensor. Multi-temporary data was collected eight times during one growth season. Eight aerial missions were conducted in midsummer 2015 over the same area, which consisted of 50 plots with various cultivars of wheat, barley and rye. The vegetation indices were calculated for both datasets. Vegetation indices calculated from the NIR sensor highly correlated with plant chlorophyll and plant LAI, and revealed satisfactory correlation with plant fresh mass. Vegetation indices derived from onboard RGB camera did not reveal the significant correlation with any of plant growth parameter. The NDVI values calculated from NIR data demonstrated high correlation with the ones, which were derived from the Sentinel-2 high-resolution satellite multispectral images. The values of UAV-derived NDVI were lower than Sentinel-2-derived NDVI, and the regression slope of this relationship varied in different plant species. Reasons of such variation are discussed in the paper. After the numerous field-tests the customer accepted the developed tailored COTS UAV-borne multispectral solution cost-efficient and sufficient.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years