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Photochemical Reflectance Index (PRI) Mapping using Drone-based Hyperspectral Image for Evaluation of Crop Stress and its Application to Multispectral Imagery

작물 스트레스 평가를 위한 드론 초분광 영상 기반 광화학반사지수 산출 및 다중분광 영상에의 적용

Na, Sang-il;Park, Chan-won;So, Kyu-ho;Ahn, Ho-yong;Lee, Kyung-do
나상일;박찬원;소규호;안호용;이경도

  • Received : 2019.09.25
  • Accepted : 2019.10.01
  • Published : 2019.10.31

Abstract

The detection of crop stress is an important issue for the accurate assessment of yield decline. The photochemical reflectance index (PRI) was developed as a remotely sensed indicator of light use efficiency (LUE). The PRI has been tested in crop stress detection and a number of studies demonstrated the feasibility of using it. However, only few studies have focused on the use of PRI from remote sensing imagery. The monitoring of PRI using drone and satellite is made difficult by the low spectral resolution image captures. In order to estimate PRI from multispectral sensor, we propose a band fusion method using adjacent bands. The method is applied to the drone-based hyperspectral and multispectral imagery and estimated PRI explain 79% of the original PRI. And time series analyses showed that two PRI data (drone-based and SRS sensor) had very similar temporal variations. From these results, PRI from multispectral imagery using band fusion can be used as a new method for evaluation of crop stress.

Keywords

Photochemical Reflectance Index (PRI);crop stress;hyperspectral;multispectral;drone

Acknowledgement

Supported by : 농촌진흥청