Disclosed is a method for evaluating accuracy of a vegetation index using an inexpensive optical sensor of a drone. Vegetation provides various ecological spaces to humans and is important in terms of water resources and climate environment. In general, to monitor vegetation, images taken by installing a near-infrared sensor on a drone and are used. However, the near-infrared sensor is expensive, so vegetation monitoring research becomes practically difficult when the near-infrared sensor is not provided. To solve this problem, the method evaluated accuracy of an inexpensive optical sensor-based vegetation index by using the vegetation index observed by a near-infrared sensor as reference data. First, a Kappa coefficient was calculated by overlapping vegetation survey points surveyed in a field with a normalized difference vegetation index (NDVI) and a vegetation area with a threshold value of 0.6 or higher, in which the highest Kappa coefficient is 0.930, was selected as reference data for accuracy evaluation of an inexpensive optical sensor-based vegetation index. As a result of comparing the normal vegetation index (NDVI) with the inexpensive optical sensor-based vegetation index, the Kappa coefficient was analyzed to be the highest at 0.713, 0.713, and 0.828 in threshold ranges of 0.04, 0.08, and 0.30 or more, respectively. In particular, in the case of a red/green/red vegetation index (RGBVI) vegetation index, the Kappa coefficient was high at 0.828, Accordingly, vegetation monitoring research using an optical sensor can be performed even in an environment where a near-infrared sensor cannot be used.

    저가의 드론 광학센서를 활용한 식생지수 정확도 평가 방법이 개시된다. 식생은 인간에게 다양한 생태공간을 제공하고 수자원 및 기후환경 측면에서도 매우 중요하다. 일반적으로 식생을 모니터링하기 위해 드론에 근적외선 센서를 탑재하여 촬영한 영상을 활용하게 된다. 그러나, 근적외선 센서는 상대적으로 고가이며, 따라서 근적외선 센서를 구비하지 못할 경우 식생 모니터링 연구가 현실적으로 어렵게 된다. 본 연구는 이러한 문제를 개선하기 위해 근적외선 센서를 활용하여 관측한 식생지수를 기준 자료로 하여 비교적 저가인 광학센서 기반의 식생지수의 정확도를 평가하였다. 먼저 현장에서 조사한 식생조사 지점과 정규식생지수(NDVI)와의 중첩을 통해 Kappa 계수를 계산하였으며, 그 결과 Kappa 계수가 0.930으로 가장 높게 나타난 0.6 이상의 임계값을 갖는 식생영역을 광학센서 기반의 식생지수 정확도 평가의 기준자료로 선정하였다. 정규식생지수(NDVI)를 기준자료로 하여 비교적 저가인 광학센서 기반의 식생지수와의 비교를 수행한 결과, 0.04, 0.08, 0.30 이상의 임계값 구간에서 Kappa 계수가 각각 0.713, 0.713, 0.828로 가장 높게 분석되었다. 특히 RGBVI 식생지수의 경우 Kappa 계수가 0.828로 높게 나타났으며, 따라서 근적외선 센서를 활용하지 못하는 환경에서도 광학센서를 활용한 식생 모니터링 연구가 가능함을 알 수 있었다.


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    Titel :

    Evaluation method of vegetation index accuracy using low-cost drone optical sensor


    Weitere Titelangaben:

    저가의 드론 광학 센서를 활용한 식생지수 정확도 평가 방법


    Beteiligte:
    LEE GEUN SANG (Autor:in) / YOUNG JOO KIM (Autor:in)

    Erscheinungsdatum :

    2022-04-22


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Koreanisch


    Klassifikation :

    IPC:    G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / B64C AEROPLANES , Flugzeuge / B64D Ausrüstung für Flugzeuge , EQUIPMENT FOR FITTING IN OR TO AIRCRAFT / G01C Messen von Entfernungen, Höhen, Neigungen oder Richtungen , MEASURING DISTANCES, LEVELS OR BEARINGS / G03B APPARATUS OR ARRANGEMENTS FOR TAKING PHOTOGRAPHS OR FOR PROJECTING OR VIEWING THEM , Geräte oder Anordnungen zum Aufnehmen, Projizieren oder Betrachten von Fotografien / H04N PICTORIAL COMMUNICATION, e.g. TELEVISION , Bildübertragung, z.B. Fernsehen



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