본 연구는 무인기를 이용한 동계사료의 수량조사시 필요한 검량식의 작성을 위한 식생조사 및 분광측정의 적정 시기와, 작성된 검량식의 적용이 적절한 시기를 판단하기 위하여 고정식 자동 분광 측정장치를 개발하여 호밀, 총체보리, IRG를 대상으로 NDVI 를 장기간 측정하였다. 그리고 NDVI가 최댓값이 되는 날을 기준 으로 증가기간과 감소시간으로 기간을 나누어 건물수량 예측을 위한 검량식을 작성하고 검량식의 예측정확도를 각각 비교하였다. 조사결과 호밀, 총체보리, IRG는 각각 4월 8일, 4월 9일, 4월 5일에 NDVI가 최대치가 되었으며 NDVI 증가기간의 검량식은 결정계수(R2)는 각각 0.84, 0.84, 0.78로 높은 상관관계를 보였고 NDVI 감소기간에는 각각 0.00, 0.02, 0.27로 매우 낮게 나타났다. 따라서 NDVI 측정을 통한 건물수량 예측을 효율적으로 하기 위해서는 NDVI 변화를 정확히 측정할 필요가 있으며 고정식 자동 분광 측정 방법은 생육에 따른 NDVI의 정밀 측정에 효과적인 것으로 판단된다.

Recently, satellite image data has been widely used in various fields. Extraction of forest information is the field which has great application possibility. Forest type information can be used in forecasting and simulating soil erosion, landslides and debris flow as an important influence factor. Application of satellite imagery has advantages to obtain latest forest type information. NDVI calculated from near infra red band of satellite imagery represents vegetation activity, with seasonal difference of it forest type can be classified. In this study, we analyzed MODIS imagery from 2011 years to 2013 years in Gangwon-do where forest area is large and classified forest type with coniferous and deciduous forests. As a result, there was high correlation between forest type of digital map and it classified from NDVI. The possibility for extraction of forest type information from satellite imagery was confirmed.

현위성영상을 이용하여 도시 지역을 추출하는 방법으로 가장 널리 사용되는 방법은 영상 분류이다. 영상 분류는 도시 지역을 추출하는 자동화된 방법으로 단시간에 도시 지역을 추출할 수 있지만 그 정확도는 상황에 따라 큰 차이를 보일 뿐만 아니라 시계열적인 변화를 추출하기에는 상당히 번거로운 작업 절차가 요구된다. 따라서 본 연구에서는 식생지수 결합에 의한 도시 지역 추출 방법을 제안하고자 한다. 본 연구에서는 정규식생지수와 정규시화지화지수를 결합한 방법을 이용하여 도시 지역을 추출하였다. 1988년과 2000년 서울지역 위성영상에 영상 분류 방법과 지수결합방법을 사용한 결과, 식생지수결합법에 의해 도시로 추출된 지역이 감독분류기법에 의해서도 도시 지역으로 추출된 확률이 각각 98.1%(1988년), 99.3%(2000년)인 것으로 나타나, 식생지수 결합법을 사용해 도시 지역을 추출할 수 있는 가능성을 알 수 있었다. 또한 두 방법을 사용한 각 시기의 도시 지역영상과 환경부 토지피복대분류(1999년) 결과를 비교분석한 결과, 1988년의 분류 결과 도시 과대추정 가능성을 확인하였다. 이러한 결과를 토대로 분류를 통한 도시 지역 추출 방법에 비해 식생지수결합법을 이용한 도시 지역 추출이 절차상 수월한 점으로 미루어볼 때, 도시 지역 추출에 있어서 식생지수결합법의 효율성을 입증할 수 있었다.

Background : It is necessary to develop a diagnostic tool for the precision agriculture according to the change of agriculture environment. In particular, medicinal crops are often cultivated in poor areas such as mountains and valleys, and are susceptible to abnormal climates. Therefore, there is a need for a method that can diagnose the growth easily and with time. We conducted a study to investigate the possibility of remote sensing for 10 species of medicinal crops using unmanned aerial vehicles and multispectral images. Methods and Results : This study was conducted in 0 - 4 times continuously cultivated field with 10 species of medicinal crops (Angelica gigas, A. koreana, A. tenuissiman, A. dahurica, A. acutiloba, A. polymorpha, Ledebouriella seseloides, Lithospermum erythrorhizon, Rhemannia glutinosa). Growth characteristics such as plant height, number of leaves, leaf length, leaf width, stem diamanter and number of stems were investigated between July 10 and July 16. The reflectance map of red (660 ㎚) and NIR (790 ㎚) was obtained using a UAV equipped with a multi-spectral sensor and NDVI [Normalized Difference Vegetation Index] was obtained with a Pix4D mapper. As the number of times of continuos cultivation increased, the growth and NDVI tend to decreased. 6 species of Angelica genus were positively correlated with growth characteristics such as plant height, leaf length, leaf width, and stem diameter and NDVI. Otherwise, there was no significant relationship between growth characteristics and NDVI in Ledebouriella seseloides, Lithospermum erythrorhizon, and Rhemannia glutinosa. This is because the difference in the growth according to time of continuos cultivation was not significant and the canopy structure tended to overlap with the upper and lower leaves. Conclusion : NDVI is widely used as a useful tool for evaluating the canopy productivity and is highly correlated with the above-ground growth characteristics of 6 species of Angelica spp. It is necessary to develop the growth index suitable for the each species and to enhance the validity of growth index by examining the correlation under various cultivation conditions.

Normalized Difference Vegetation Index (NDVI) has played an important role in assessing green plant biomass through remote sensing on global scale since the early 1970s. The concept of NDVI is based on the fact that green plants show higher reflection in near-infrared region than in visible region of the electromagnetic spectrum. However, it is well known that the relocation of chloroplasts in plant leaf cells may dramatically change the optical properties of plant leaves. In this study I traced the changes in the reflectance and transmittance properties of Tobacco leaves at the wavelengths of 660 and 800 nm after a sudden increase in light intensity. The results showed that NDVI of leaves gradually decreased from 72.7% to 69.9% when exposed to a sudden increase in light intensity from 30 to 1,200 μmol/m2 · s. This means that the error resulting from the physiological status of the plant should be accounted for a more precise understanding of ground truth corresponding to the data from the remotely acquired images.

In this study, the yearly mean normalized difference vegetation index(YMNDVI) in Chungcheongnam-do was calculated using S10 NDVI data of the vegetation sensor for SPOT 4 and 5. Based on this calculation, statistical values such as mean value, standard deviation and coefficient of variation were determined. In addition, a comparative analysis was performed by calculating YMNDVI for cities and counties of Chungcheongnam-do. The YMNDVI of Chungcheongnam-do revealed a slight increase during 14 years between 1999 to 2012. However, it showed only a slight change within the range of 0.476 to 0.553, and no significant increase or decrease was noted. As a result, the highest YMNDVI was 0.553 at 2009, the lowest YMNDVI was 0.476 at 2001 and 2006. The mean value of YMNDVI in Chungcheongnam-do for 14 years turned out to be 0.502. As a result of the regional YMNDVI analysis, the highest YMNDVI region was Geumsan-gun, followed by Geryong-si, Cheongyang-gun and Gongjusi. The lowest YMNDVI region was Taean-gun, followed by Dangjin-si, Seosan-si and Seocheon-gun. An analysis of coefficient of variation in the research area showed that the mean value of Chungcheongnamdo was 4.2%, while the overall value was also not that high.

A split-plot designed experiment including four rice varieties and 10 nitrogen levels was conducted in 2003 at the Experimental Farm of Seoul National University, Suwon, Korea. Before heading, hyperspectral canopy reflectance (300-1100nm with 1.55nm step) and nine crop variables such as shoot fresh weight (SFW), leaf area index, leaf dry weight, shoot dry weight, leaf N concentration, shoot N concentration, leaf N density, shoot N density and N nutrition index were measured at 54 and 72 days after transplanting. Grain yield, total number of spikelets, number of filled spikelets and 1000-grain weight were measured at harvest. 14,635 narrow-band NDVIs as combinations of reflectances at wavelength ~lambdal~;and~;~lambda2 were correlated to the nine crop variables. One NDVI with the highest correlation coefficient with a given crop variable was selected as the NDVI of the best fit for this crop variable. As expected, models to predict crop variables before heading using the NDVI of the best fit had higher r2 (>10~%) than those using common broad- band NDVI red or NDVI green. The models with the narrow-band NDVI of the best fit overcame broad- band NDVI saturation at high LAI values as frequently reported. Models using NDVIs of the best fit at booting showed higher predictive capacity for yield and yield component than models using crop variables.

가뭄은 주요 자연 재해 중의 하나이다. 가뭄 파악을 위하여 주로 강우량과 같은 기상자료를 주요 입력 자료로 활용하여 분석하고 있으나 이러한 기상 자료는 한정된 기상 관측소로부터 얻어진 점자료에 해당된다. 따라서, 기상자료를 이용한 분석에서는 시간적 혹은 공간적으로 원하는 자료의 제공이 원활하게 이루어지지 않을 수 있다. 원격탐사 자료는 가뭄분석을 위하여 기상자료에서 포착할 수 없는 이러한 문제점을 보완하기 위한 자료로 활용될 수 있다. 따라서, 본 연구