• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.5
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• pp.39-48
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• 2006

The objective of this research was to find an indirect method to estimate land surface temperature (LST) efficiently, using Landsat images. Agricultural fields including paddy fields have long been known to have multi-functions beneficial to the environment and ecology of the urban surrounding areas. Among these functions, the ambient temperature cooling (ATC) effect is widely acknowledged. However, quantitative and regional assessment of such effect has not been performed. Thermal remote sensing has been used over urban areas to assess the ATC effect, Thermal Island Effect(TIE), and as input for models of urban surface atmosphere exchange. Here, we review the use of thermal remote sensing in the study of paddy fields and urban climates, focusing primarily on the ATC effect. Landsat satellite images were used to determine the surface temperatures of different land cover types of a $44km^{2}$ study area in Cheongiu, Korea. The results show that the ATC is a function of paddy area percentage in Landsat pixels. Landsat pixels with higher paddy area percentage have much more cooling effect. The use of satellite data may contribute to a globally consistent method for analysis of ATC effect.

• Weed & Turfgrass Science
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• v.5 no.2
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• pp.88-94
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• 2016

Vehicular traffic on turf results in loss of green cover due to direct tearing of shoots and indirect long-term soil compaction. Protection of turfgrass crowns from wear could increase the ability of turf to recover from heavy traffic. Plastic turfpavers have been installed in trafficked areas to reduce soil compaction and to protect turfgrass crowns from wear. The objectives of this study were to evaluate traffic performance of turfgrasses (Zoysia matrella and Axonopus compressus) and soil mixture (high, medium and low sand mix) combinations on turf-paver complex. The traffic performance of turf and recovery was evaluated based on percent green cover determined by digital image analysis and spectral reflectance responses by NDVI-meter. Bulk density cores indicated significant increase in soil compaction from medium and low sand mixtures compared to high sand mixture. Higher reduction of percent green cover was observed from A. compressus (30-40%) than Z. matrella (10-20%) across soil mixtures. Both turf species displayed higher wear tolerance when established on higher sand (>50% sand) than low sand mixture. Positive turf recovery was also supported by complementary spectral responses. Establishment of Zoysia matrella turf on turfpaver complex using high sand mixture will result in improved wear tolerance.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.2
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• pp.7-14
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• 2009

The purpose of this study is to identify how much the MODIS NDVI (Normalized Difference Vegetation Index) can explain the forest soil moisture simulated from SWAT (Soil and Water Assessment Tool) model. For ChungjuDam watershed ($6,661.3\;km^2$) which covers 82.2% of forest, the SWAT model was calibrated for four years (2003-2006) at two locations of the watershed using daily streamflow data and was verified for three years (2000-2002) with average Nash and Sutcliffe model efficiencies of 0.69 and 0.75 respectively. For the period from March to June, the average spatial correlation between 16 days composite MODIS NDVI and the corresponding SWAT forest soil moisture was 0.90. The two variables averaged for each data set during that period showed an inverse relation with the average coefficient of determination of 0.55.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.11-20
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• 2017

This study is to estimate the spatial soil moisture using multiple linear regression model (MLRM) and 15 minutes interval Land Surface Temperature (LST) data of Communication, Ocean and Meteorological Satellite (COMS). For the modeling, the input data of COMS LST, Terra MODIS Normalized Difference Vegetation Index (NDVI), daily rainfall and sunshine hour were considered and prepared. Using the observed soil moisture data at 9 stations of Automated Agriculture Observing System (AAOS) from January 2013 to May 2015, the MLRMs were developed by twelve scenarios of input components combination. The model results showed that the correlation between observed and modelled soil moisture increased when using antecedent rainfalls before the soil moisture simulation day. In addition, the correlation increased more when the model coefficients were evaluated by seasonal base. This was from the reverse correlation between MODIS NDVI and soil moisture in spring and autumn season.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1615-1619
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• 2010

토양수분은 토양입자에 포함되어 있는 물을 의미하는 것으로 지표면과 대기간의 에너지 균형과 물 순환을 조절하는데 중요한 요소이다. 본 연구에서는 토양수분 산정을 위하여 2003년 1월부터 2008년 12월까지의 MODIS(Moderate Resolution Imaging Spectroradiometer) 위성관측 자료로부터 획득한 정규식생지수(NDVI: Normalized Difference Vegetation Index)자료와 지표면 온도자료, 우리나라 76개소 기상관측소 중에 자료의 보유기간이 30년 이하인 관측소와 섬 지역들을 제외한 57개 지점의 강수량, 토양온도 자료 및 우리나라 전역에 대한 토지피복, 유효토심자료를 이용하여 데이터 마이닝(Data Mining) 기법의 하나인 CART(Classification And Regression Tree) 기법을 이용하여 토양수분을 산정하였다. 먼저 신뢰성 높은 토양수분 관측 자료를 가진 용담댐 유역의 6개 지점에 대하여 토양수분을 산정하여 적용 가능성을 분석하였다. 3개 지점의 토양수분 관측치는 토양수분 산정 모형 수립에 사용하였으며 검증에 사용된 1개 지점의 토양수분의 관측치와 추정치 간의 상관계수를 확인한 결과 전체적인 토양수분의 거동을 잘 나타내고 있어 토양수분 추정 모형의 적용가능성을 확인하였다. 이를 이용하여 용담댐 유역의 토양수분 분포와 우리나라 전역에 대한 토양수분 분포도를 추정하였다. 신뢰할 수 있는 지상관측 토양수분 관측치가 다양한 지상조건에 대하여 존재하지 않는 한계가 있음에도 불구하고 제시된 토양수분산정 방법은 제한된 가용자료를 사용한 우리나라 전역의 토양수분 산정에 있어 합리적인 접근법이라 판단된다.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.116-120
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• 2009

원격탐사 기술은 사람이 직접 방문하여 조사하기 힘든 극지라든가 농업환경에 대한 자료 요구도가 높으면서도 직접 수집이 어려운 비접근 지역에 대한 정보를 추출하는데 유용한 관측수단이다. 본 연구는 MODIS(Moderate Resolution Imaging Spectroradiometer) 제공 산출물 중 16일 단위로 작성되는 NDVI(Normalized Difference Vegetation Index, MOD13)를 이용하여 북한의 벼 수량을 추정하는 것을 목적으로 하였고, 그 가능성과 한계에 대하여 알아보았다. 2000년부터 2008년까지 촬영된 MODIS MOD13 자료를 미국 NASA로부터 제공받아 좌표체계를 우리나라에 맞게 투영하고 NDVI를 추출하여 자료분석에 사용하였다. 통계청에서 발표한 벼 수량 및 생산량 통계자료를 이용하였다. 농촌진흥청 국립농업과학원에서 작성한 북한의 토지피복분류도를 이용하여 서해안 평야지대에 위치한 논을 위도별로 네군데 정하여 관심지역(area of interest)으로 설정하였다. 이 관심지역에 대한 시계열 값을 추출하여 연중 연간 변화를 분석하고 2000년부터 2007년까지 수잉기의 NDVI 값을 이용하여 수량에 대한 상관계수(r)는 $0.77^*$로 5%에서 유의하여 NDVI 값에 따라 벼 수량에 큰 영향을 주는 것으로 나타났다. 수잉기의 NDVI 값과 벼 수량에 대해 회귀분석한 결과($R^2=0.591^*$), NDVI에 따른 벼 수량의 변이를 59.1% 설명할 수 있었다. 이와 같이 회귀식을 이용하여 2008년 북한의 벼 수량은 약 2.80 ton/ha로 추정되었다.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.39-50
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• 2017

Growth monitoring of highland Kimchi cabbage is very important to respond the fluctuations in supply and demand from middle of August to early September in Korea. For evaluating Kimchi cabbage growth, it needs to classify the transplanting period of Kimchi cabbage, preferentially. This study was conducted to estimate the transplanting period of highland Kimchi cabbage from 2015 to 2016 in the main production area of highland Kimchi cabbage, Anbandegi, Maebongsan, and Gwinemi. Correlation between NDVI (Normalized Difference Vegetation Index) from UAV images and days after transplanting of Kimchi cabbage was high in early transplanting period. But because the growth curve of Kimchi cabbage showed S-type, joint use of multi-temporal linear regression equation for estimation of transplanting period was more suitable. Using application of these equations at Anbandegi, Maebongsan, and Gwinemi, we made the map of transplanting periods of highland Kimchi cabbage. Generally, highland Kimchi cabbage is harvested in sixty days later since transplanting. As a result, we could estimate the harvest time and area of highland Kimchi cabbage.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.351-353
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• 2003

We present a retrieval scheme for the remote sensing of evapotranspiration (ET) over rice paddy. To perform the retrieval, high-resolution airborne imagery of multi-spectral visible and thermal infrared data, and ground-based meteorological measurements are utilized. Our ET retrieval scheme is based on the basic principal of surface energy budget, which is a result of balance in longwave and shortwave radiation, latent heat, sensible heat, and energy flux into the ground. To partition the latent and sensible heat fluxes of interest from the energy balance equation, three basic parameters are of most concern, including albedo, surface temperature, and normalized difference vegetation index (NDVI). The NDVI and albedo can be easily derived from the visible and near infrared spectral data, while the surface tem-perature can be determined through the analysis of the infrared data with the Stefan Boltzmann law. From the airborne imagery taken on 28 April 2003, we observe very good dry and wet pixels that can be easily corre-sponded to the radiation and evaporation controlled crite-ria, respectively, and, hence, for the further use in defin-ing the evaporative fraction needed to partition sensible and latent heat fluxes from the net energy flux. The de-rived ET is compared with the in situ measurements.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.99-102
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• 2012

지표면 온도는 토지피복의 상태, 식생의 분포 상태, 토양수분, 증발산 등의 영향으로 많은 차이를 가지게 되며, 지면-대기의 상호순환의 중요한 인자로써 기후모델 및 농업 등의 기본적인 데이터로 사용되고 있다. 이러한 지표면의 온도를 정확하게 파악하는 것은 수문학적 관점 및 기상적인 관점에서 매우 중요하다. 기존에 LST (Land Surface Temperature, 지표면온도), ET (EvapoTranspiration, 증발산), NDVI (Normalized Difference Vegetation Index, 정규식생지수) 등의 검증이 많이 이루어진 MODIS위성의 Terra/Aqua센서는 한반도를 스캔하고 지나갈 때의 순간적인 데이터를 산출된다. 공간적인 면에서는 많은 이점이 있으나 시간적인 면에서는 시간에 따른 인자들의 변동성을 파악 하는데는 많은 문제가 있다. 그렇기 때문에 시 공간적으로 변화양상을 측정 할 수 있는 정지궤도위성의 중요성이 대두되고 있다. 본 연구에서는 국내에서 2010년 6월 27일 발사된 정지궤도위성인 천리안의 데이터를 활용하였다. 천리안 위성은 기상 센서와 해양관측 센서 그리고 통신센서를 가진 위성이다. 천리안 위성의 기상 센서는 MTSAT-1 위성과 같은 적외선 센서를 탑재하고 있으며, 평시에는 15분 단위의 데이터를 산출하게 된다. 천리안에서 제공되는 많은 Product(강우강도, 해수면온도, 가강수량, 지구방출복사 등)는 수자원 및 기상에 관련된 데이터가 제공된다. 하지만 아직 검증이 많이 이루어지지 못하였다. 그래서 천리안 위성 데이터인 지표면 온도자료를 이용하여 천리안 위성의 효율성에 대해서 알아보고자 하며, 기존의 검증이 많이 이루어진 MODIS의 데이터와의 상관성을 분석하고 지상과의 관계를 검증 및 비교하여 천리안 위성의 활용성에 대해서 알아보려고 한다.