• KCID journal
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• v.21 no.1
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• pp.78-88
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• 2014

This study is to analyze the 2012 spring drought of Korea using drought index and satellite image. The severe spring drought recorded in May of 2012 showed 36.4% of normal rainfall(99.5mm). The areas of west part of Gyeonggi-do and Chungcheong-do were particularly serious. The drought indices both the SPI(Standardized Precipitation Index) and WADI(WAter supply Drought Index) represented the drought areas from the end of May and to the severe drought at the end of June. The drought by SPI completely ended at the middle of July, but the drought by WADI continued severe drought in the agricultural reservoir watersheds of whole country even to the end of the July. On the other hand, the results by spatial NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index) data from Terra MODIS, both indices showed relatively low values around the areas of Sinuiju, Pyongyang, and west coast of North Korea and Gyeonggi-do and Chungcheong-do of South Korea indicating drought condition. Especially, the values of NDVI and EVI at Chungcheong-do were critically low in June compared to the normal year value.

• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.507-514
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• 2009

In this study, a dynamic modeling scheme is presented to describe the probabilistic structure of soil water and plant water stress index under stochastic precipitation conditions. The proposed model has the form of the Fokker-Planck equation, and its applicability as a model for the probabilistic evolution of the soil water and plant water stress index is investigated under a climate change scenario. The simulation results of soil water confirm that the proposed soil water model can properly reproduce the observations and show that the soil water behaves with consistent cycle based on the precipitation pattern. The simulation results of plant water stress index show two different PDF patterns according to the precipitation. The simple impact assessment of climate change to soil water and plant water stress is discussed with Korean Meteorological Administration regional climate model.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.1-14
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• 2019

North Korea has frequently suffered from extreme agricultural crop droughts, which have led to food shortages, according to the Food and Agriculture Organization (FAO). The increasing frequency of extreme droughts, due to global warming and climate change, has increased the importance of enhancing the national capacity for drought management. Historically, a meteorological drought index based on data collected from weather stations has been widely used. But it has limitations in terms of the distribution of weather stations and the spatial pattern of drought impacts. Satellite-based data can be obtained with the same accuracy and at regular intervals, and is useful for long-term change analysis and environmental monitoring and wide area access in time and space. The Evaporative Stress Index (ESI), a satellite-based drought index using the ratio of potential and actual evaporation, is being used to detect drought response as a index of the droughts occurring rapidly over short periods of time. It is more accurate and provides faster analysis of drought conditions compared to the Standardized Precipitation Index (SPI), and the Palmer Drought Severity Index (PDSI). In this study, we analyze drought events during 2015-2017 in North Korea using the ESI satellite-based drought index to determine drought response by comparing with it with the SPI and SPEI drought indices.

• Journal of Environmental Science International
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• v.17 no.10
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• pp.1169-1182
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• 2008

The chemical and meteorological effects on the concentration variations of air pollutants ($O_3$ and its precursors) were evaluated based on ground observation data in coastal and inland regions, Busan during springs and summers of 2005-2006. For the purpose of this study, study areas were classified into 5 categories: coastal area (CA), industrial area (IA), downtown area (DA), residential area (RA), and suburban area (SA). Two sites of Dongsam (DS) and Yeonsan (YS) were selected for the comparison purpose between the coastal and inland regions. $O_3$ concentrations in CA and SA were observed to be highest during spring (e.g., 40 ppb), whereas those in DA and RA were relatively low during summer (e.g., $22\sim24$ ppb). It was found that $O_3$ concentrations in IA were not significantly high although high VOCs (especially toluene of about 40 ppb) and $NO_x$ ($\geq$ 35 ppb) were observed. On the other hand, the concentration levels of $O_3$ and $PM_{10}$ at the DS site were significantly higher than those at the YS site, but $NO_x$ was slightly lower than that at the YS site. This might be caused by the photochemical activity and meteorological conditions (e.g., sea-land breeze and atmospheric stagnance). When maximum $O_3$ (an index of photochemical activity) exceeds 100 ppb, the contribution of secondary $PM_{10}\;((PM_{10})_{SEC})$ to total observed $PM_{10}$ concentrations was estimated up to 32% and 17% at the DS and YS sites, respectively. In addition, the diurnal variations of $(PM_{10})_{SEC}$ at the DS site were similar to those of $O_3$ regardless of season, which suggests that they are mostly secondary $PM_{10}$ produced from photochemical reactions.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.607-615
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• 2017

The aerosol optical thickness data retrieved by Moderate Resolution Imaging Spectrometer (MODIS) of Terra & Aqua and Meteorological Imager (MI) of Communication Ocean and Meteorological Satellite (COMS) are analyzed and compared with the measurement data of Aerosol Robotic Network (AERONET) in Northeast Asia. As the result, the aerosol optical thickness retrieved by MODIS and MI were well agreed at ocean region but quite different at cloud edge and barren surface. The reason was that MODIS aerosol optical thickness was retrieved using the visible and infrared channels but MI was retrieved with the visible channel only. Consequentially, the thin cloud be misinterpreted as aerosol by MI and the difference between MODIS and MI aerosol optical thicknesses could be occurred with Normal Distribution Vegetation Index (NDVI) and land surface property. Therefore, the accuracies of clear/cloud region and surface reflectivity are required in order to improve the aerosol optical thickness algorithm by MI.

• Atmosphere
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• v.22 no.1
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• pp.13-28
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• 2012

The $PM_{10}$ concentration data is useful for indentifying intensity and a transport way of Asian dust. However, it is difficult to identify them properly due to the limited spatial resolution and coverage. Therefore, a methodology to estimate $PM_{10}$ concentration using visibility data obtained from synoptic observation was developed. To derive the converting function, correlation between visibility and $PM_{10}$ concentration is investigated using visibility and $PM_{10}$ concentration data observed at 20 stations in Korea from 2005 to 2009. To minimize bias due to atmospheric moisture, data with higher relative humidity over a critical value were eliminated while deriving $PM_{10}$-visibility relationship. As a result, an exponentially decreasing function of visibility is obtained under the condition that relative humidity is less than 82%. Verification of the visibility converting function to $PM_{10}$ concentration was carried out for the dust cases in 2010. It was found that spatial distributions of $PM_{10}$ calculated by visibility are in good agreement with the observed $PM_{10}$ distribution, especially for the strong dust cases in 2010. And correlation between the derived and observed $PM_{10}$ concentration was 0.63. We applied the function to obtain distributions of $PM_{10}$ concentration over North Korea, in which concentration data are not available, and compared them with satellite derived dust index, IODI distributions for dust cases in 2010. It is shown that the visibility function estimates quite similar patterns of dust concentration with IODI image, which suggests that it can contribute for prediction by indentifying transport route of Asian dust.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.4
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• pp.306-317
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• 2017

Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And $NDVI_{UAV}$ in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to $NDVI_{UAV}$ and other meteorological factors were well reflected in the model.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.420-428
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• 2016

For more than 50 years, satellite images have been used to monitor crop growth. Currently, unmanned aerial vehicle (UAV) imagery is being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of growth estimating equation for highland Kimchi cabbage using UAV derived normalized difference vegetation index (NDVI) and agro-meteorological factors. Anbandeok area in Gangneung, Gangwon-do, Korea is one of main districts producing highland Kimchi cabbage. UAV imagery was taken in the Anbandeok ten times from early June to early September. Meanwhile, three plant growth parameters, plant height (P.H.), leaf length (L.L.) and outer leaf number (L.N.), were measured for about 40 plants (ten plants per plot) for each ground survey. Six agro-meteorological factors include average temperature; maximum temperature; minimum temperature; accumulated temperature; rainfall and irradiation during growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 93% of the P.H. and L.L. with a root mean square error (RMSE) of 2.22, 1.90 cm. And $NDVI_{UAV}$ and accumulated temperature in the model explain 86% of the L.N. with a RMSE of 4.29. These lead to the result that the characteristics of variations in highland Kimchi cabbage growth according to $NDVI_{UAV}$ and other agro-meteorological factors were well reflected in the model.

• Atmosphere
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• v.18 no.4
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• pp.287-297
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• 2008

The vertical profiles and optical properties of Asian dust are investigated using ground-based measurements from 1998 to 2002. Vertical profiles of aerosol extinction coefficient are evaluated using MPL (Micro Pulse Lidar) data. Optical parameters such as aerosol optical thickness ($\tau$), ${\AA}ngstr\ddot{o}m$ exponent ($\alpha$), single scattering albedo ($\omega$), refractive index, and volume size distribution are analyzed with sun/sky radiometer data for the same period. We can separate aerosol vertical profiles into three categories. First category named as 'Asian dust case', which aerosol extinction coefficient is larger than $0.15km^{-1}$ and dust layer exists from surface up to 3-4km. Second category named as 'Elevated aerosol case', which aerosol layer exists between 2 and 6km with 1-2.5km thickness, and extinction coefficient is smaller than $0.15km^{-1}$. Third category named as 'Clear sky case', which aerosol extinction coefficient appears smaller than $0.15km^{-1}$. and shows that diurnal variation of background aerosol in urban area. While optical parameters for first category indicate that $\tau$ and $\alpha$ are $0.63{\pm}0.14$, $0.48{\pm}0.19$, respectively. Also, aerosol volume concentration is increased for range of 1 and $4{\mu}m$, in coarse mode. Optical parameters for second category can be separated into two different types. Optical properties of first type are very close to Asian dust cases. Also, dust reports of source region and backward trajectory analyses assure that these type is much related with Asian dust event. However, optical properties of the other type are similar to those of urban aerosol. For clear sky case, $\tau$ is relatively smaller and $\alpha$ is larger compare with other cases. Each case shows distinct characteristics in aerosol optical parameters.

• Journal of the Korean GEO-environmental Society
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• v.25 no.11
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• pp.33-43
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• 2024

In this study, data from the Gwangyang Automated Synoptic Observing System (ASOS) meteorological observatory were utilized for drought assessment. Drought occurrence days were evaluated using the Precipitation-based Standardized Precipitation Index (SPI) and two types of Standardized Precipitation Evapotranspiration Index (SPEI) (SPEI_Thornthwaite and SPEI_Penman-Monteith), considering precipitation and evapotranspiration. The SPI and SPEIs yielded generally similar quantitative results for drought occurrence days. However, the SPEI_Penman-Monteith, which uses the physically-based Penman-Monteith method for evapotranspiration estimation, showed a higher number of drought days compared to the SPI_Thornthwaite. The amount of evapotranspiration by the Penman-Monteith method had high seasonal variability and high moisture loss, while the amount of evapotranspiration by the Thornthwaite method had low variability and low moisture loss. Consequently, the SPEI_Thornthwaite had a higher correlation with the SPI compared to the SPEI_Penman-Monteith. Since the SPEI_Penman-Monteith index can more accurately calculate the amount of water loss caused by the hydrological circulation, more reasonable results are derived in calculating the number of drought occurrence days. However, due to the lack of sufficient high-quality meteorological data at ASOS observatories, the Penman-Monteith method may be difficult to apply. In such cases, the SPEI_Thornthwaite, estimating evapotranspiration based solely on monthly average temperature, can be used as an alternative.