• 한국토양비료학회지
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• 제48권5호
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• pp.340-350
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• 2015

This experiment was carried out to find out the mitigation of greenhouse gases (GHGs) emission and changes of soil carbon contents in the cropland. In order to minimize the soil disturbance, this study was conducted without crop cultivation at the pots treated with different biomass. Different biomass was buried in the soil for 12 months. Decomposition rates of expander rice hull, pig manure compost and carbonized rice hull were 18%, 11~11.5% and 0.5~1.2%, respectively. It was appeared that carbonized rice hull was slightly decomposed. No difference was shown between chemical fertilizer treatment plot and non-application plot. It was appeared that soil carbon content in the non chemical fertilizer application plot was high when compared to its chemical fertilizer. Its content at soil depth of 20 cm more decreased than the upper layer of soil. Accumulative emission of $CO_2$ with different treatments of biomass was highest of 829.0~876.6 g $CO_2m^{-2}$ in the application plot of PMC (Pig Manure Compost) regardless of chemical fertilizer treatment during 16 months of experiment. However, the emission for expander rice hull treatment plot was lowest of 672.3~808.1 g $CO_2m^{-2}$. For application plot of the carbonized rice hull, it was shown that non chemical fertilizer plot, 304.1 mg $N_2Om^{-2}$, was higher than the chemical fertilizer treatment, 271.6 mg $N_2Om^{-2}$. Greenhouse gas emissions in the PMC treatment were highest of 0.94 ton $CO_2eqha^{-1}yr^{-1}$. However, it was estimated to be the lowest in the expander rice hull treatment.

• 농업과학연구
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• 제46권1호
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• pp.205-217
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• 2019

The aim of this study was to identify land resources because food production and supply in North Korea have been at risk due to variations in its seasonal climate. More than three-fifths of the soils are locally derived from the weathering of granitic rocks or various kinds of schists developed from crystalline rocks. Well-developed reddish brown soils derived from limestone are found in the North Hwanghae province and in the southern part of the South Pyeongan province. Additionally, a narrow strip of similarly fertile land runs through the eastern seaboard of the Hamgyong and Kangwon Provinces. The loss of clay particles and organic matter are major causes of degradation in the soil physical and chemical properties in North Korea. 75% of the areas converted from forests became croplands, and 69% of the land converted to croplands came from forests. The net forest loss was quite small from the 1990s to the 2000s. However, deforestation in areas with a slightly lower elevation and gentler slope between 1997 and 2014 led to severe soil erosion resulting in a drastic change in the physical and chemical properties of the soil which influenced cropland stability and productivity. Therefore, the drastic changes in land cover as well as in the physical and chemical properties of the soil caused by various geographical features have seriously influenced the productivity of crops in North Korea.

• 한국기후변화학회지
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• 제6권1호
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• pp.33-40
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• 2015

Forests are to be recognized as an important carbon sink under the UNFCCC that consist of above- and below-biomass, dead organic matter (DOM) such as dead wood and litter, and soil organic matter (SOM). In order to asses for DOM and SOM, however, it is relevant to land-use change matrices over last 20 years for each land-use category. In this study, a land-use change matrix was produced and its uncertainty was assessed using a point sampling technique with permanent sample plots in national forest inventory at Chungbuk province. With point sampling estimated areas at 2012 year for each land-use category were significantly similar to the true areas by given six land-use categories. Relative standard error in terms of uncertainty of land-use change among land-use categories ranged in 4.3~44.4%, excluding the other land. Forest and cropland covered relatively large areas showed lower uncertainty compared to the other land-use categories. This result showed that selected permanent samples in the NFI are able to support for producing land-use change matrix at a national or province level. If the $6^{th}$ NFI data are fully collected, the uncertainty of estimated area should be improved.

• 한국기후변화학회지
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• 제9권4호
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• pp.385-398
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• 2018

Although the importance of developing reliable and systematic GHG inventory has increased, the GIS/RS-based national scale LULUCF (Land Use, Land-Use Change and Forestry) sector analysis is insufficient in the context of the Paris Agreement. In this study, the change in $CO_2$ storage of forest land due to land use change is estimated using two GIS/RS methodologies, Sampling and Wall-to-Wall methods, from 2000 to 2010. Particularly, various imagery with sampling data and land cover maps are used for Sampling and Wall-to-Wall methods, respectively. This land use matrix of these methodologies and the national cadastral statistics are classified by six land-use categories (Forest land, Cropland, Grassland, Wetlands, Settlements, and Other land). The difference of area between the result of Sampling methods and the cadastral statistics decreases as the sample plot distance decreases. However, the difference is not significant under a 2 km sample plot. In the 2000s, the Wall-to-Wall method showed similar results to sampling under a 2 km distance except for the Settlement category. With the Wall-to-Wall method, $CO_2$ storage is higher than that of the Sampling method. Accordingly, the Wall-to-Wall method would be more advantageous than the Sampling method in the presence of sufficient spatial data for GHG inventory assessment. These results can contribute to establish an annual report system of national greenhouse gas inventory in the LULUCF sector.

• 한국폐기물자원순환학회지
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• 제35권8호
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• pp.777-784
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• 2018

Since climate change increases the risk of extreme rainfall events, concerns on flood management have also increased. In order to rapidly recover from flood damages and prevent secondary damages, fast collection and treatment of flood debris are necessary. Therefore, a quick and precise estimation of flood debris generation is a crucial procedure in disaster management. Despite the importance of debris estimation, methodologies have not been well established. Given the intrinsic heterogeneity of flood debris from local conditions, a regional-scale model can increase the accuracy of the estimation. The objectives of this study are 1) to identify significant damage variables to predict the flood debris generation, 2) to ascertain the difference in the coefficients, and 3) to evaluate the accuracy of the debris estimation model. The scope of this work is flood events in Ulsan city region during 2008-2016. According to the correlation test and multicollinearity test, the number of damaged buildings, area of damaged cropland, and length of damaged roads were derived as significant parameters. Key parameters seems to be strongly dependent on regional conditions and not only selected parameters but also coefficients in this study were different from those in previous studies. The debris estimation in this study has better accuracy than previous models in nationwide scale. It can be said that the development of a regional-scale flood debris estimation model will enhance the accuracy of the prediction.

• 농촌계획
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• 제27권4호
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• pp.33-41
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• 2021

Ammonia emission from the agricultural sector contributes almost 78% of total ammonia emission in Korea. The current ammonia emission estimation method from fertilizer application has high uncertainty and needs to be improved. In this study, we propose an improvement method for estimating the amount of ammonia emission from agricultural land with improved spatiotemporal resolution using Farm Manager Registration Information System and criteria for the fertilizer. We calculated ammonia emissions by utilizing the 2020 cultivation area provided by Farm Manager Registration Information System for 55 kinds of upland crops cultivated in the field area of the farmland. As a result, soybeans were the most cultivated field crop in 2020, and the area of cultivated land was surveyed at about 77,021 ha, followed by sweet potatoes 22,057 ha, garlic 20004 ha, potatoes 17,512 ha, and corn 16,636 ha. The month with the highest ammonia emissions throughout the year was calculated by emitting 590.01 ton yr-1 in May, followed by 486.55 ton yr-1 in March. Hallim-eup in Jeju showed the highest ammonia emission at 117.50 ton yr-1.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.329-329
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• 2022

Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.

• 대한원격탐사학회지
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• 제39권5_1호
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• pp.507-519
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• 2023

Multi-temporal optical images have been utilized for time-series monitoring of croplands. However, the presence of clouds imposes limitations on image availability, often requiring a cloud removal procedure. This study assesses the applicability of various machine learning algorithms for effective cloud removal in optical imagery. We conducted comparative experiments by focusing on two key variables that significantly influence the predictive performance of machine learning algorithms: (1) land-cover types of training data and (2) temporal variability of land-cover types. Three machine learning algorithms, including Gaussian process regression (GPR), support vector machine (SVM), and random forest (RF), were employed for the experiments using simulated cloudy images in paddy fields of Gunsan. GPR and SVM exhibited superior prediction accuracy when the training data had the same land-cover types as the cloud region, and GPR showed the best stability with respect to sampling fluctuations. In addition, RF was the least affected by the land-cover types and temporal variations of training data. These results indicate that GPR is recommended when the land-cover type and spectral characteristics of the training data are the same as those of the cloud region. On the other hand, RF should be applied when it is difficult to obtain training data with the same land-cover types as the cloud region. Therefore, the land-cover types in cloud areas should be taken into account for extracting informative training data along with selecting the optimal machine learning algorithm.

• 한국토양비료학회지
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• 제45권4호
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• pp.475-483
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• 2012

최근 농경지의 급격한 감소와 더불어 도시화, 경지정리, 도로공사 및 혁신도시 건설 등으로 토지이용의 변화가 심하게 발생되고 있다. 특히, 토지이용 변화심화지역인 경기도 고양시, 충청남도 천안시, 강원도 원주시를 대상으로 토지 이용변화실태, 토양특성변화양상, 토양도수정내용 및 기업도시 등으로 편입되는 지역의 토양환경분석을 하였다. 이에 대한 결과를 요약하면 다음과 같다. 1. 우리나라의 경지면적 (2011년)은 2009년대비 17.3 ha가 감소되었다. 논의 경우 24.2 ha가 감소되었으나, 밭의 경우에는 7.0 ha가 증가하였다. 2. 논의 면적 감소사유로는 논밭전환 (20.7 ha) > 공공시설 (3.2) ${\geq}$ 건물건축 (3.2) > 유휴지 (1.3) > 기타 (0.9) 순이며, 밭 면적의 증가원인은 논밭전환 (20.7 ha) > 개간 (4.5) > 복구 (0.3) 순이었다. 논밭전환의 이유는 논농사에서 농가소득이 높은 밭작물 내지 시설작물로 전환하는 것으로 생각된다. 3. 토지이용변화가 심한 해당시군의 농경지감소 (논, 밭, 과수)는 밭토양조사 (1995~1999) 당시와 비교 (2011년)할 때 고양시는 1,466 ha, 천안시 9,708, 원주시 6,980 ha가 감소되었으며, 1999년 대비 45%~25%의 농경지가 급격히 감소되었다. 4. 환경부 토지이용피복도의 통계자료 활용성을 검토하기 위해 농식품부 통계자료와 비교시 지목별로 큰 차이가 있었다. 따라서, 추후 면밀한 검토를 통하여 활용 방안을 마련해야 할 것이다. 5. 원주시의 토양정보 변경내용을 보면 곡간지의 일부 논토양이 밭 또는 과수원으로 토지이용이 변경되었으며, 배수등급의 경우 도로건설 등으로 인해 저습화되는 등 해당 토양의 일부 특성정보가 변경되었다. 특히, 논토양의 경우 시설재배지, 밭, 과수원, 휴경, 성토화 등으로 토지 이용의 변화가 심하였다. 6. 원주시 혁신도시에 편입되는 논토양은 급지가 떨어지는 3~4급지가 대부분으로 3급지 70.8%, 4급지 29.2%이었다. 밭토양 역시 4급지가 88.7%인 토양으로 우량 급지가 혁신도시 건설에 속하지는 않았다. 앞으로 우량농경지 보전을 위해 제도적 장치의 마련이 필요하다고 생각한다.

• 한국습지학회지
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• 제7권1호
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• pp.107-117
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• 2005

토양침식은 강우분포, 토양, 토지이용과 같은 많은 요인들에 의해 영향을 받는다. 이런 요인들은 시간과 공간에 의해 여러 가지 형태로 나타난다. 본 연구에서는 유역에서의 토양침식 위험지역을 평가하는 것을 목적으로 하고 있으며, 토양침식량 계산은 RUSLE를 이용하였고, RUSLE의 지형 및 공간정보 관련 인자들은 DEM, 토양도, 토지이용도를 이용하여 추출하였고 유역에서 발생하는 토양침식량을 산정하였다. 연구대상유역으로는 한강수계 제1지류인 경안천 유역의 농경지로 하였으며, 토양침식량 분석결과 보통, 특수작물(1210) 재배지역, 과수원(1220), 미경지정리답(1120), 경지정리답(1110)의 순으로 가장 큰 토양침식이 발생하고 있으며, 이 재배지역의 평균 토양침식량 또한 보통, 특수작물 재배지역에서 가장 크게 나타났다. 이 토양침식량 분석결과를 이용하여 농경지의 토양침식 위험지역을 5개 등급으로 구분하여 분석한 결과 토양침식의 위험성이 가장 크다고 판단되는 5등급의 경우 전체 농경지의 2.4%에 해당하는 72.5ha정도가 침식위험지역으로 판단하였다. 이 침식위험지역은 밭작물재배지역이 72.4ha이고 과수원이 0.1ha로 분석되었으며, 기타의 농경지역에서는 5등급의 위험지역은 나타나지 않았다. 또한 토지이용 상황에 관계없이 2등급(1~50ton/ha/yr) 지역이 전체 농경지의 70.2%로 가장 많은 비율로 나타났다.