• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.199-205
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• 2001

This study was conducted to figure out temperature profiles of a partially developed paddy rice canopy, which are necessary to run plant disease forecasting models. Air temperature over and within the developing rice canopy was monitored from one month after transplanting (June 29) to just before heading (August 24) in 1999 and 2001. During the study period, the temporal march of the within-canopy profile was analyzed and an empirical formula was developed for simulating the profile. A partially developed rice canopy temperature seemed to be controlled mainly by the ambient temperature above the canopy and the water temperature beneath the canopy, and to some extent by the solar altitude, resulting in alternating isothermal and inversion structures. On sunny days, air temperature at the height of maximum leafages was increased at the same rate as the ambient temperature above the canopy after sunrise. Below the height, the temperature increase was delayed until the solar noon. Air temperature near the water surface varied much less than those of the outer- and the upper-canopy, which kept increasing by the time of daily maximum temperature observed at the nearby synoptic station. After sunset, cooling rate is much less at the lower canopy, resulting in an isothermal profile at around the midnight. A fairly consistent drop in temperature at rice paddies compared with the nearby synoptic weather stations across geographic areas and time of day was found. According to this result, a cooling by 0.6 to 1.2$^{\circ}C$ is expected over paddy rice fields compared with the officially reported temperature during the summer months. An empirical equation for simulating the temperature profile was formulated from the field observations. Given the temperature estimates at 150 cm above the canopy and the maximum deviation at the lowest layer, air temperature at any height within the canopy can be predicted by this equation. As an application, temperature surfaces at several heights within rice fields were produced over the southwestern plains in Korea at a 1 km by 1km grid spacing, where rice paddies were identified by a satellite image analysis. The outer canopy temperature was prepared by a lapse rate corrected spatial interpolation of the synoptic temperature observations combined with the hourly cooling rate over the rice paddies.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.56-68
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• 2009

Ongoing and extensive urbanisation, which is frequently accompanied with careless construction works, may threaten important archaeological structures that are still buried in the urban areas. Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) methods are most promising alternatives for resolving buried archaeological structures in urban territories. In this work, three case studies are presented, each of which involves an integrated geophysical survey employing the surface three-dimensional (3D) ERT and GPR techniques, in order to archaeologically characterise the investigated areas. The test field sites are located at the historical centres of two of the most populated cities of the island of Crete, in Greece. The ERT and GPR data were collected along a dense network of parallel profiles. The subsurface resistivity structure was reconstructed by processing the apparent resistivity data with a 3D inversion algorithm. The GPR sections were processed with a systematic way, applying specific filters to the data in order to enhance their information content. Finally, horizontal depth slices representing the 3D variation of the physical properties were created. The GPR and ERT images significantly contributed in reconstructing the complex subsurface properties in these urban areas. Strong GPR reflections and highresistivity anomalies were correlated with possible archaeological structures. Subsequent excavations in specific places at both sites verified the geophysical results. The specific case studies demonstrated the applicability of ERT and GPR techniques during the design and construction stages of urban infrastructure works, indicating areas of archaeological significance and guiding archaeological excavations before construction work.

• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.176-187
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• 2015

In this study, we hypothesized that the size of wintering crane population would change due to the climate factors. We assumed that wintering population size would differ by climate values in January, which is the coldest period in year. Especially, White-naped cranes were able to choose wintering site between Cheorwon and other alternative place where snow coverage had low influence, differing from Red crowned cranes. For this reason, we predicted the population size of White-naped cranes would fluctuate according to the extent of snow coverage in Cheorwon. Therefore we used snow coverage data based on MODIS and climate data from KMA (Korea Meteorological Administration) that are generally used. We analyzed the crane's population size in Cheorwon in January from 2002 to 2014. The temperature in the Cheorwon increased from 2002 to wintering period in 2007~ 2008 and went down, showing the lowest temperature in 2011~ 2012. With this phenomenon, warmth index showed the similar pattern with temperature. Amount of newly accumulated snow (the amount of snow that fallen from 0:01 am to 11:29 pm in a day) was low after 2002, but rapidly increased in 2010~ 2011 and 2011~ 2012. The area of snow coverage rapidly declined from 2002 to 2005~ 2006 but suddenly expanded in wintering period in 2009~ 2010 and 2010~ 2011. Wintering population size of the White-naped cranes decreased as snow coverage area increased in January and the highest correlation was found between them, compared to the other climatic factors. However, the number of individuals of Red crowned cranes had little relationship with general climate factors including snow cover range. Therefore it seems that population size of the Red crowned crane varied by factors related with habitat selection such as secure roosting site and area of foraging place, not by climatic factors. In multiple regression analysis, wintering population of White-naped cranes showed significant relationship with logarithmic value of snow cover range and its period. Therefore, it suggests that the population size of the White-naped crane was affected by snow cover range n wintering period and this was because it was hard for them to find out rice grains which are their main food items, buried in snow cover. The population size variation in White-naped cranes was caused by some individuals which left Cheorwon for Izumi where snow cover had little influence on them. The wintering population in Izumi and Cheorwon had negative correlation, implying they were mutually related.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.686-697
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• 2018

Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.