• Journal of Korean Society for Atmospheric Environment
• /
• v.22 no.6
• /
• pp.940-953
• /
• 2006

The major source of carbon monoxide (CO) at the Earth's surface is the incomplete combustion of biomass and fossil fuels. Because the global lifetime of CO is about two months, it can be used as a tracer for pollution from anthropogenic activities and biomass hurtling. In this paper, we introduced the principle and algorithm of the Measurement of Pollution in the Troposphere (MOPITT) instrument for global CO monitoring. The MOPITT instrument, which was launched on the Satellite Terra in 1999, measures CO column and mixing ratio based on gas correlation radiometry. CO levels can be determined by a retrieval algorithm based on the maximum likelihood method minimizing the difference between observed and modeled radiances. MOPITT level 2 data (HDF format) can be downloaded through the Earth Observing System (EOS) data gateway of NASA. ASCII files of CO parameters can be extracted from HDF files, and then temporal and spatial distributions can be obtained. Finally, we showed an example of CO monitoring in April 2000. The locations of forest fires and distribution of MOPITT CO clearly indicated that not only anthropogenic emissions but also forest fires play an important role in CO levels and global CO distribution. Our introduction to MOPITT and the example of MOPITT data interpretation would be helpful for scientists who want to use the EOS data.

• Journal of Korea Water Resources Association
• /
• v.39 no.10 s.171
• /
• pp.823-832
• /
• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.31-31
• /
• 2015

토양수분은 일반적으로 시료를 채취하거나 현장에 설치된 다양한 센서를 통해 추정하지만 이는 시간과 비용이 많이 소모되기 ?문에 유역내의 공간적인 토양수분 분포를 추정하는데 상당한 어려움이 따른다. 토양수분뿐만 아니라 공간적인 대기현상, 토양수분, 식생현황 등을 관측하는데 대중적으로 사용되는 것이 위성 관측이며, 기본적으로는 위성에 탑재된 센서가 각 주파수대역에 따라 영상을 생성하면 이를 특정 알고리듬을 적용하여 원하는 값을 도출하게 된다. 토양수분 산정에 사용되는 대표적인 위성영상으로는 SMOS (Soil Moisture and Ocean Salinity), ARMS-E(Advanced Microwave Scanning Radiometer - Earth Observing System), ARMS2 (ARMS ver.2) 영상 등이 있으며, 이러한 위성은 해상도가 약 10 km ~ 40 km로 상당이 낮기 때문에 우리나라와 같이 면적이 좁고 지형이 복잡하며 다양한 토지피복이 밀집되어있는 곳에서는 기존 수문 연구에 응용할 수 있는 토양수분 공간지도 산정을 위해 상세화(Downscaling)과정이 필요하다고 판단된다. 따라서 본 연구에서는 ARMS2 토양수분 영상을 MODIS 영상의 식생지수(NDVI, Normalized Difference Vegetation Index), 알베도 및 온도를 활용하여 공간적으로 상세화된 토양 수분 지도를 작성하였고, 유역 내에서 실제 측정되고 있는 토양수분 관측값을 활용하여 상세화기법의 적용성을 검토하였다.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.953-966
• /
• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Journal of Convergence for Information Technology
• /
• v.11 no.11
• /
• pp.57-65
• /
• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.

• Korean Journal of Remote Sensing
• /
• v.32 no.3
• /
• pp.201-220
• /
• 2016

In this study, the net solar radiation fluxes at the surface are retrieved by updating an existing algorithm to be applicable for MODerate resolution Imaging Spectroradiometer (MODIS) observations, in which linear relationships between the solar radiation reflected from the top of atmosphere and the net surface solar radiation are employed. The results of this study have been evaluated through intercomparison with existing Clouds and the Earth's Radiant Energy System (CERES) data products and ground-based data from pyranometers at Gangneung-Wonju National University (GWNU) and the Southern Great Plains (SGP) of observatory of Atmospheric Radiation Measurement (ARM) site. Prior to the comparison of the surface radiation energy in relation to the energy balance of the earth, the radiation energy of the upper part of the atmosphere was compared. As a result, the coefficient of determination was over 0.9, showing considerable similarity, but the Root-Mean-Square-Deviation (RMSD) value was somewhat different, and the downward and net solar-radiation energy also showed similar results. The surface solar radiation data measured from pyranometers at Gangneung-Wonju National University (GWNU) and Atmospheric Radiation Measurement (ARM) observatory are used to validate the solar radiation data produced in this study. When compared to the GWNU, The results of this study show smaller RMSD values than CERES data, showing slightly better agreements with the surface data. On the other hand, when compared with the data from ARM SGP observatory, the results of this study bear slightly larger RMSD values than those for CERES. The downward and net solar radiation estimated by the algorithm of this study at a high spatial resolution are expected to be very useful in the near future after refinements on the identified problems, especially for those area without ground measurements of solar radiation.

• Horticultural Science & Technology
• /
• v.34 no.6
• /
• pp.860-870
• /
• 2016

Continuous monitoring of environmental parameters provides farmers with useful information, which can improve the quality and productivity of crops grown in greenhouses. The objective of this study was to develop a greenhouse environment measurement system using a low-cost microcontroller with open-source software. Greenhouse environment parameters measured were air temperature, relative humidity, and carbon dioxide ($CO_2$) concentration. The ranges of the temperature, relative humidity, and $CO_2$ concentration were -40 to $120^{\circ}C$, 0 to 100%, and 0 to 10,000 ppm, respectively. A $128{\times}64$ graphic LCD display was used for real-time monitoring of the greenhouse environments. An Arduino Uno R3 consisted of a USB interface for communicating with a computer, 6 analog inputs, and 14 digital input/output pins. A temperature/relative humidity sensor was connected to digital pins 2 and 3. A $CO_2$ sensor was connected to digital pins 12 and 13. The LCD was connected to digital pin 1 (TX). The sketches were programmed with the Arduino Software (IDE). A measurement system including the Arduino board, sensors, and accessories was developed (totaling $244). Data for the environmental parameters in a venlo-type greenhouse were obtained using this system without any problems. We expect that the low-cost microcontroller using open-source software can be used for monitoring the environments of plastic greenhouses in Korea.

• Journal of Korea Water Resources Association
• /
• v.47 no.10
• /
• pp.935-943
• /
• 2014

Normalized Difference Vegetation Index (NDVI) used as input data for various hydrologic models plays a key role in understanding the variation of Hydrometeological parameters and Interaction between surface and atmosphere. Many studies have been conducted to estimate accurate remotely-sensed NDVI using spectral characteristics of vegetation. In this study, we conducted comparative analysis between Communication, Ocean and Meteorological Satellite and MOderate-Resolution Imaging Spectroradiometer (MODIS) NDVI. For comparison, Maximum Value Composite (MVC) was used to estimate 8-day and 16-day composite COMS NDVI. Both 8-day and 16-day COMS NDVI showed high statistical results compared with MODIS NDVI. Based on the results in this study, it can be concluded that COMS can be widely applicable for further ecological and hydrological studies.

• Korean Journal of Remote Sensing
• /
• v.14 no.1
• /
• pp.1-16
• /
• 1998

Microwave brightness temperature data measured from the Special Sensor Microwave/Imager (SSM/I) aboard Defense Meteorological Satellite Program (DMSP) satellite are used to investigate the characteristics of hydrological features of the East Asian summer monsoon during 1994 and 1995. The analyzed parameters include total columnar water vapor, cloud liquid water, and rain rate. These are estimated from SSM/I brightness temperature data for the two summer seasons (June, July, August) of 1994 and 1995 over the Asian monsoon region (0$^{\circ}$-60$^{\circ}$N, 45$^{\circ}$-180$^{\circ}$E). Results indicate that there are periodic westward movement of dry air over the 20$^{\circ}$-30$^{\circ}$N latitudinal belt with about 20-30 day period. Considering that the location of the North Pacific high is closely linked to the evolution of the monsoon activities over East Asia, the westward expansion of the North Pacific high may be the one important element modulating the monsoon intensity.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.18 no.1
• /
• pp.32-39
• /
• 2013

Although space-borne satellites are useful in obtaining information all around the world, they cannot observe at a suitable time and place. In order to overcome these limitations, an airborne remote sensing system was developed in this study. It is composed of a SAR sensor and a thermal infrared sensor. Additionally GPS, IMU, and thermometer/hygrometer were attached to the plane for radiometric and geometric calibration. The brightness of SAR image varies depending on surface roughness, and capillary waves on the sea surface, which are easily generated by sea winds, induce the surface roughness. Thus, sea surface wind can be estimated using the relationship between quantified SAR backscattering coefficient and the sea surface wind. On the other hand, thermal infrared sensor is sensitive to measure object's temperature. Sea surface temperature is obtained from the thermal infrared sensor after correcting the atmospheric effects which are located between sea surface and the sensor. Using these two remote sensing sensors mounted on airplane, four test flights were carried out along the west coast of Korea. The obtained SAR and thermal infrared images have shown that these images were useful enough to monitor coastal environment and estimate marine meteorology data.