• Journal of Plant Biotechnology
• /
• v.43 no.1
• /
• pp.21-29
• /
• 2016

Remote Sensing (RS) is a technique to obtain necessary information in a non-contact and non-destructive method by using various sensors on the surface, water or atmospheric phenomena. These techniques combine elements such as sensors, and platform and information communication technology (ICT) for mounting the sensor. ICT has contributed significantly to the success of smart agriculture through quantification and measurement of environmental factors and information such as weather, crop and soil management to distribution and consumption stage, as well as the production stage by the cloud computer. Remote sensing techniques, including non-destructive non-contact bioimaging (remote imaging) is required to measure the plant function. In addition, bioimaging study in plant science is performed at the gene, cellular and individual plant level. Recently, bioimaging technology is considered the latest phenomics that identifies the relationship between the genotype and environment for distinguishing phenotypes. In this review, trends in remote sensing in plants, plants diagnostics and response to environment and status of plants phonemics research were presented.

• Smart Media Journal
• /
• v.9 no.1
• /
• pp.75-83
• /
• 2020

Compensation services that are indispensable during large-scale public utilities projects have been gradually increasing with the recent increase in construction, but there are no systematic compensation services due to the complicated procedures and manual work. For this reason, various problems such as construction period delays due to various complaints, corruption in compensation work, and impossible to trace the history of compensation data in the past are emerging. In this paper, in order to solve this problem, in-depth interviews and questionnaires were conducted to find out the problems of each compensation status. Based on this, 3 core technologies and 10 technical needs based on ICT were selected to improve the compensation work by deriving STEEP analysis and Issue Tree. The three core technologies are big data-based decision-making and prediction technology, advanced measurement technology, and open cloud-based compensation platform technology. In order to introduce the derived technologies to the institutions in charge of compensation, the possibility of technology diffusion by project operators was suggested based on the results of the current status of informatization by institution. Based on the core technology derived from this paper, it is necessary to make a prototype that can be advanced in compensation work and apply it to each institution and analyze the effect.

• Journal of the Korean earth science society
• /
• v.26 no.8
• /
• pp.790-799
• /
• 2005

We investigate the optical properties of aerosols over Gongju by an indirect method using the pound measurement, Sky-radiometer. The analysis period is from January to December, 2004. Skyrad. pack.3 is used to estimate the optical properties, such as the aerosol optical thickness (AOT), single scattering albedo (SSA), ${\AA}ngstron$ exponent $({\alpha})$ and size distribution, of aerosols from the ground measured radiance data. And qualify control is applied to minimize the cloud-contaminated data and improve the quality of analysis results. The 12-month average of AOT, ${\alpha}$, and SSA are 0.46, 1.14, and 0.91, respectively. The average volume spectra of aerosols shows a bi-modal distribution, the first peak at fine mode and the second peak at coarse mode. AOT and coarse particles clearly increases while SSA decreases during the Asian dust events. The optical properties of aerosols at Gongju vary with?seasons, but those are not influenced by the wind direction.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_2
• /
• pp.849-858
• /
• 2023

Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.3
• /
• pp.374-383
• /
• 2010

Microwave radar can penetrate cloud cover regardless of weather conditions and can be used day and night. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. Kim et al. (2009) have measured backscattering coefficients of paddy rice using L-, C-, X-band scatterometer system with full polarization and various angles during the rice growth period and have revealed the necessity of near-continuous automatic measurement to eliminate the difficulties, inaccuracy and sparseness of data acquisitions arising from manual operation of the system. In this study, we constructed an X-band automatic scatterometer system, analyzed scattering characteristics of paddy rice from X-band scatterometer data and estimated rice growth parameter using backscattering coefficients in X-band. The system was installed inside a shelter in an experimental paddy field at the National Academy of Agricultural Science (NAAS) before rice transplanting. The scatterometer system consists of X-band antennas, HP8720D vector network analyzer, RF cables and personal computer that controls frequency, polarization and data storage. This system using automatically measures fully-polarimetric backscattering coefficients of rice crop every 10 minutes. The backscattering coefficients were calculated from the measured data at a fixed incidence angle of $45^{\circ}$ and with full polarization (HH, VV, HV, VH) by applying the radar equation and compared with rice growth data such as plant height, stem number, fresh dry weight and Leaf Area Index (LAI) that were collected at the same time of each rice growth parameter. We examined the temporal behaviour of the backscattering coefficients of the rice crop at X-band during rice growth period. The HH-, VV-polarization backscattering coefficients steadily increased toward panicle initiation stage, thereafter decreased and again increased in early-September. We analyzed the relationships between backscattering coefficients in X-band and plant parameters and predicted the rice growth parameters using backscattering coefficients. It was confirmed that X-band is sensitive to grain maturity at near harvesting season.

• Journal of the Korean earth science society
• /
• v.26 no.3
• /
• pp.283-296
• /
• 2005

The effect of ozone and surface temperature on the ozone band at $9.7{\mu}m$ has been investigated from radiative transfer theory together with observations in order to derive empirical methods for remotely sensing ground-ozone concentration. Simultaneous observations of satellite (MODIS Aqua; ECT 13:30) and ground-ozone at 79 stations have been used over the Seoul Metropolitan Area (SMA; 125.7-127.2 E, 37.2-37.7 N) during four ozone-warning days in the year 2003. Cloud effect on the band in the methods was filtered out based on synoptic observations. Upwelling radiance values at $9.6{\mu}m$ which have been estimated at the given ozone concentration of 327-391 DU depend on surface temperature (Ts) showing $5.52\~5.78Wm^{-2}sr^{-1}\;at\;Ts = 290 K,\;and\;9.00\~9.57Wm^{-2}sr^{-1}$ Ts = 325K. Thus, the partitioned contributions of ozone and temperature to intensity of ozone absorption band are $0.26Wm^{-1}sr^{-1}/64\;DU\;and\;0.31 Wm^{-2}sr^{-1}/35K$, respectively. Here the intensity which has been used to remotely detect ground-ozone concentration from infrared satellite measurement is defined as the difference in brightness temperature between $11{\mu} m\;and\;9.7{\mu}m (i.e.,\; T_{11-9.7})$. The methods in this study have been applied to estimate ground-ozone from MODIS data in cases that there are significant correlations between the band intensity and ground-ozone. The values of estimated ozone significantly correlate (0.49-0.63) with ground observations at a significance level of $1\%$. For the improved methods, further study may be required to use tropospheric ozone rather than ground-ozone, considering the variation stratospheric ozone.

• Korean Journal of Remote Sensing
• /
• v.37 no.3
• /
• pp.449-461
• /
• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Korean Journal of Remote Sensing
• /
• v.40 no.2
• /
• pp.229-241
• /
• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.