• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.289-292
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• 2008

Recently, several satellite data analyses projects and numerical weather prediction (NWP) reanalysis projects have produced the ocean surface Latent Heat Flux (LHF) data sets in the global coverage. Comparisons of these LHF data sets showed substantial discrepancies in the LHF values. Recently, the increase of LHF in during 1970s-1990s over the global ocean is shown by the LHF data that have been developed at the Objective Analyzed Air-Sea Fluxes (OAFlux) project. It is interesting to investigate the existence of the increase of LHF over a global ocean in the other LHF products. It is interesting to investigate the existence of the increase of LHF over a global ocean in the other LHF products. In this study, we assessed the consistencies and discrepancies of the inter-annual variability and decadal trend for the period 1988-2005 among six LHF products ((J-OFURO2, HOAPS3, IFREMER, NCEP1,2 and OAFlux) over the global ocean. As results, all LHF products showed a positive trend. In particular, the positive trend in satellite-based data analyses (J-OFURO2, HOAPS3, IFREMER) is larger than that in reanalysis products (NCEP1/2). Also, the consistencies and discrepancies are shown on the spatial patterns of the LHF trends across the six data sets. The positive trend of LHF is remarkable in the regions of western boundary currents such as the Kuroshio and the Gulf Stream in all LHF data sets. But, the discrepancies are shown on the spatial patterns of the LHF trends in tropics and subtropics. These discrepancies are primarily caused by the differences of the input meteorological state variables, particularly for the air specific humidity, used to calculate LHF.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.63-69
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• 2005

Interferometric Synthetic Aperture Radar(InSAR) is a rapidly evolving technique. Spectacular results obtained in various fields such as the monitoring of earthquakes, volcanoes, land subsidence and glacier dynamics, as well as in the construction of Digital Elevation Models(DEMs) of the Earth's surface and the classification of different land types have demonstrated its strength. As InSAR is a remote sensing technique, it has various sources of errors due to the satellite positions and attitude, atmosphere, and others. Therefore, it is important to validate its accuracy, especially for the DEM derived from Satellite SAR images. In this study, Real Time Kinematic(RTK) GPS and Kinematic GPS positioning were chosen as tools for the validation of InSAR derived DEM. The results showed that Kinematic GPS positioning had greater coverage of test area in terms of the number of measurements than RTK GPS. But tracking the satellites near and/or under trees md transmitting data between reference and rover receivers are still pending tasks in GPS techniques.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.51-59
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• 2013

It is usual to evaluate the performance of the cool roof by measuring in-site rooftop temperature using thermal infra-red camera. The principal advantage of rooftop thermal infrared image acquired in oblique vantage point of super high-rise building as a remote sensor is to provide, in a cost-effective manner, area-wide information required for a scattered rooftop target with different colors, utilizing wide view angle and multi-temporal data coverage. This research idea was formulated by incorporating the concept of traditional remote sensing into rooftop temperature monitoring. Correlations between infrared image of super high-rise building and in-situ data were investigated to compare rooftop surface temperature for a total of four different rooftop locations. The results of the correlations analyses indicate that the rooftop surface temperature by the infrared images of super high-rise building alone could be explained yielding $R^2$ values of 0.951. The visible permanent record of the oblique thermal infra-red image was quite useful in better understanding the nature and extent of rooftop color that occurs in sampling points. This thermal infrared image acquired in oblique vantage point of super high-rise made it possible to identify area wide patterns of rooftop temperature change subject to many different colors, which cannot be acquired by traditional in-site field sampling. The infrared image of super high-rise building breaks down the usual concept of field sampling established as a conventional cool roof performance evaluation technique.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.137-147
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• 2012

Recently, floating green algae (FGA) in open oceans and coastal waters have been reported over wide area, yet accurate detection of these using traditional ground based measurement and chemical analysis in the laboratory has been difficult or even impossible due to the lack of spatial resolution, coverage, and revisit frequency. In contrast, spectral reflectance measurement makes it possible to quickly assess the chlorophyll content in green algae. Our objectives are to investigate the spectral reflectance of the FGA observed in the Yellow Sea and to develop a new index to detect FGA from satellite imagery, namely floating green algae index (FGAI), which uses relatively simple reflectance ratio technique. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Geostationary Ocean Color Imager (GOCI) satellite images at 500m spatial resolution were utilized to produce FGAI which is defined as the ratio between reflectance at 860nm and 660nm bands. Both FGAI results yielded reasonable green algae detection at the regional scale distribution. Especially houly GOCI observations can present more detaield information of FGAI than low-orbit satellite.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.121-127
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• 2011

This paper presents an autonomous formation flight algorithm for micro aerial vehicles (MAVs) and its flight test results. Since MAVs have severe limits on the payload and flight time, formation of MAVs can help alleviate the mission load of each MAV by sharing the tasks or coverage areas. The proposed formation guidance law is designed using nonlinear dynamic inversion method based on 'Leader-Follower' formation geometric relationship. The sensing of other vehicles in a formation is achieved by sharing the vehicles' states using a high-speed radio data link. the designed formation law was simulated with flight data of MAV to verify its robustness against sensor noises. A series of test flights were performed to validate the proposed formation guidance law. The test result shows that the proposed formation flight algorithm with inter-communication is feasible and yields satisfactory results.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.158-168
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• 2009

As nation and society progresses, urban ground facilities and their management system get more complicated and the cost and effort to control the system efficiently grows exponentially. This study suggests to the deployment method of a sensor node by Wireless Sensor Network for controling the Urban Ground Facilities of National Facilities. First, we achieve the management facilities and method using the first analysis and then make the coverage of sensing and then set up the Sensor Node in Urban Ground Facilities. Second, we propose the solution way of repetition by the second analysis. And, we embody the GIS program by Digital Map and this method, we improve the reality by overlapping an aerial photo. Also we make an experience on the sensor node allocation using making program. we can remove the repetition sensor node about 50%, and we can confirm that the sensor nodes are evenly distributed on the road.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.125-125
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• 2020

European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.251-263
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• 2019

Sentinel-2 Multi Spectral Instrument(MSI) launched by the European Space Agency (ESA) offered high spatial resolution optical products, enhanced temporal revisit of five days, and 13 spectral bands in the visible, near infrared and shortwave infrared wavelengths similar to Landsat mission. Landsat satellite imagery has been applied to various previous studies, but Sentinel-2 optical satellite imagery has not been widely used. Currently, for global coverage, Sentinel-2 products are systematically processed and distributed to Level-1C (L1C) products which contain the Top-of-Atmosphere (TOA) reflectance. Furthermore, ESA plans a systematic global production of Level-2A(L2A) product including the atmospheric corrected Bottom-of-Atmosphere (BOA) reflectance considered the aerosol optical thickness and the water vapor content. Therefore, the Sentinel-2 L2A products are expected to enhance the reliability of image quality for overall coverage in the Sentinel-2 mission with enhanced spatial,spectral, and temporal resolution. The purpose of this work is a quantitative comparison Sentinel-2 L2A products and fully simulated image to evaluate the applicability of the Sentinel-2 dataset in cultivated land growing various kinds of crops in Korea. Reference image of Sentinel-2 L2A data was simulated by airborne hyperspectral data acquired from AISA Fenix sensor. The simulation imagery was compared with the reflectance of L1C TOA and that of L2A BOA data. The result of quantitative comparison shows that, for the atmospherically corrected L2A reflectance, the decrease in RMSE and the increase in correlation coefficient were found at the visible band and vegetation indices to be significant.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.117-127
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• 2015

Recently, research and development on satellite payloads are being developed such as the optical sensor, SAR etc. Satellite image for earth observation is being utilized both domestically and abroad. Advanced satellite payload technology has led to the collection and analysis of satellite images relying on the optical sensor. Currently, related organizations such as RDA(the Rural Development Administration) are collectively collaborating to plan a national project to develop a medium-sized satellite based on Korea's domestic technology independently. This paper investigated the cases of the past research on application of satellite images for agriculture and analyzed the technical specifications for satellite payload in each area of such application. Based on the results of the past surveys and consultation studies among local experts in satellite image application, we analyzed the current trends, plans and applications of domestic and overseas R&D in satellite payloads for earth observation in agriculture, and proposed the appropriate technical specifications for developing a future medium-sized satellite for agriculture. The proposed specifications were then incorporated into a simulated satellite to examine its performance to observe the Korean farming areas. The authors anticipate that the findings of this paper will form a useful technical basis for providing the appropriate specifications for developing future medium-sized satellite payloads to be used in agriculture and forestry, and enabling the end users to efficiently utilize the satellite.