• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.351-353
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• 2003

We present a retrieval scheme for the remote sensing of evapotranspiration (ET) over rice paddy. To perform the retrieval, high-resolution airborne imagery of multi-spectral visible and thermal infrared data, and ground-based meteorological measurements are utilized. Our ET retrieval scheme is based on the basic principal of surface energy budget, which is a result of balance in longwave and shortwave radiation, latent heat, sensible heat, and energy flux into the ground. To partition the latent and sensible heat fluxes of interest from the energy balance equation, three basic parameters are of most concern, including albedo, surface temperature, and normalized difference vegetation index (NDVI). The NDVI and albedo can be easily derived from the visible and near infrared spectral data, while the surface tem-perature can be determined through the analysis of the infrared data with the Stefan Boltzmann law. From the airborne imagery taken on 28 April 2003, we observe very good dry and wet pixels that can be easily corre-sponded to the radiation and evaporation controlled crite-ria, respectively, and, hence, for the further use in defin-ing the evaporative fraction needed to partition sensible and latent heat fluxes from the net energy flux. The de-rived ET is compared with the in situ measurements.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.1-10
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• 2023

Open surface water body extraction is gaining popularity in recent years due to its versatile applications. Multiple techniques are used for water detection based on applications. Different applications of Radar as LADAR, Ground-penetrating, synthetic aperture, and sounding radars are used to detect water. Shortwave infrared, thermal, optical, and multi-spectral sensors are widely used to detect water bodies. A stereo camera is another way to detect water and different methods are applied to the images of stereo cameras such as deep learning, machine learning, polarization, color variations, and descriptors are used to segment water and no water areas. The Satellite is also used at a high level to get water imagery and the captured imagery is processed using various methods such as features extraction, thresholding, entropy-based, and machine learning to find water on the surface. In this paper, we have summarized all the available methods to detect water areas. The main focus of this survey is on water detection especially in small patches or in small areas. The second aim of this survey is to detect water hazards for unmanned vehicles and off-sure navigation.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.437-443
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• 2015

This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.305-316
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• 2018

As the urbanization ratio increases, the heat environment in cities is becoming more important due to the urban heat island. In this study, the heat island spatial analysis was calculated and conducted for analysis of urban thermal environment of Sejong city, which was launched in 2012 and has been developed rapidly. To analyze the ratio and change rate of urban area, a multi temporal land cover map (2013 to 2015 and 2017) of study area is generated based on Landsat-8 OLI/TIRS (Operational Land Imager / Thermal Infrared Sensor) satellite imagery. Then, we select an TIR (Thermal Infrared) band from the two TIR bands provided by the Landsat-8, which is used for calculating the heat island potential, through the accuracy evaluation of the brightness temperature and AWS (Automatic Weathering Station) data. Based on the selected band and surface emissivity, land surface temperature is calculated and the estimated heat island potential change is analyzed. As a result, the land surface temperature of the high ratio and change rate of urban area was significantly higher than the surrounding area around $3^{\circ}C$ to $4^{\circ}C$, and the heat island potential was also higher around $4^{\circ}C$ to $5^{\circ}C$. However, the heat island phenomenon was alleviated in urban areas with high rate of change that also show high green area ratio. Therefore, we demonstrated that dense urban area increases the possibility of inducing heat island, but it can mitigate the heat island through green areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.555-563
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• 2018

Thermal infrared images have the characteristic of being able to detect objects that can not be seen with the naked eye and have the advantage of easily obtaining information of inaccessible areas. However, TIR (Thermal InfraRed) images have a relatively low spatial resolution. In this study, the applicability of the pansharpening algorithm used for satellite imagery on images acquired by the UAV (Unmanned Aerial Vehicle) was tested. RGB image have higher spatial resolution than TIR images. In this study, pansharpening algorithm was applied to TIR image to create the images which have similar spatial resolution as RGB images and have temperature information in it. Experimental results show that the pansharpening algorithm using the PC1 band and the average of RGB band shows better results for the quantitative evaluation than the other bands, and it has been confirmed that pansharpening results by ATWT (${\grave{A}}$ Trous Wavelet Transform) exhibit superior spectral resolution and spatial resolution than those by HPF (High-Pass Filter) and SFIM (Smoothing Filter-based Intensity Modulation) pansharpening algorithm.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.883-902
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• 2023

Water is critical to the health and productivity of fruit trees. Efficient monitoring of water stress is essential for optimizing irrigation practices and ensuring sustainable fruit production. Short-range sensing can be reliable, rapid, inexpensive, and used for applications based on well-developed and validated algorithms. This paper reviews the recent advancement in fruit tree water stress detection via short-range sensing, which can be used for irrigation scheduling in orchards. Thermal imagery, near-infrared, and shortwave infrared methods are widely used for crop water stress detection. This review also presents research demonstrating the efficacy of short-range sensing in detecting water stress indicators in different fruit tree species. These indicators include changes in leaf temperature, stomatal conductance, chlorophyll content, and canopy reflectance. Short-range sensing enables precision irrigation strategies by utilizing real-time data to customize water applications for individual fruit trees or specific orchard areas. This approach leads to benefits, such as water conservation, optimized resource utilization, and improved fruit quality and yield. Short-range sensing shows great promise for potentially changing water stress monitoring in fruit trees. It could become a useful tool for effective fruit tree water stress management through continued research and development.

• Korean Journal of Remote Sensing
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• v.7 no.2
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• pp.149-163
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• 1991

This paper discusses the capabilities of airborne remotely sensed data to detect and classify forest damades. In this work the AMS (Aircraft Multiband Scanner) was used to obtain digital imagery at 300m altitude for forest damage inventory in the Black Forest of Germany. MSS(Multispectral Scanner) digital numbers were converted to spectral emittance and radiance values in 8 spectral bands from the visible to the thermal infrared and submitted to a maximum-likelihood classification for : (1) tree species ; and. (2) damage classes. As expected, the resulted, the results of MSS data with high spatial resolution 0.75m$\times$0.75m enabled the detection and identification of single trees with different damages and were nearly equivalent to the truth information of ground checked data.

• The Journal of Engineering Geology
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• v.26 no.1
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• pp.23-32
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• 2016

This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.

• Proceedings of the KSRS Conference
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• v.2
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• pp.752-755
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• 2006

Evaportranspiration is an important factor in hydrology cycle. Traditionally, it is measured by using basin or empirical formula with meteorology data, while it does not represent the evaportranspiration over a regional area. With the advent of improved remote sensing technology, it becomes a surface parameter of research interest in the field of remote sensing. Airborne and satellite imagery are utilized in this study. The high resolution airborne images include visible, near infrared, and thermal infrared bands and the satellite images are acquired by MODIS. Surface heat fluxes such as latent heat flux and sensible heat flux are estimate by using airborne and satellite images with surface meteorological measurements. We develop a new method to estimate the evaportranspiration over the rice paddy. The surface heat fluxes are initialized with a surface energy balance concept and iterated for convergent solution with atmospheric correct functions associated with aerodynamic resistance of heat transport. Furthermore, we redistribute the total net energy into sensible heat and latent heat fluxes. The result reveals that radiation and evaporation controlled extremes can be properly decided with both airborne and satellite images. The correlation coefficient of latent heat flux and sensible heat flux with corresponding in situ observations are 0.66 and 0.76, respectively. The relative root mean squared errors (RMSEs) for latent heat flux and sensible heat flux are 97.81 $(W/m^2)$ and 124.33 $(W/m^2)$, respectively. It is also shown that the newly developed retrieval scheme performs well when it is tested by using MODIS date.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1469-1478
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• 2018

Earthquakes and volcanic eruptions are disaster that causes billions of dollars in property damage and the loss of human life. Therefore, it is required to effectively monitor earthquakes and volcanoes. With the increase of satellite data, researches on earthquake and volcano using satellite imagery has been improved. Satellite images can be divided into three types i.e. optical, thermal, Synthetic Aperture Radar (SAR) and each image has different characteristics. In this article, we summarized its advantages and disadvantages of each type of satellite image. Moreover, we investigated the previous researches about earthquake and volcano using satellite images. Finally, we suggest application method to respond earthquake and volcano disaster using satellite images.