• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1397-1399
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• 2003

When and Where, What kind of agricultural products will be produced and provided for the market? It is a commercial requirement, and also an academic questions to remote sensing technology. Crop physiology analysis and growth monitoring are important elements for precision agriculture management. Remote sensing technology supplies us more selections and available spaces in this dynamic change study by producing images of different spatial, spectral and temporal resolutions. Especially, the hyperspectral remote sensing should do play a key role in crop growth investigation at national, regional and global scales. In the past five years, Chinese academy of sciences and Japan NTT-DATA have made great efforts to establish a prototype information service system to dynamically survey the vegetable planting situation in Nagano area of Japan mainly based on remote sensing data. For such concern, a flexible and light-duty flight system and some practical data processing system and some necessary background information should be rationally made together. In addition, some studies are also important, such as quick pre-processing for hyperspectral data, Multi-temporal vegetation index analysis, hyperspectral image classification in support of GIS data, etc. In this paper, several spectral data analysis models and a designed airborne platform are provided and discussed here.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.837-847
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• 2023

In this study, we explored a method for assessing the extent of damage caused by chemical substances at an accident site through the use of a vegetation index. Data collection involved the deployment of two different drone types, and the damaged area was determined using photogrammetry technology from the 3D point cloud data. To create a vegetation index image, we utilized spectral band data from a multi-spectral sensor to generate an orthoimage. Subsequently, we conducted statistical analyses of the accident site with respect to the damaged area using a predefined threshold value. The Kappa values for the vegetation index, based on the near-infrared band and the green band, were found to be 0.79 and 0.76, respectively. These results suggest that the vegetation index-based approach for analyzing damage areas can be effectively applied in investigations of chemical accidents.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.60-68
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• 2007

Conventional analysis of spectral induced polarization (SIP) data consists of measuring impedances over a range of frequencies, followed by spectral analysis to estimate spectral parameters. For the quantitative and accurate estimation of subsurface SIP parameter distribution, however, a sophisticated and stable inversion technique is required. In this study, we have developed a two-step inversion approach to obtain the two-dimensional distribution of SIP parameters. In the first inversion step, all the SIP data measured over a range of frequencies are simultaneously inverted, adopting cross regularisation of model complex resistivities at each frequency. The cross regularisation makes it possible to enhance the noise characteristics of the inversion by imposing a strong assumption, that complex resistivities should show similar characteristics over a range of frequencies. In numerical experiments, we could verify that our inversion approach successfully reduced inversion artefacts. As a second step, we have also developed an inversion algorithm to obtain SIP parameters based on the Cole-Cole model, in which frequency-dependent complex resistivities from the first step are inverted to obtain a two-dimensional distribution of SIP parameters. In numerical tests, the SIP parameter images showed a fairly good match with the exact model, which suggests that SIP imaging can provide a very useful subsurface image to complement resistivity.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1041-1053
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• 2018

In this study, a real-time storage level and capacity monitoring and forecasting system for Yongdam Dam watershed was developed using high resolution satellite image. The drought indices such as Standardized Precipitation Index (SPI) from satellite data were used for storage level monitoring in case of drought. Moreover, to predict storage volume we used a statistical method based on Principle Component Analysis (PCA) of Singular Spectrum Analysis (SSA). According to this study, correlation coefficient between storage level and SPI (3) was highly calculated with CC=0.78, and the monitoring and predictability of storage level was diagnosed using the drought index calculated from satellite data. As a result of analysis of principal component analysis by SSA, correlation between SPI (3) and each Reconstructed Components (RCs) data were highly correlated with CC=0.87 to 0.99. And also, the correlations of RC data with Normalized Water Surface Level (N-W.S.L.) were confirmed that has highly correlated with CC=0.83 to 0.97. In terms of high resolution satellite image we developed a water detection algorithm by applying an exponential method to monitor the change of storage level by using Multi-Spectral Instrument (MSI) sensor of Sentinel-2 satellite. The materials of satellite image for water surface area detection in Yongdam dam watershed was considered from 2016 to 2018, respectively. Based on this, we proposed the possibility of real-time drought monitoring system using high resolution water surface area detection by Sentinel-2 satellite image. The results of this study can be applied to estimate of the reservoir volume calculated from various satellite observations, which can be used for monitoring and estimating hydrological droughts in an unmeasured area.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.452-455
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• 2004

MSC (Multi-Spectral Camera) system is a remote sensing instrument to obtain high resolution ground image. EOS (Electro-Optic System) for MSC mainly consists of PMA (Primary Mirror Assembly), SMA (Secondary Mirror Assembly), HSTS (High Stability Telescope Structure) and DFPA (Detector Focal Plane Assembly). High performance of EOS makes it possible for MSC system to provide high resolution and high quality ground images. Temperature of the EOS needs to be controlled to be in a specific range in order not to have any thermal distortion which can cause performance degradation. It is controlled by full redundant CPU based electronics. The validity of thermistor readings can be checked because a few thermistors are installed on each control point on EOS. Various kinds of thermal control logics are used to prevent 'Single Point Failure'. Control logic has a few set of database in order not to be corrupted by SEU (Single Event Upset). Even though the thermal control logic is working automatically, it can also be monitored and controlled by ground-station operator. In this paper, various ways of thermal control logic for EOS in MSC will be presented, which include thermal control mode and logic, redundancy design and status monitoring and reporting scheme.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.448-451
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• 2004

MSC (Multi-Spectral Camera) system is an electro-optical camera system which is being developed to be installed on KOMPSAT-2 satellite. High resolution image data from MSC system will be transmitted to the ground-station through x-band antenna called APS (Antenna Pointing System). APS is a directional antenna which will point to the receiving antenna at ground station while the satellite is passing over it. The APS needs to be controlled accurately to provide the reliable communication with big RF link margin. The APS is controlled by ATS (Antenna Tracking Software) which is included in the MSC software. ATS uses the closed loop control algorithm which will use TPF (Tracking Parameter File) as an input for antenna position, and will use two resolve readings from APS as a feedback. ATS has been developed and verified using APS QM (Qualification Model) and all the control parameters for ATS have been tested and verified. Various kinds of maximum, nominal and realistic dynamics for the APS movement have been simulated and verified. In this paper, closed loop servo control algorithm and obtained APS position error from the verification test with APS QM will be presented in detail

• Proceedings of the KSRS Conference
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• v.2
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• pp.555-558
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• 2006

In recent years, urban development has expanded rapidly in Nawabshah City of Pakistan. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. The core objective of this study are to provide time-series information to define and measure the urban land cover changes of Nawabshah, Pakistan between the years 1992 and 2002, and to examine related urbanization impacts on air quality of the study area. Two multi-temporal Landsat images acquired in 1992 and 2002 together with standard topographical maps to measure land cover changes were used in this study. The image processing and data manipulation were conducted using algorithms supplied with the ERDAS Imagine software. An unsupervised classification approach, which uses a minimum spectral distance to assign pixels to clusters, was used with the overall accuracy ranging from 84 percent to 92 percent. Land cover statistics demonstrate that during the study period (1992-2002) extensive transformation of barren and vegetated lands into urban land have taken place in Nawabshah City. Results revealed that land cover changes due to urbanization has not only contaminated the air quality of the study area but also raised the health concerns for the local residents.

• Aerospace Engineering and Technology
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• v.3 no.2
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• pp.160-169
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• 2004

In order to get the high resolution satellite image, MSC has TDI function in the KOMPSAT-2. So it is required to control the yaw angle of the attitude as operation concepts of KOMPSAT-2. This study was to explain the TDI function, to set up the geometric equation to satisfy the condition, and finally to determine the equation of yaw angle. The calculating program was developed and simulated with orbit and imaging attitude as input data, and the results were compared with the yaw steering values calculated in the on-board computer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.593-598
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• 2006

High-resolution satellite imagery has many benefits, compared to aerial photo in the wide area as well as multi-spectral character. So, it can be used well for constructing GIS data when making digital map. This study analysed the possibilities that road information derived automatically from IKONOS can be used for making ITS system or updating digital map of the urban areas where change frequently and producing satellite image map. In this study, Sobel was applied for road edge dectection after low pass filtering. As the results, it's possible for low pass filtering and high pass filtering to be used as the basic data for ITS construction when extracting edge roads and constructs according to the characteristic of high-resolution satellite imagery.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.597-609
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• 2012

Leaf area index (LAI) is important in explaining the ability of the crop to intercept solar energy for biomass production and in understanding the impact of crop management practices. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of IKONOS, Landsat TM, and MODIS satellite images using empirical models and demonstrates its use with data collected at Missouri field sites. LAI data were obtained several times during the 2002 growing season at monitoring sites established in two central Missouri experimental fields, one planted to soybean (Glycine max L.) and the other planted to corn (Zea mays L.). Satellite images at varying spatial and spectral resolutions were acquired and the data were extracted to calculate normalized difference vegetation index (NDVI) after geometric and atmospheric correction. Linear, exponential, and expolinear models were developed to relate temporal NDVI to measured LAI data. Models using IKONOS NDVI estimated LAI of both soybean and corn better than those using Landsat TM or MODIS NDVI. Expolinear models provided more accurate results than linear or exponential models.