• Proceedings of the KSRS Conference
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• v.1
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• pp.150-152
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• 2006

The DISCOVER Project (${\underline{D}}istributed$ ${\underline{I}}nformation$ ${\underline{S}}ervices$ for ${\underline{C}}limate$ and ${\underline{O}}cean$ products and ${\underline{V}}isualizations$ for ${\underline{E}}arth$ ${\underline{R}}esearch$) is a NASA funded Earth Science REASoN project that strives to provide highly accurate, carefully calibrated, long-term climate data records and near-real-time ocean products suitable for the most demanding Earth research applications via easy-to-use display and data access tools. A key element of DISCOVER is the merging of data from the multiple sensors on multiple platforms into geophysical data sets consistent in both time and space. The project is a follow-on to the SSM/I Pathfinder and Passive Microwave ESIP projects which pioneered the simultaneous retrieval of sea surface temperature, surface wind speed, columnar water vapor, cloud liquid water content, and rain rate from SSM/I and TMI observations. The ocean products available through DISCOVER are derived from multi-sensor observations combined into daily products and a consistent multi-decadal climate time series. The DISCOVER team has a strong track record in identifying and removing unexpected sources of systematic error in radiometric measurements, including misspecification of SSM/I pointing geometry, the slightly emissive TMI antenna, and problems with the hot calibration source on AMSR-E. This in-depth experience with inter-calibration is absolutely essential for achieving our objective of merging multi-sensor observations into consistent data sets. Extreme care in satellite inter-calibration and commonality of geophysical algorithms is applied to all sensors. This presentation will introduce the DISCOVER products currently available from the web site, http://www.discover-earth.org and provide examples of the scientific application of both the diurnally corrected optimally interpolated global sea surface temperature product and the 4x-daily global microwave water vapor product.

• Proceedings of the KSRS Conference
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• v.2
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• pp.959-962
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• 2006

Public education is undoubtedly a very important aspect for a country to develop space program. People have the rights to understand how the tax they paid is being used. This paper addresses the effectiveness of FORMOSAT-2 on public education in Taiwan. As the first remote sensing satellite of the National Space Organization (NSPO) of Taiwan, FORMOSAT-2 is a small satellite of 746 kg mass for two remote sensing missions: Earth and upward lightning observations. The mission orbit is sun-synchronous of 888 km altitude for exactly 14 revolutions per day. For earth observation, the payload is an advanced high resolution remote sensing instrument (RSI) with ground sampling distance (GSD) 2 m in panchromatic (PAN) band and 8 m in four multi-spectral (MS) bands. For upward lightning observation, the payload is an imager of sprites and upper atmospheric lightning (ISUAL). After more than two years of Earth observation started in June 2004, the effectiveness of FORMOSAT-2 images on public education in Taiwan is very promised. Five domestic universities and one private company in Taiwan have signed contracts respectively with NSPO to take the roles of satellite image investigator and distributor. A private company has signed contract with NSPO to generate and provide URMAP (= your map) in its website for general public applications by using FORMOSAT-2 images. The Newtonkids Book Company used FORMOSAT-2 images to publish a kind of calendar for children education purpose. Besides, a science team in National Cheng Kung University (NCKU) is doing the research work on the 3820 (up to 30 June 2006) transient luminous events (TLEs) observed by FORMOSAT-2.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1785-1791
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• 2021

Natural and environmental disasters are recently increasing in frequency and complexity worldwide due to the rapid expansion of overpopulation, industrialization, and urbanization. Thus, analyzing past critical events/disasters in deep and preparing for future disasters in terms of risk identification, assessment and management are imperative requirements. In this special issue, we introduce several interesting studies covering disaster risk management and observation technologies for the heat waves, particulate matters, floods, drought, and earthquake using remote sensing and GIS performed by i-SEED (School of Integrated Science for Sustainable Earth & Environmental Disaster at Pukyong National University). We expect that the results of this special issue provide comprehensive information on the risk management and damage prevention of natural and environmental disasters and offer guidance on the application to future disasters to reduce their risks and impacts.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.887-899
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• 2022

Drought caused by meteorological factors negatively affects vegetation in terrestrial ecosystems. In this study, the state in which meteorological drought affects vegetation was defined as the ecological drought of vegetation, and the ecological drought condition index of vegetation (EDCI-veg) was proposed to quantitatively monitor the degree of impact. EDCI-veg is derived from a copula-based bi-variate joint probability model between vegetation and meteorological drought information, and can be expressed numerically how affected the current vegetation condition was by the drought when the drought occurred. Comparing past meteorological drought events with their corresponding vegetation condition, the proposed index was examined, and it was confirmed that EDCI-veg could properly monitor the ecological drought of vegetation. In addition, it was possible to spatially identify ecological drought conditions by creating a high-resolution drought map using remote sensing data.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.125-127
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• 2004

High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry, texture and attribute characteristic. The pixel-based image classification can't satisfy high-resolution satellite image's classification precision and produce large data redundancy. Object-oriented information extraction not only depends on spectrum character, but also use geometry and structure information. It can provide an accessible and truly revolutionary approach. Using Beijing Spot 5 high-resolution image and object-oriented classification with the eCognition software, we accomplish the cultures' precise classification. The test areas have five culture types including water, vegetation, road, building and bare lands. We use nearest neighbor classification and appraise the overall classification accuracy. The average of five species reaches 0.90. All of maximum is 1. The standard deviation is less than 0.11. The overall accuracy can reach $95.47\%.$ This method offers a new technology for high-resolution satellite images' available applications in remote sensing culture classification.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.382-387
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• 2002

In this paper, we propose a geostatistical approach incorporated to the Bayesian data fusion technique for supervised classification of multi-sensor remote sensing data. Traditional spectral based classification cannot account for the spatial information and may result in unrealistic classification results. To obtain accurate spatial/contextual information, the indicator kriging that allows one to estimate the probability of occurrence of classes on the basis of surrounding observations is incorporated into the Bayesian framework. This approach has its merit incorporating both the spectral information and spatial information and improves the confidence level in the final data fusion task. To illustrate the proposed scheme, supervised classification of multi-sensor test remote sensing data set was carried out.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.404-408
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• 1998

Yellow sand event has been studied using SeaWiFS data in order to examine the aerosol optical characteristics in the Yellow Sea and their influences on the atmospheric correction for the ocean color remote sensing. Two SeaWiFS images of April 18 and April 25, 1998, representing Yellow Sand event and clear-sky case respectively, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. SeaWiFS aerosol optical thickness is compared with nearby ground-based sun photometer measurements and also is compared with radiative transfer simulation in conjunction with yellow sand model, examining the performance of NASA's atmospheric correction algorithm in case of the heavy dust event.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.280.1-285
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• 1998

The earth's environmental problems have attracted serious attention worldwide. Various kinds of environmental data, such as remote sensing data, have become available for examining. Although this data is crucial to understanding such problems, there has become an over-abundance in variety of size, format, and filetype which makes it difficult for researchers to handle. We feel that earth environmental researchers should not be burdened by such cumbersome tasks. Therefore, we are developing a digital library for earth environmental information and a VRML based data visualization system for it. Even now, content-based image retrieval systems have many problems attributed to the degree of difficulty in implementing them. Thus, we are trying to visualize this data so that researchers can utilize it more efficiently, effectively, and easily. A great advantage for VRML users is that people can see environmental data from any perspective above the earth and with any resolution easily. Also by using MPEG-movie, users can observe the changes of data drawn from time series files.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.61-69
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• 2009

This paper presents design and implementation of a system for effective visualizing driving history data of the Jeju taxi telematics system using Google Earth. It is possible to review the situation of all taxies or extract the trace of any taxi or search taxies driven through a region of interest.

• Current Industrial and Technological Trends in Aerospace
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• v.9 no.1
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• pp.45-54
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• 2011

Earth observation satellites data apply to various fields and global satellite imagery market continues to expand with increasing the scale according to the developed satellites. Sudden natural disasters frequently have occurred in Japan. ALOS satellite data support to repair the damaged area and mitigate the disasters in Japan as well as all around the world. In this paper, the status of remote sensing and data policy in Japan are described. In addition, satellite-based remote sensing technology effectively contribute to the public sector and related support to establish the infra system of satellite application promotion has been investigated.