• Title/Summary/Keyword: Environmental sensing

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A Study on Index of Vegetation Surface Roughness using Multiangular Observation

  • Konda, Asako;Kajiwara, Koji;Honda, Yoshiaki
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.673-678
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    • 2002
  • A satellite remote sensing is useful for vegetation monitoring. But it has some problem. One of these, it is difficult to find a difference of vegetation surface roughness using satellite remote sensing. Each vegetation type has unique surface roughness, for example needle leaves forest, broad leaves forest and grassland. Difference of vegetation surface roughness can be detected by satellite multiangular observation. In this study, objective is to propose index of vegetation surface roughness using BRF property. General vegetation indices are calculated from nadir data of satellite data. A proposed index is calculated from two different observation zenith angle data. Two different zenith data can provide BRF (Bi-directional Reflectance Factor) property of satellite observation data. A proposed index was able to detect different value on where NDVI shows similar high value areas of rice field and forest. This index is useful for vegetation monitoring.

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Impact of a New Formula on the Fresnel Reflectance on Microwave Remote Sensing

  • Qing, Xu;Yuguang, Liu
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1340-1342
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    • 2003
  • In microwave remote sensing, the Fresnel reflectance formula is widely used in the sea surface emissivity modeling. As an essential contribution to microwave remote sensing, a new formula on the Fresnel reflectance has been derived based on our understanding of the complex index of refraction and continuity condition of E-M waves at the interface between two mediums. The proposed formula can be used to obtain the emissivity of sea surface, which is useful to retrieve sea surface temperature, sea surface salinity and the brightness temperature. Considering Bragg-resonant scatter, it is useful for the calculation of the normalized radar cross-section, and the retrieval of sea surface wind either.

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Improving an index for surface water detection

  • Hu, Yuanming;Paik, Kyungrock
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.144-144
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    • 2022
  • Identifying waterbody from remote sensing images, namely water detection, helps understand continuous redistribution of terrestrial water storage and accompanying hydrological processes. It also allows us to estimate available surface water resources and help effective water management. For this problem, NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index) are widely used. Although remote sensing indexes can highlight remote sensing image in the water, the noise and the spatial information of the remote sensing image are difficult to be considered, so the accuracy is difficult to be compared with the visual interpretation (the most accurate method, but it requires a lot of labor, which makes it difficult to apply). In this study, we attempt to improve existing NDWI and MNDWI to better water detection. We establish waterbody database of South Korea first and then used it for assessing waterbody indices.

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Remote Sensing and GIS for Earth & Environmental disasters: The Current and Future in Monitoring, Assessment, and Management (원격탐사와 GIS를 이용한 지구환경재해 관측과 관리 기술 현황)

  • Yang, Minjune;Kim, Jae-Jin;Han, Kyung-soo;Kim, Jinsoo
    • 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.

Monitoring the Ecological Drought Condition of Vegetation during Meteorological Drought Using Remote Sensing Data (원격탐사자료를 활용한 기상학적 가뭄 시 식생의 생태학적 가뭄 상태 모니터링)

  • Won, Jeongeun;Jung, Haeun;Kang, Shinuk;Kim, Sangdan
    • 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.

A wireless impedance analyzer for automated tomographic mapping of a nanoengineered sensing skin

  • Pyo, Sukhoon;Loh, Kenneth J.;Hou, Tsung-Chin;Jarva, Erik;Lynch, Jerome P.
    • Smart Structures and Systems
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    • v.8 no.1
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    • pp.139-155
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    • 2011
  • Polymeric thin-film assemblies whose bulk electrical conductivity and mechanical performance have been enhanced by single-walled carbon nanotubes are proposed for measuring strain and corrosion activity in metallic structural systems. Similar to the dermatological system found in animals, the proposed self-sensing thin-film assembly supports spatial strain and pH sensing via localized changes in electrical conductivity. Specifically, electrical impedance tomography (EIT) is used to create detailed mappings of film conductivity over its complete surface area using electrical measurements taken at the film boundary. While EIT is a powerful means of mapping the sensing skin's spatial response, it requires a data acquisition system capable of taking electrical impedance measurements on a large number of electrodes. A low-cost wireless impedance analyzer is proposed to fully automate EIT data acquisition. The key attribute of the device is a flexible sinusoidal waveform generator capable of generating regulated current signals with frequencies from near-DC to 20 MHz. Furthermore, a multiplexed sensing interface offers 32 addressable channels from which voltage measurements can be made. A wireless interface is included to eliminate the cumbersome wiring often required for data acquisition in a structure. The functionality of the wireless impedance analyzer is illustrated on an experimental setup with the system used for automated acquisition of electrical impedance measurements taken on the boundary of a bio-inspired sensing skin recently proposed for structural health monitoring.

Disaster Prediction, Monitoring, and Response Using Remote Sensing and GIS (원격탐사와 GIS를 이용한 재난 예측, 감시 및 대응)

  • Kim, Junwoo;Kim, Duk-jin;Sohn, Hong-Gyoo;Choi, Jinmu;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.38 no.5_2
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    • pp.661-667
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    • 2022
  • As remote sensing and GIS have been considered to be essential technologies for disasters information production, researches on developing methods for analyzing spatial data, and developing new technologies for such purposes, have been actively conducted. Especially, it is assumed that the use of remote sensing and GIS for disaster management will continue to develop thanks to the launch of recent satellite constellations, the use of various remote sensing platforms, the improvement of acquired data processing and storage capacity, and the advancement of artificial intelligence technology. This spatial issue presents 10 research papers regarding ship detection, building information extraction, ocean environment monitoring, flood monitoring, forest fire detection, and decision making using remote sensing and GIS technologies, which can be applied at the disaster prediction, monitoring and response stages. It is anticipated that the papers published in this special issue could be a valuable reference for developing technologies for disaster management and academic advancement of related fields.

Estimated groundwater recharge including water pipes leakage in Kumagaya City

  • Saito, Keisuke;Ogawa, Susumu;Takamura, Hiroki;Yashiro, Yusuke
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.735-737
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    • 2003
  • The drying up of seepage in Kumagaya City was caused by the increase of impermeable area with urbanization. The project of rain fall infiltration facilities has been planned for improvement of a hydrological cycle in Kumagaya City. With GIS and remote sensing, the most suitable arrangement for the rainfall infiltration inlets was examined. Distribution maps for infiltration, evapotranspiration and groundwater recharge at each town in Kumagaya City was designed from the land cover classification map with hydrological analysis. In these distribution maps, influence of the leak from drinking water and sewage networks was counted to the hydrological cycle.

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Study on Forest Vegetation Classification with Remote Sensing

  • Yuan, Jinguo;Long, Limin
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.250-255
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    • 2002
  • This paper describes the study methods of identifying forest vegetation types, based on this study, forest vegetation classification method based on vegetation index is proposed. According to reflectance data of vegetation canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun, China, many vegetation index are calculated and analyzed. The relationships between vegetation index and vegetation types are that PVI identifies broadleaf forest and conifer forest the most easily, the next is TSAVI and MSAVI, but their calculation is complex. RVI values of different conifer trees vary obviously, so RVI can classify conifer trees. In a word, combination of PVI and RVI is evaluated to classify different vegetation types.

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Merging of Satellite Remote Sensing and Environmental Stress Model for Ensuring Marine Safety

  • Yang, Chan-Su;Park, Young-Soo
    • Journal of Navigation and Port Research
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    • v.27 no.6
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    • pp.645-652
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    • 2003
  • A virtual vessel traffic control system is introduced to contribute to prevent a marine accident such as collision and stranding from happening. Existing VTS has its limit. The virtual vessel traffic control system consists of both data acquisition by satellite remote sensing and a simulation of traffic environment stress based on the satellite data, remotely sensed data And it could be used to provide timely and detailed information about the marine safety, including the location, speed and direction of ships, and help us operate vessels safely and efficiently. If environmental stress values are simulated for the ship information derived from satellite data, proper actions can be taken to prevent accidents. Since optical sensor has a high spatial resolution, JERS satellite data are used to track ships and extract their information. We present an algorithm of automatic identification of ship size and velocity. It lastly is shown that based on ship information extracted from JERS data, a qualitative evaluation method of environmental stress is introduced.