지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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초록· 키워드
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The GOSAT (Greenhouse gases Observing SATellite) data provide new opportunities the most regionally complete and up-to-date assessment of CO_2. However, in practice, GOSAT records often suffer from missing data values mainly due to unfavorable meteorological condition in specific time periods of data acquisition. The aim of this research was to identify optimal spatial interpolation techniques to ensure the continuity of CO_2 from samples taken in the North East Asia. The accuracy among ordinary kriging (OK), universal kriging (UK) and simple kriging (SK) was compared based on the combined consideration of R^2 values, Root Mean Square Error (RMSE), Mean Error (ME) for variogram models. Cross validation for 1312random sampling points indicate that the (UK) kriging is the best geostatistical method for spatial predictions of CO_2 in the East Asia region. The results from this study can be useful for selecting optimal kriging algorithm to produce CO_2 map of various landscapes. Also, data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the GOSAT sample data.
목차
등록된 정보가 없습니다.
참고문헌 (21)
참고문헌 신청
Coulibaly L. / 2008 / Mapping aboveground forest biomass from IKONOS satellite image and multisource geospatial data using neural networks and a kriging interpolation / Geoscience
Florio E. N. / 2004 / Integrating AVHRR satellite data and NOAA ground observations to predict surface air temperature:a statistical approach / International Journal of Remo
Isaaks E.H. / 1989 / Applied Geosatistics / Oxford University Press
Kuze A. / 2006 / The Instrumentation and the BBM test results of thermal and near-infrared sensor for carbon observation(TANSO) on GOSAT / Infrared Spaceborne Remote Sensing
Kuze A. / 2009 / Thermal and near infrared sensor for carbon observation fouriertransform spectrometer on the greenhouse gases observing satellite for greenhouse gases monit
Florio E. N. / 2004 / Integrating AVHRR satellite data and NOAA ground observations to predict surface air temperature:a statistical approach / International Journal of Remo
Isaaks E.H. / 1989 / Applied Geosatistics / Oxford University Press
Kuze A. / 2006 / The Instrumentation and the BBM test results of thermal and near-infrared sensor for carbon observation(TANSO) on GOSAT / Infrared Spaceborne Remote Sensing
Kuze A. / 2009 / Thermal and near infrared sensor for carbon observation fouriertransform spectrometer on the greenhouse gases observing satellite for greenhouse gases monit
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