2012
DOI: 10.7780/kjrs.2012.28.2.215
|View full text |Cite
|
Sign up to set email alerts
|

The Estimation of Gross Primary Productivity over North Korea Using MODIS FPAR and WRF Meteorological Data

Abstract: : NASA MODIS GPP provides a useful tool to monitor global terrestrial vegetation productivity. Two major problems of NASA GPP in regional applications are coarse spatial resolution (1.25˚ 1˚) of DAO meteorological data and cloud contamination of MODIS FPAR product. In this study, we improved the NASA GPP by using enhanced input data of high spatial resolution (3 km 3 km) WRF meteorological data and cloud-corrected FPAR over the North Korea. ), FPAR enhancement increased GPP (861) but utilization of WRF data de… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
1
0
1

Year Published

2014
2014
2015
2015

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 18 publications
0
1
0
1
Order By: Relevance
“…The MODIS07_L2 atmosphere profiles product covers the entire globe at 1-2 day intervals, and produces various atmosphere variables, including T a , at 5 km spatial resolution. The temperature variables derived from MODIS07_L2 product have been widely used to estimate surface radiation budget parameters, evapotranspiration, and plant productivity in previous applications [31][32][33][34][35][36][37][38]. However, the MODIS IR and temperature retrievals are significantly degraded by atmosphere aerosol, smoke and cloud cover contamination, which hampers terrestrial monitoring applications.…”
Section: Introductionmentioning
confidence: 99%
“…The MODIS07_L2 atmosphere profiles product covers the entire globe at 1-2 day intervals, and produces various atmosphere variables, including T a , at 5 km spatial resolution. The temperature variables derived from MODIS07_L2 product have been widely used to estimate surface radiation budget parameters, evapotranspiration, and plant productivity in previous applications [31][32][33][34][35][36][37][38]. However, the MODIS IR and temperature retrievals are significantly degraded by atmosphere aerosol, smoke and cloud cover contamination, which hampers terrestrial monitoring applications.…”
Section: Introductionmentioning
confidence: 99%
“…(Seemann et al, 2006;Borbas et al, 2011). MODIS 로부터 생산된 기온과 이슬점온도 프로파일 정보는 지 표 수준의 미기상 요소 추정연구 (Urban et al, 2013;Hill, 2013;Rhee and Im, 2014;Williamson et al, 2014), 대기의 연직구조 및 안정도 연구 (Park et al, 2006;Kim and Kwon, 2007;Mitra et al, 2012), 지표복사수지 산출 (Bisht et al, Korean Journal of Remote Sensing, Vol.30, No.5, 2014 -5 72- 2005; Ryu et al, 2008;Jang et al, 2009;Bisht and Bras, 2010), 육상 증발산 추정 (Batra et al, 2006;Jeong et al, 2009;Jang et al, 2010;Jang et al, 2013) 및 식생 일차생 산성 추정연구 (Lee et al, 2011;Ryu et al, 2011;Do et al, 2012 …”
Section: 서 론unclassified