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Status of Rice Paddy Field and Weather Anomaly in the Spring of 2015 in DPRK
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 Title & Authors
Status of Rice Paddy Field and Weather Anomaly in the Spring of 2015 in DPRK
Hong, Suk Young; Park, Hye-Jin; Jang, Keunchang; Na, Sang-Il; Baek, Shin-Chul; Lee, Kyung-Do; Ahn, Joong-Bae;
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 Abstract
To understand the impact of 2015 spring drought on crop production of DPRK (Democratic People's Republic of Korea), we analyzed satellite and weather data to produce 2015 spring outlook of rice paddy field and rice growth in relation to weather anomaly. We defined anomaly of 2015 for weather and NDVI in comparison to past 5 year-average data. Weather anomaly layers for rainfall and mean temperature were calculated based on 27 weather station data. Rainfall in late April, early May, and late May in 2015 was much lower than those in average years. NDVI values as an indicator of rice growth in early June of 2015 was much lower than in 2014 and the average years. RapidEye and Radarsat-2 images were used to monitor status of rice paddy irrigation and transplanting. Due to rainfall shortage from late April to May, rice paddy irrigation was not favorable and rice planting was not progressed in large portion of paddy fields until early June near Pyongyang. Satellite images taken in late June showed rice paddy fields which were not irrigated until early June were flooded, assuming that rice was transplanted after rainfall in June. Weather and NDVI anomaly data in regular basis and timely acquired satellite data can be useful for grasping the crop and land status of DPRK, which is in high demand.
 Keywords
Remote Sensing;Rice paddy;NDVI;Anomaly;North Korea;
 Language
Korean
 Cited by
1.
Estimation of Highland Kimchi Cabbage Growth using UAV NDVI and Agro-meteorological Factors, Korean Journal of Soil Science and Fertilizer, 2016, 49, 5, 420  crossref(new windwow)
 References
1.
Ahn, J.B., C.K. Park, and E.S. Im, 2002. Reproduction of regional scale surface air temperature by estimating systematic bias of mesoscale numerical model, J. Kor. Meteo. Soc. 38(1):69-80.

2.
Ahn, J.B., J.N. Hur, K.M. Shim, 2010. A simulation of agroclimate index over the Korean peninsula using dynamical downscaling with a numerical weather prediction. Kor. J. Agr. Forest Meteo. 12(1):1-10. crossref(new window)

3.
Barnes, S., 1964. A technique for maximizing details in numerical weather map analysis, J. Appl. Meteor. 9(3); 396-409.

4.
Cho, S.H., S.J. Kwon, Y.E. Song, D.R. Lee, and Y.J. Song, 2013. Optimum transplanting time for improving the rice quality in Jeonbuk Plain Area. Research report of Jeollabukdo Agricultural Research and Extension Services. Iksan, Jeollabukdo.

5.
FAO Global Information and Early Warning System on Food and Agriculture (GIEW), http://www.fao.org/giews/english/index.htm.

6.
Ham, J.K., Y.B. Kim, J.K. Choi, B.S. Kim, and M.W. Kim, 2001. Impact of drought which causes delay of transplanting on rice growth and yield, Research report of Gangwondo Agricultural Research and Extension Services. Chuncheon, Gangwondo.

7.
Hong, S.Y., S.K. Rim, S.H. Lee, J.C. Lee, and Y.H. Kim. 2008. Spatial analysis of agro-environment of North Korea using remote sensing I. landcover classification from Landsat TM imagery and topography analysis in North Korea. Korean J. Environ. Agric. 27(2):120-132. (In Korean) crossref(new window)

8.
Hong, S.Y., E.Y. Choe, G.Y. Kim, S.K. Kang, Y.H. Kim, and Y.S. Zhang. 2009. A study on estimating rice yield of North Korea using MODIS NDVI. Proc. of the KSRS Conf.. pp.116-120. (In Korean)

9.
Hong, S.Y., B.K. Min, J.M. Lee, Y.H. Kim, and K.D. Lee. 2012a. Estimation of paddy field area in North Korea Using RapidEye Images. Korea. J. Soil Sci. Fert. 45(6):1194-1202. (In Korean) crossref(new window)

10.
Hong, S.Y., J.N. Hur, J.B. Ahn, J.M. Lee, B.K. Min, C.K. Lee, Y.H. Kim, K.D. Lee, S.H. Kim, G.Y. Kim, and K.M. Shim. 2012b. Estimating rice yield using MODIS NDVI and meteorological data in Korea. Kor. J. Remote Sens. 28(5):509-520. (In Korean) crossref(new window)

11.
Joint Research Center "Seasonal Monitoring in DPRK 2014". http://mars.jrc.ec.europa.eu/mars/content/download/3496/17 312/file/JRC_report_DPRK_crop_season_assessment_September2014.pdf

12.
Jordan, C.F.. 1969. Derivation of leaf area index from quality of light on the forest floor. Ecology. 50:663-666. crossref(new window)

13.
National Climate Data Service System, http://sts.kma.go.kr/jsp/home/contents /main/main.do

14.
Penning de Vries, F.W.T., D.M. Jansen, H.F.M. ten Berge and A. Bakema, 1989. Simulation of ecophysical processes of growth in several annual crops. Pudoc Wageningen, Wageningen, The Netherlands. pp.6-8.

15.
RDA, 2010. Crop management countermeasure coping with unusual weather conditions. http://www.rda.go.kr

16.
RDA, 2011. Preprocess Program for MODIS satellite images. Program Registration No. 2011-01-189-012198 (2011.12. 28.)

17.
Rouse, J.W, R.H. Haas, J.A. Schell. and D.W. Deering. 1973. Monitoring vegetation systems in the great plains with ETRA. In third ETRS Symposium, NASA SP-353. U.S. Govt. Printing Office, Washington D.C. Vol. 1:309-317.

18.
USDA FAS, http://www.pecad.fas.usda.gov/highlights/2015/07/northkorea/index.htm

19.
USGS Data Pool. http://lpdaac.usgs.gov/ data_access/data_pool