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http://dx.doi.org/10.7780/kjrs.2018.34.6.1.3

A Long-term Variability of the Extent of East Asian Desert  

Han, Hyeon-Gyeong (Department of Spatial Information Engineering, Pukyong National University)
Lee, Eunkyung (Department of Spatial Information Engineering, Pukyong National University)
Son, Sanghun (Department of Spatial Information Engineering, Pukyong National University)
Choi, Sungwon (Department of Spatial Information Engineering, Pukyong National University)
Lee, Kyeong-Sang (Department of Spatial Information Engineering, Pukyong National University)
Seo, Minji (Department of Spatial Information Engineering, Pukyong National University)
Jin, Donghyun (Department of Spatial Information Engineering, Pukyong National University)
Kim, Honghee (Department of Spatial Information Engineering, Pukyong National University)
Kwon, Chaeyoung (National Disaster Management Research Institute)
Lee, Darae (Korea Hydrographic and oceanographic agency)
Han, Kyung-Soo (Department of Spatial Information Engineering, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.34, no.6_1, 2018 , pp. 869-877 More about this Journal
Abstract
The area of desert in East Asia is increasing every year, and it cause a great cost of social damage. Because desert is widely distributed and it is difficult to approach people, remote sensing using satellites is commonly used. But the study of desert area comparison is insufficient which is calculated by satellite sensor. It is important to recognize the characteristics of the desert area data that are calculated for each sensor because the desert area calculated according to the selection of the sensor may be different and may affect the climate prediction and desertification prevention measures. In this study, the desert area of Northeast Asia in 2001-2013 was calculated and compared using Moderate Resolution Imaging Spectroradiometer (MODIS) and Vegetation. As a result of the comparison, the desert area of Vegetation increased by $3,020km^2/year$, while in the case of MODIS, it decreased by $20,911km^2/year$. We performed indirect validation because It is difficult to obtain actual data. We analyzed the correlation with the occurrence frequency of Asian dust affected by desert area change. As a result, MODIS showed a relatively low correlation with R = 0.2071 and Vegetation had a relatively high correlation with R = 0.4837. It is considered that Vegetation performed more accurate desert area calculation in Northeast Asian desert area.
Keywords
SPOT/Vegetation; MODIS; Desert Extent; Asian dust frequency;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Tucker, C.J., H.E. Dregne, and W.W. Newcomb, 1991. Expansion and contraction of the Sahara Desert from 1980 to 1990, Science, 253(5017): 299-300.   DOI
2 Yeom, J.M., K.S. Han, and Y.S. Kim, 2006. Identification of Contaminated Pixels in 10-day NDVI Image, Proc. of the Korean Society of Remote Sensing Spring Conference, Dae-Jeon, Mar. 31, vol. 16(2), pp. 113-116.
3 Zhou, L., C.J. Tucker, R.K. Kaufmanl, D. Slaybac, N.V. Shabanov, and R.B. Myneni, 2001. Variations in northern Vegetation activity inferred from satellite data of vegetation index during 1981 to 1999, Journal of Geophysical Research: Atmospheres, 106(D17): 20069-20083.   DOI
4 Ceccato, P., 2004. Operational Early Warning System Using SPOT-VGT and TERRA-MODIS to Predict Desert Locust Outbreaks, Proc. of the Second International SPOT-VEGETATION Users Conference, Antwerp, Belgium, Mar. 24-26. pp. 66-76.
5 Giri, C., Z. Zhu, and B. Reed, 2005. A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets, Remote Sensing of Environment, 94(1): 123-132.   DOI
6 Choi, B.G., Y.W. Na, and T.H. Kim, 2010. Detection of land cover change using Landsat image data in desert area, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 28(4): 471-476 (in Korean with English abstract).
7 Erdenechimeg, M., B.G. Choi, Y.W. Na, and T.H. Kim, 2010. Detection of Land Cove Change Using Landsat Image Data in Desert Area, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 28(4): 471-476 (in Korean with English abstract).
8 Friedl, M.A., D.S. Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley, and X. Huang, 2010. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets, Remote Sensing of Environment, 114(1): 168-182.   DOI
9 Holben, B.N., 1986. Characteristics of maximum-value composite images from temporal AVHRR data, International Journal of Remote Sensing, 7(11): 1417-1434.   DOI
10 Husar, R.B., D.M. Tratt, B.A. Schichtel, S.R. Falke, F. Li, D. Jaffe, S. Gasso, T. Gill, N.S. Laulainens, F. Lu, M.C. Reheis, Y. Chun, D. Westphal, B.N. Holben, C. Gueymard, I. McKendry, N. Kuring, G.C. Feldman, C. McClain, R.J. Frouin, J. Merrill, D. DuBois, F. Vignola, T. Murayama, S. Nickovic, W.E. Wilson, K. Sassen, N. Sugimoto, and W.C. Malm, 2001. Asian dust events of April 1998, Journal of Geophysical Research: Atmospheres, 106(D16): 18317-18330.   DOI
11 Iwasa, Y., 2000. The geometry of ecological interactions: simplifying spatial complexity, Cambridge University Press, Cambridge, UK.
12 Kang, S.K., 2012. Climatic and Socio-ecological Considerations on Yellow Dust and Desertification in Dryland Regions of the Northeast Asia, Korean Journal of Nature Conservation, 6(1): 1-8 (in Korean with English abstract).
13 Park, J.Y. and M.S. Suh, 2014. Characteristics of MODIS land-cover data sets over Northeast Asia for the recent 12 years(2001-2012), Korean Journal of Remote Sensing, 30(4): 511-524 (in Korean with English abstract).   DOI
14 Jo, M.H., 2012. A Study on the Extraction of a River from the Rapid Eye Image Using ISODATA Algorithm, Journal of the Korean Association of Geographic Information Studies, 15(4): 1-14 (in Korean with English abstract).   DOI
15 Kang, K.G., J.M. Chu, H.S. Jung, H.J. Han, and N.M. Yoo, 2004. Study on the Analysis of Damages from the Northeast Asian Dust and Sand Storm and the Regional Cooperation Strategies, Korea Environment Institute, Sejong, Korea.
16 Kim, D.W., 2013. Current Status and Outlook of Yellow Sand Spring in 2013, National Disaster Management Research Institute, Ulsan, Korea.
17 Kim, G.S., 1992. Encyclopedia of meteorology, Hyangmunsa, Seoul, Korea.
18 Lee, K.W., 2005. The Land Use Change and the Desertification in the East Inner Mongolia, China - A Case Study on Horqin Desert, The Korea Geographical Society, 40(6): 694-715 (in Korean with English abstract).
19 Kim, S.Y. and S.H. Lee, 2009. The Study on Occurrence of Asian Dust and Their Controlling Factors in Korea, The Korea Geographical Society, 40(6): 675-690 (in Korean with English abstract).
20 Klein, I., U. Gessner, and C. Kuenzer, 2012. Regional land cover mapping and change detection in Central Asia using MODIS time-series, Applied Geography, 35(1-2): 219-234.   DOI
21 Park, I.S., 1995. Desertification and prevention measures in China, Korea Research Institute for Human Settlements for Planning and Policy, 167: 98-101.
22 Strahler, A., D. Muchoney, J. Borak, M. Friedl, S. Gopal, E. Lambin, and A. Moody, 1999. MODIS Land Cover Product Algorithm Theoretical Basis Document (ATBD) Version 5.0 for MODIS Land Cover and Land-Cover Change, NASA, Washington, D.C., USA.
23 Phiri, D. and J. Morgenroth, 2017. Developments in Landsat land cover classification methods: A review, Remote Sensing, 9(9): 967.   DOI
24 Pi, J.J., K.S. Han, and S.J. Park, 2009. A Comparative Analysis of Land Cover Changes Among Different Source Regions of Dust Emission in East Asia: Gobi Desert and Manchuria, Korean Journal of Remote Sensing, 25(2): 175-184 (in Korean with English abstract).   DOI
25 Safriel, U. and Z. Adeel, 2008. Development paths of drylands: thresholds and sustainability, Sustainability Science, 3(1): 117-123.   DOI