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http://dx.doi.org/10.7780/kjrs.2011.27.3.289

Sub-class Clustering of Land Cover over Asia considering 9-year NDVI and Climate Data  

Lee, Ga-Lam (Geoinformatic Engineering Research Institute, Pukyong National University)
Han, Kyung-Soo (Department of Spatial Information Engineering, Pukyong National University)
Kim, Do-Yong (BK21 Graduate School of Earth Environmental System, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.27, no.3, 2011 , pp. 289-301 More about this Journal
Abstract
In this paper an attempt has been made to classify Asia land cover considering climatic and vegetative characteristics. The sub-class clustering based on the 13 MODIS land cover classes (except water) over Asia was performed with the climate map and the NOVI derived from SPOT 5 VGT D10 data. The unsupervised classification for the sub-class clustering was performed in each land cover class, and total 74 clusters were determined over the study area. Via these clusters, the annual variations (from 1999 to 2007) of precipitation rate and temperature were analyzed as an example by a simple linear regression model. The various annual variations (negative or positive pattern) were represented for each cluster because of the various climate zones and NOVI annual cycles. Therefore, the detailed land cover map as the classification result by the sub-class clustering in this study can be useful information in modelling works for requiring the detailed climatic and vegetative information as a boundary condition.
Keywords
land cover; sub-class clustering; climate map; NOVI; SPOT VGT;
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1 Townshend, J. R. G., C. O. Justice, and V. Kalb, 1987. Characterization and classification of South American land cover types using satellite data, International Journal of Remote Sensing, 8(8): 1189-1207.   DOI   ScienceOn
2 Tucker, C. J., J. R. G. Townshend, and T. E. Goff, 1985. African land-cover classification using satellite data, Science, 227(4685): 369-375.   DOI
3 Vancutsem, C., J. F. Pekel, C. Evrard, F. Malaisse, and P. Defourny, 2009. Mapping and characterizing the vegetation types of the Democratic Republic of Congo using SPOT VEGETATION time series, International Journal of Applied Earth Observation and Geoinformation, 11(1): 62-76.   DOI
4 Verhoef, W., M. Menenti, and S. Azzali, 1996. Cover A colour composite of NOAA-AVHRR-NDVI based on time series analysis (1981-1992), International Journal of Remote Sensing, 17(2): 231-235.   DOI   ScienceOn
5 Yang, D., and K. Musiake, 2003. A continental scale hydrological model using the distributed approach and its application to Asia, Hydrological Processes, 17(14): 2855-2869.   DOI   ScienceOn
6 Loveland, T. R., J. W. Merchant, D. O. Ohlen, and J. F. Brown, 1991. Development of a land-cover characteristics database for the conterminous United States, Photogrammetric Engineering and Remote Sensing, 57(11): 1453-1463.
7 Melesse, A. M., and J. D. Jordan, 2002. A comparison of fuzzy vs. augmented-ISODATA classification algorithms for cloud-shadow discrimination from Landsat images, Photogrammetric Engineering and Remote Sensing, 68(9): 905-911.
8 Pasqualini, V., C. Pergent-Martini, G. Pergent, M. Agreil, G. Skoufas, L. Sourbes, and A. Tsirika, 2005. Use of SPOT 5 for mapping seagrasses: An application to Posidonia oceanica, Remote Sensing of Environment, 94(1): 39-45.   DOI   ScienceOn
9 Park, Y. Y., K. S. Han, J. M. Yeom, and Y. C. Suh, 2006. An Adjustment for a Regional Incongruity in Global Land Cover Map: case of Korea, Korean Journal of Remote Sensing, 22(3): 1-11   DOI
10 Sandholt, I., J. Andersen, G. Dybkjaer, M. Lo, K. Rasmussen, J. C. Refsgaard, and K. H. Jensen, 1999. Use of remote sensing data in distributed hydrological models: applications in the Senegal River basin, Danish Journal of Geography, 99: 47-57.   DOI
11 Stroppiana, D., J. M. Grégoire, and J. M. C. Pereira, 2003. The use of SPOT VEGETATION data in a classification tree approach for burnt area mapping in Australian savanna, International Journal of Remote Sensing, 24(10): 2131- 2151.   DOI   ScienceOn
12 Stibig, H. J., F. Achard, and S. Fritz, 2004. A new forest cover map of continental Southeast Asia derived from SPOT-VEGETATION satellite imagery, Applied Vegetation Science, 7(2): 153-162.   DOI   ScienceOn
13 Stibig, H. J., A. S. Belward, P. S. Roy, U. Rosalina- Wasrin, S. Agrawal, P. K. Joshi, R. Beuchle, S. Fritz, S. Mubareka, and C. Giri, 2007. A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data, Journal of Biogeography, 34(4): 625-637.   DOI   ScienceOn
14 Stone, T. A., P. Schlesinger, R. A. Houghton, and G. M. Woodwell, 1994. A map of the vegetation of South America based on satellite imagery, Photogrammetric Engineering and Remote Sensing, 60(5): 541-551.
15 Tou, J. T., and R. C. Gonzalez, 1974. Isodata algorithm, Pattern Classification by Distance Functions, Pattern recognition principles, Addison-Wesley, Reading, Massachusetts.
16 Jang, J. D., 2006. Rural Land Cover Classification using Multispectral Image and LIDAR Data, Korean Journal of Remote Sensing, 22(2): 101-110.   DOI
17 Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, R. Jenne, and D. Joseph, 1996. The NCEP/NCAR 40-year reanalysis project, Bulletin of the American Meteorological Society, 77(3): 437-471.   DOI
18 Kim, D. H., S. G. Jeong, and C. H. Park, 2007. Comparison of Three Land Cover Classification Algorithms - ISODATA, SMA, and SOM - for the Monitoring of North Korea with MODIS Multi-temporal Data, Korean Journal of Remote Sensing, 23(3): 181-188.   DOI
19 Kimball, J. S., S. W. Running, and S. S. Saatchi, 1999. Sensitivity of boreal forest regional water flux and net primary production simulations to sub-grid-scale land cover complexity, Journal of Geophysical Research-Atmospheres, 104(D22): 27789-27801.   DOI
20 Kistler, R., E. Kalnay, W. Collins, S. Saha, G. White, J. Woollen, M. Chelliah, W. Ebisuzaki, M. Kanamitsu, V. Kousky, H. van den Dool, R. Jenne, and M. Fiorino, 2001. The NCEP-NCAR 50-year reanalysis: Monthly means CD-ROM and documentation, Bulletin of the American Meteorological Society, 82(2): 247-267.   DOI   ScienceOn
21 Koeppe, C. E., and G. C. De Long, 1958. Weather and climate, McGraw-Hill, 341.
22 Latifovic, R., and I. Olthof, 2004. Accuracy assessment using sub-pixel fractional error matrices of global land cover products derived from satellite data, Remote Sensing of Environment, 90(2): 153-165.   DOI   ScienceOn
23 Lee, K. S., Y. S. Yoon, S. H. Kim, J. I. Shin, J. S. Yoon, and S. J. Kang, 2009. Analysis of Present Status for the Monitoring of Land Use and Land Cover in the Korean Peninsula, Korean Journal of Remote Sensing, 25(1): 71- 83.   DOI
24 Liu, J., J. M. Chen, J. Cihlar, and W. Chen, 2002. Net primary productivity mapped for Canada at 1- km resolution, Global Ecology & Biogeography, 11(2): 115-129.   DOI   ScienceOn
25 Lotsch, A., Y. Tian, M. A. Friedl, and R. B. Myneni, 2003. Land cover mapping in support of LAI and FPAR retrievals from EOS-MODIS and MISR: classification methods and sensitivities to errors, International Journal of Remote Sensing, 24(10): 1997-2016.   DOI   ScienceOn
26 Friedl, M. A., D. K. McIver, J. C. F. Hodges, X. Y. Zhang, D. Muchoney, A. H. Strahler, C. E. Woodcock, S. Gopal, A. Schneider, A. Cooper, A. Baccini, F. Gao, and C. Schaaf, 2002. Global land cover mapping from MODIS: algorithms and early results, Remote Sensing of Environment, 83(1-2): 287-302.   DOI   ScienceOn
27 Fuller, D. O., and C. Ottke, 2002. Land cover, rainfall and land-surface albedo in West Africa, Climatic Change, 54(1-2): 181-204.   DOI
28 Hagolle, O., A. Lobo, P. Maisongrande, F. Cabot, B. Duchemin, and A. De Pereyra, 2004. Quality assessment and improvement of temporally composited products of remotely sensed imagery by combination of VEGETATION 1 and 2 images, Remote Sensing of Environment, 94(2): 172-186.   DOI
29 Han, K. S., J. L. Champeaux, and J. L. Roujean, 2004. A land cover classification product over France at 1 km resolution using SPOT4/ VEGETATION data, Remote Sensing of Environment, 92(1): 52-66.   DOI   ScienceOn
30 Hansen, M. C., R. S. DeFries, J. R. G. Townshend, and?R. Sohlberg, 2000. Global land cover classification at 1km spatial resolution using a classification tree approach, International Journal of Remote Sensing, 21(6-7): 1331-1364.   DOI   ScienceOn
31 Hansen, M. C., R. S. DeFries, J. R. G. Townshend, R. Sohlberg, C. Dimiceli, and M. Carroll, 2002. Towards an operational MODIS continuous field of percent tree cover algorithm: examples using AVHRR and MODIS data, Remote Sensing of Environment, 83(1-2): 303-319.   DOI
32 Huang, S., and F. Siegert, 2006. Land cover classification optimized to detect areas at risk of desertification in North China based on SPOT VEGETATION imagery, Journal of Arid Environments, 67(2): 308-327.   DOI   ScienceOn
33 Inoue, Y., and A. Olioso, 2004. Synergistic linkage between remote sensing and biophysical models for estimating plant ecophysiological and ecosystem processes, Journal of the Remote Sensing Society of Japan, 24(1): 1-17.
34 Intergovernmental Panel on Climate Change (IPCC), 2007. Climate Change 2007, The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the IPCC, Cambridge University Press, 996.
35 Irvin, B. J., S. J. Ventura, and B. K. Slater, 1997. Fuzzy and isodata classification of landform elements from digital terrain data in Pleasant Valley, Wisconsin. Geoderma, 77(2-4): 137-154.   DOI   ScienceOn
36 Champeaux, J. L., K. S. Han, and V. Masson, 2004. ECOCLIMAP II: A future Global Surface Parameters Database using SPOT/VEGETATION data and the GLC2000 product, 2nd VEGETATION International Users Conference, 2046-2049
37 Chase, T. N., R. A. Pielke Sr., T. G. F. Kittel, R. R. Nemani, and S. W. Running, 2000. Simulated impacts of historical land cover changes on global climate in northern winter, Climate Dynamics, 16(2-3): 93-105.   DOI   ScienceOn
38 Cihlar, J., Q. Xiao, J. Chen, J. Beaubien, K. Fung, and R. Latifovic, 1998. Classification by progressive generalization: a new automated methodology for remote sensing multichannel data, International Journal of Remote Sensing, 19(14): 2685-2704.   DOI   ScienceOn
39 DeFries, R. S., and J. R. G. Townshend, 1994a. Global land cover: comparison of groundbased data sets to classifications with AVHRR data, In Environmental Remote Sensing from Regional to Global Scales, edited by G. Foody and P. Curran (Chichester: Wiley).
40 Clark, D. B., Y. Xue, R. J. Harding, and P. J. Valdes, 2001. Modeling the impact of land surface degradation on the climate of tropical North Africa, Journal of Climate, 14(8): 1809-1822.   DOI   ScienceOn
41 DeFries, R. S., and J. R. G. Townshend, 1994b. NDVI-derived land cover classifications at a global scale, International Journal of Remote Sensing, 15(17): 3567-3586.   DOI   ScienceOn
42 DeFries, R. S., M. Hansen, and J. R. G. Townshend, 1995. Global discrimination of land cover types from metrics derived from AVHRR pathfinder data, Remote Sensing of Environment, 54(3): 209-222.   DOI
43 DeFries, R. S., M. Hansen, J. R. G. Townshend, and R. Sohlberg, 1998. Global land cover classifications at 8 km spatial resolution: the use of training data derived from Landsat imagery in decision tree classifiers, International Journal of Remote Sensing, 19(16): 3141-3168.   DOI   ScienceOn
44 Dickinson, R. E., 1995. Land processes in climate models, Remote Sensing of Environment, 51(1): 27-38.   DOI   ScienceOn
45 Droogers, P., and G. Kite, 2002. Remotely sensed data used for modelling at different hydrological scales, Hydrological Processes, 16(8): 1543-1556.   DOI   ScienceOn
46 Duchemin, B., and P. Maisongrande, 2002. Normalisation of directional effects in 10-day global syntheses derived from VEGETATION/ SPOT: I. Investigation of concepts based on simulation, Remote Sensing of Environment, 81(1): 90-100.   DOI   ScienceOn
47 Cabral, A. I. R., M. J. P. De Vasconcelos, J. M. C. Pereira, É. Bartholomé, and P. Mayaux, 2003. Multi-temporal compositing approaches for SPOT-4 VEGETATION, International Journal of Remote Sensing, 24(16): 3343-3350.   DOI   ScienceOn
48 Bartalev, S. A., A. S. Belward, D. V. Erchov, and A. S. Isaev, 2003. A new SPOT4-VEGETATION derived land cover map of Northern Eurasia, International Journal of Remote Sensing, 24(9): 1977-1982.?   DOI   ScienceOn
49 Boles, S., X. Xiao, J. Liu, Q. Zhang, S. Munkhtuya, S. Chen, and D. Ojima, 2004. Land cover characterization of Temperate East Asia using multi-temporal VEGETATION sensor data, Remote Sensing of Environment, 90(4): 477-489.   DOI   ScienceOn
50 Bounoua, L., R. DeFries, G. J. Collatz, P. Sellers, and H. Khan, 2002. Effects of land cover conversion on surface climate, Climatic Change, 52(1-2): 29-64.   DOI
51 Cabral, A. I. R., M. J. P. Vasconcelos, J. M. C. Pereira, E. Martins, and É. Bartholomé, 2006. A land cover map of southern hemisphere Africa based on SPOT-4 Vegetation data, International Journal of Remote Sensing, 27(6): 1053-1074.   DOI   ScienceOn
52 Champeaux, J. L., D. Arcos, E. Bazile, D. Giard, J. P. Goutorbe, F. Habets, J. Noilhan, and J. L. Roujean, 2000. AVHRR-derived vegetation mapping over Western Europe for use in Numerical Weather Prediction models, International Journal of Remote Sensing, 21 (6-7): 1183-1199.   DOI   ScienceOn