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Original Articles

A logistic-based method for rice monitoring from multitemporal MODIS-Landsat fusion data

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Pages 39-56 | Received 07 Jul 2015, Accepted 11 Jan 2016, Published online: 17 Feb 2017

References

  • Bartoszek K., Siluch M., Bednarczyk P. (2015)—Characteristics of the onset of the growing season in Poland based on the application of remotely sensed data in the context of weather conditions and land cover types. European Journal of Remote Sensing, 48: 327–344. doi: http://dx.doi.org/10.5721/EuJRS20154819.
  • Beck P.S.A., Atzberger C., HØgda K.A., Johansen B., Skidmore A.K. (2006)—Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI. Remote Sensing of Environment, 100: 321–334. doi: http://dx.doi.org/10.1016/j.rse.2005.10.021.
  • Chen C.F., Huang S.-W., Son N.-T., Chang L.-Y. (2011)—Mapping double-cropped irrigated rice fields in Taiwan using time-series Satellite Pour I'Observation de la Terre data. Journal of Applied Remote Sensing, 5: 053528–053528. doi: http://dx.doi.org/10.1117/1.3595276.
  • Chen X., Vierling L., Deering D. (2005)—A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of Environment, 98: 63–79. doi: http://dx.doi.org/10.1016/j.rse.2005.05.021.
  • Evenson R.E., Rosegrant M. (2003)—The economic consequences of crop genetic: Improvement programmes. Crop varietal improvement and its effects on productivity: The impact of international agricultural research. CABI Publishing, CAB International, Wallingford, UK. doi: http://dx.doi.org/10.1079/9780851995496.0000.
  • Fangping D., Gaoli S., Chuang L. (2007)—Seasonal variation of MODIS vegetation indexes and their statistical relationship with climate over the subtropic evergreen forest in Zhejiang, China. IEEE Geoscience and Remote Sensing Letters, 4: 236–240. doi: http://dx.doi.org/10.1109/LGRS.2006.888844.
  • FAO (2010)—Food outlook: global market analysis. Food and Agriculture Organization of the United Nations, Rome, Italy.
  • Feng G., Masek J., Schwaller M., Hall F. (2006)—On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance. IEEE Transactions on Geoscience and Remote Sensing, 44: 2207–2218. doi: http://dx.doi.org/10.1109/TGRS.2006.872081.
  • Gaulton R., Hilker T., Wulder M.A., Coops N.C., Stenhouse G. (2011)—Characterizing stand-replacing disturbance in western Alberta grizzly bear habitat, using a satellite- derived high temporal and spatial resolution change sequence. Forest Ecology and Management, 261: 865–877. doi: http://dx.doi.org/10.1016/j.foreco.2010.12.020.
  • GSO (2010)—Statistical yearbook of Vietnam. General Statistics Office of Vietnam, Vietnam.
  • Gumma M.K., Thenkabail P.S., Maunahan A., Islam S., Nelson A. (2014)—Mapping seasonal rice cropland extent and area in the high cropping intensity environment of Bangladesh using MODIS 500 m data for the year 2010. ISPRS Journal of Photogrammetry and Remote Sensing, 91: 98–113. doi: http://dx.doi.org/10.1016/j.isprsjprs.2014.02.007.
  • Hilker T., Wulder, M.A., Coops N.C., Seitz N., White J.C., Gao, F., Masek J.G., Stenhouse G. (2009)—Generation of dense time series synthetic Landsat data through data blending with MODIS using a spatial and temporal adaptive reflectance fusion model. Remote Sensing of Environment, 113: 1988–1999. doi: http://dx.doi.org/10.1016/j.rse.2009.05.011.
  • Hossain M. (1997)—Rice supply and demand in Asia: A socioeconomic and biophysical analysis. In: Applications of systems approaches at the farm and regional levels. Kluwer Academic Publishers, Dordrecht, Netherlands. doi: http://dx.doi.org/10.1007/978-94-011-5416-1_20.
  • Intergovernmental Panel on Climate Change (2007)—Climate change: AR4 synthesis report. Cambridge University Press.
  • Jiang Z., Huete A.R., Didan K., Miura T. (2008)—Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment, 112: 3833–3845. doi: http://dx.doi.org/10.1016/j.rse.2008.06.006.
  • Julien Y., Sobrino J.A. (2009)—Global land surface phenology trends from GIMMS database. International Journal of Remote Sensing, 30: 3495–3513. doi: http://dx.doi.org/10.1080/01431160802562255.
  • Le Trong H. (2012)—The rice situation in Vietnam. Asian Development Bank, Manila, Philippines.
  • Mackay P., Russell M. (2011)—Socialist Republic of Viet Nam: Climate change impact and adaptation study in the Mekong Delta. Asian Development Bank, Manila, Philippines.
  • Maclean J.L., Dawe D.C., Hardy B., Hettel G.P. (2002)—Rice almanac: Source book for the most important economic activity on earth. CABI Publishing, Wallingford, UK.
  • Nguyen V.N., Do M.H., Nguyen N.A., Le V.K. (2004)—Rice production in the Mekong delta (Vietnam): Trends of development and diversification. Mekong Rice Conference 2004: Rice the Environment, and Livelihoods for the Poor, Ho Chi Minh City, Vietnam, pp. 15–17.
  • Pandey S., Byerlee D., Dawe D., Dobermann A., Mohanty S., Rozelle S., Hardy B. (2010)—Rice in the global economy: Strategic research and policy issues for food security. International Rice Research Institute, Phillipines.
  • Richards J.A., Jia X. (2006)—Remote sensing digital image analysis: An Introduction. Springer-Verlag, New York, USA.
  • Schmidt M., Lucas R., Bunting P., Verbesselt J., Armston J. (2015)—Multi-resolution time series imagery for forest disturbance and regrowth monitoring in Queensland, Australia. Remote Sensing of Environment, 158: 156–168. doi: http://dx.doi.org/10.1016/j.rse.2014.11.015.
  • Schmidt M., Udelhoven T., Gill T., Röder A. (2012)—Long term data fusion for a dense time series analysis with MODIS and Landsat imagery in an Australian Savanna. Journal of Applied Remote Sensing, 6: 063512-063511-063512-063518.
  • Son N.-T., Chen C.-F., Chen C.-R., Duc H.-N., Chang L.-Y. (2013)—A phenology-based classification of time-series MODIS data for rice crop monitoring in Mekong Delta, Vietnam. Remote Sensing, 6: 135–156. doi: http://dx.doi.org/10.3390/rs6010135.
  • Sub-NIAPP (2002)—Land-use map of the Mekong Delta. The Sub-National Institute for Agricultural Planning and Projection, Ho Chi Minh City, Vietnam.
  • Timmer C.P. (2009)—A world without agriculture: The structural transformation in historical perspective. American Enterprise Institute, Washington DC, USA.
  • Tornos L., Huesca M., Dominguez J.A., Moyano M.C., Cicuendez V., Recuero L., Palacios- Orueta A. (2015)—Assessment of MODIS spectral indices for determining rice paddy agricultural practices and hydroperiod. ISPRS Journal of Photogrammetry and Remote Sensing, 101: 110–124. doi: http://dx.doi.org/10.1016/j.isprsjprs.2014.12.006.
  • USDA (2012)—Vietnam: Record rice production forecast on surge in planting in Mekong Delta. United States Department of Agriculture, USA.
  • Vermote E.F., Kotchenova S.Y., Ray J.P. (2008)—MODIS surface reflectance user's guide. NASA GSFC Terrestrial Information Systems Laboratory, Greenbelt, MD 20771, USA.
  • Wardlow B.D., Kastens J.H., Egbert S.L. (2006)—Using USDA crop progress data for the evaluation of greenup onset date calculated from MODIS 250-meter data. Photogrammetric Engineering & Remote Sensing, 72: 1225–1234. doi: http://dx.doi.org/10.14358/PERS.72.11.1225.
  • Watts J.D., Powell S.L., Lawrence R.L., Hilker T. (2011)—Improved classification of conservation tillage adoption using high temporal and synthetic satellite imagery. Remote Sensing of Environment, 115: 66–75. doi: http://dx.doi.org/10.1016/j.rse.2010.08.005.
  • Xiao X., Boles S., Liu J., Zhuang D., Frolking S., Li C., Salas W., Moore III B. (2005)—Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remote Sensing of Environment, 95: 480–492. doi: http://dx.doi.org/10.1016/j.rse.2004.12.009.
  • Zhang F., Zhu X., Liu D. (2014)—Blending MODIS and Landsat images for urban flood mapping. International Journal of Remote Sensing, 35: 3237–3253. doi: http://dx.doi.org/10.1080/01431161.2014.903351.
  • Zhang G., Xiao X., Dong J., Kou W., Jin C., Qin Y., Zhou Y., Wang J., Menarguez M.A., Biradar C. (2015)—Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data. ISPRS Journal of Photogrammetry and Remote Sensing, 106: 157–171. doi: http://dx.doi.org/10.1016/j.isprsjprs.2015.05.011.
  • Zhang X., Friedl M.A., Schaaf C.B., Strahler A.H., Hodges J.C.F., Gao F., Reed B.C., Huete A. (2003)—Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 84: 471–475. doi: http://dx.doi.org/10.1016/S0034-4257(02)00135-9.
  • Zhao H., Yang Z., Di L., Pei Z. (2012)—Evaluation of temporal resolution effect in remote sensing based crop phenology detection studies. In: Li D., Chen Y. (Eds.), Computer and Computing Technologies in Agriculture V. Springer Berlin Heidelberg, pp. 135–150. doi: http://dx.doi.org/10.1007/978-3-642-27278-3_16.