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Indian Journal of Agricultural Research

Temporal and Spatial Delineation the Rice Growing Stages for Cropping Calendar Estimation in the Southern of Vietnam using Remote Sensing

DOI: 10.18805/IJARe.A-660    | Article Id: A-660 | Page : 268-275
Citation :- Temporal and Spatial Delineation the Rice Growing Stages for Cropping Calendar Estimation in the Southern of Vietnam using Remote Sensing.Indian Journal of Agricultural Research.2022.(56):268-275
Vo Quang Minh, Tran Thi Hien, Nguyen Thi Hong Diep, Huynh Thi Thu Huong, Phan Kieu Diem vqminh@ctu.edu.vn
Address : Department of Land Resources, College of Environment Natural Resources, Cantho University, Cantho, 900000, Vietnam.
Submitted Date : 27-05-2021
Accepted Date : 20-09-2021
First Online:

Abstract

Background: MODerate resolution imaging spectroradiometer (MODIS) is the crucial instrument aboard. It provides global maps of several land surface characteristics. 
Method: The study uses MODIS to delineate the rice sowing and progress of the rice cropping calendar in the Vietnamese Mekong Delta. The study used multi-time series of normalized difference vegetation index (NDVI) images from 250 m spatial resolution MOD13Q1 images with 16-day combination to determine rice sowing/planting and harvesting schedules (from 01/01/2008 to 30/09/2009). Using 82 MODIS images, the study calculates the NDVI time series for rice sowing/transplanting stages in the Mekong Delta. Over time, the relationship between NDVI values and the rice cropping stages determines each cropping season starting and ending time. 
Result: As a result, we delineate three (3) major rice cropping systems and eight (8) cropping seasons. In which Main Winter-Spring and Early Summer-Autumn and Late Main Winter-Spring and Main Summer-Autumn cropping seasons dominated. MODIS satellite images are efficient and helpful for determining the current state of rice evolution. It is suitable for the regional or national level, which can provide quick and low-cost information for managers and decision-makers to select the proper strategies for crop management.

Keywords

MODIS NDVI Rice sowing Satellite images Season  ​Transplanting

References

  1. Anthony, E., Brunier, J.G., Besset,  M., Goichot,  M., Dussouillez, P., Nguyen,  V.L. (2015). Linking rapid erosion of the Mekong River delta to human activities. Sci. Rep. 5: 1-12. doi:10.1038/srep14745.  
  2. ASEAN Development Bank (ADB). (2012). The Rice Situation in VietNam. Technical Assistance Consultant’s Report. Project Number: TA 7495-REG. Support for the Association of Southeast Asian Nations Plus Three Integrated Food Security Framework (Financed by the Japan Fund for Poverty Reduction).
  3. Burrough, P.A. (1986). Geographic Information Systems for Land Ressource Assessment. Prentice-Hall. Geocart International. 1(3). doi.org/10.1080/10106048609354060.
  4. Cosslett, T.L., Cosslett, P.D. (2014). The Mekong Delta. In: Water Resources and Food Security in the Vietnam Mekong Delta. Natural Resource Management and Policy, vol 44. Springer, Cham. doi.org/10.1007/978-3-319-02198-0_1.
  5. Fabrice G. Renaud, Kuenzer, C. (2012). The Mekong Delta System - Interdisciplinary Analyses of a River Delta. Springer Netherlands. Print ISBN: 978-94-007-3961-1. Electronic doi: 10.1007/978-94-007-3962-8.
  6. GSOV, (2015). General Statistic Office of Vietnam (GSOV), (2015). Statistics. Available from: https://gso.gov.vn/default.aspx? tabid=714.
  7. Huete, A.R., Justice C. (1999). (MODIS vegetation index (MOD13) algorithm theoretical basis document. Ver. 3. doi: 10.4236 /gep.2016.46008.
  8. McHugh, M.L. (2012). Interrater reliability: The kappa statistic. Biochemia Medica. 22(3): 276-282. doi: 10.11613/BM. 2012.031. 
  9. Nguyen, T.H. (2017). An Overview of Agricultural Pollution in Vietnam: The Crops Sector. Prepared for the World Bank, Washington, DC
  10. Parida, B.R., Oinam, B., Patel, N.R., Sharma, N., Kandwal, R. and Hazarika, M.K. (2008). Land surface temperature variation in relation to vegetation type using MODIS satellite data in the Gujarat state of India. International Journal of Remote Sensing, 29: 4219-4235. doi.org/10.1080/01431160701871096.
  11. Pontius, R., Millones, M. (2011). Death to Kappa: the birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing. 32(15): 4407-4429. doi:10.1080/01431161.2011.552 923. S2CID 62883674. 
  12. Sim, J., Wright, C.C. (2005). The Kappa statistic in reliability studies: Use, interpretation and sample size requirements. Physical Therapy. 85(3): 257-268. doi:10.1093/ptj/85.3.257. ISSN 1538-6724. PMID 15733050.
  13. Smajgl. A, Toan, T.Q., Nhan, D.K., Ward, J., Trung, N.H., Tri, L.Q., Tri, V.P.D., Vu, P.T. (2015). Responding to rising sea levels in the Mekong Delta. Nat. Clim. Change. 1-8, doi:10.1038/nclimate2469.
  14. Southern Center for Crop Protection. (2009). Statistical data on the progress of rice sowing in the Mekong river delta 2008 to 2009. Ministry of Agricultural and Rural Development. Vietnam.

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