Skip to main content

Advertisement

SpringerLink
Log in

Extraction of rice-planting area and identification of chilling damage by remote sensing technology: a case study of the emerging rice production region in high latitude

  • Article
  • Published:
Paddy and Water Environment Aims and scope Submit manuscript

Abstract

Rice is the second largest staple crop in the world and therefore plays an important role in food security. As a thermophilic crop, rice is sensitive to temperature changes. Thus, research on the chilling damage of rice is essential. The Sanjiang Plain is an emerging rice production area and is located at high latitudes in China, the world’s largest rice-producing country. Landsat data were used to extract rice-planting area from 1985 to 2015. MODIS 13Q1, which was uniformly distributed during the growing period of rice, was used to obtain NDVI values of paddies during 2002–2015. Dynamic Identification Index of sterile-type chilling damage and monitoring standard of delayed-type chilling damage were the proposed methods used in this paper, which were used to judge the chilling damage of rice. The results show that in the study region, the rice-planting area in 2015 is nearly 12 times larger than that in 1985. Delayed-type chilling damage occurred in 2002 and 2009, while sterile-type chilling damage occurred in 2005, 2006, 2009, 2010, 2014, and 2015. Comparing with the prevalent meteorological standards, the results indicate that the index and standards proposed in this paper are precise, applicable, and more sensitive than them. The method is a macroscopic and accurate method to identify chilling damage in rice and can also provide a scientific basis to ensuring the stability of rice yield.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Abraha MG, Savage MJ (2006) Potential impacts of climate change on the grain yield of maize for the midlands of KwaZulu-Natal, South Africa. Agric Ecosyst Environ 115(1):150–160

    Article  Google Scholar 

  • Bertin P, Bullens P, Bouharmont J, Kinet JM (1998) Somaclonal variation and chilling tolerance improvement in rice: changes in fatty acid composition. Plant Growth Regul 24(1):31–41

    Article  CAS  Google Scholar 

  • Billie L, Navin R, Jonathan AF (2004) Geographic distribution of major crops across the world. Glob Biogechem Cycles. doi:10.1029/2003GB002108

    Google Scholar 

  • Boschetti M, Stroppiana D, Confalonieri R, Brivio PA, Crema A, Bocchi S (2011) Estimation of rice production at regional scale with a light use efficiency model and MODIS time series. Italian J Remote Sens 43(3):63–81

    Google Scholar 

  • Cen H, Lu R, Zhu Q, Mendoza F (2016) Nondestructive detection of chilling injury in cucumber fruit using hyperspectral imaging with feature selection and supervised classification. Postharvest Biol Technol 111:352–361

    Article  Google Scholar 

  • China Meteorological Administration (2013) Technical standard on rice cool damage evaluate (QX/T 182-2013). China Meteorological Press, Beijing

    Google Scholar 

  • Chu C, Lee TM (1989) The relationship between ethylene biosynthesis and chilling tolerance in seedlings of rice (Oryza sativa). Bot Bull Acad Sin 30:263–273

    CAS  Google Scholar 

  • Doraiswamy PC, Hatfield JL, Jackson TJ, Akhmedov B, Prueger J, Stern A (2004) Crop condition and yield simulations using Landsat and MODIS. Remote Sens Environ 92(4):548–559

    Article  Google Scholar 

  • Farooq M, Wahid A, Kobayashi N, Fujita D, Basra SMA (2009) Plant drought stress: effects, mechanisms and management. Sustainable Agriculture. Springer, Dordrecht, pp 153–188

    Chapter  Google Scholar 

  • Feng MC, Yang WD, Cao LL, Ding GW (2009) Monitoring winter wheat freeze injury using multi-temporal MODIS data. Agric Sci China 8(9):1053–1062

    Article  Google Scholar 

  • Fisher WD (1958) On grouping for maximum homogeneity. J Am Stat Assoc 53(284):789–798

    Article  Google Scholar 

  • Guo JP, Tian ZH, Zuo X (2004) Forecasting models of heat index for rice in Northeast China. J Nat Disasters 13(3):138–145

    Google Scholar 

  • Guo XL, Wang LG, Qiu JJ, Li JH, Zhu BQ, Xiao JX, Gao MF (2009) An analysis of cold damage on rice in Northeast China based on GIS. Acta Agriculturae Universitatis Jiangxiensis 31(3):494–498

    Google Scholar 

  • Hayes MJ, Decker WL (1998) Using satellite and real-time weather data to predict maize production. Int J Biometeorol 42(1):10–15

    Article  Google Scholar 

  • He Y, Tan ZK, Li Z, Ding MH, Ou DR (2007) GIS application to the analysis of freezing damage of sugarcane in Guangxi. J Southwest University Nat Sci 29(9):81–85

    CAS  Google Scholar 

  • He YB, Chen YQ, Tang HJ (2008) Effects of cold damage on paddy rice yield per unit area based on retrieving of daily LAI by MODIS and SIMRIW model. Chinese Soc Agric Eng 23(11):188–194

    Google Scholar 

  • Jiang D, Wang NB (2002) Principles of the interaction between NDVI profile and the growing situation of crops. Acta Ecologica Sinica 22(2):247–253

    Google Scholar 

  • Jiao J, Xu XB, Meng Y (2004) Analysis of rice chilling injury and countermeasures in Heilongjiang Province. Chinese J Agrometeorol 25(2):26–28

    Google Scholar 

  • Kerdiles H, Grondona M, Rodriguez R, Seguin B (1996) Frost mapping using NOAA AVHRR data in the Pampean region, Argentina. Agric For Meteorol 79(3):157–182

    Article  Google Scholar 

  • Kogan FN (1990) Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int J Remote Sens 11(8):1405–1419

    Article  Google Scholar 

  • Kuk YI, Shin JS, Burgos NR, Hwang TE, Han O, Cho BH, Guh JO (2003) Antioxidative enzymes offer protection from chilling damage in rice plants. Crop Sci 43(6):2109–2117

    Article  CAS  Google Scholar 

  • Li ZP, Liu ZH, Li ZG, Tang PQ, Tan JY, Yang P (2014) Progress and prospect of application of remote sensing to rice spatial distribution. Chinese J Agric Resour Reg Plan 35(6):9–18

    Google Scholar 

  • Lin HR, Li ZC, Zhou QB, Luv X (2009) Monitoring frost disaster of cotton based on difference of vegetation index and canopy temperature by remote sensing. Cotton Sci 21(4):284–289

    Google Scholar 

  • Liu G, Ma XM, Xiao Y, Li XF, Liu PD (2010) Monitoring on crop condition based on CBERS image. J Anhui Agric Sci 10:5051–5052

    Google Scholar 

  • Liu XF, Zhang C, Shuai JB, Wang P, Shi WJ, Chen Y, Tao FL (2012) Effect of chilling injury on rice yield in Heilongjiang Province. Acta Geographica Sinica 67(9):1223–1232

    Google Scholar 

  • Ma YP, Wang SL, Li WJ (2011) Monitoring and predicting of Maize chilling damage based on crop crowth model in Northeast China. Acta Agronomica Sinica 37(10):1868–1878

    Article  Google Scholar 

  • Mohanty S, Wassmann R, Nelson A, Moya P, Jagadish SVK (2013) Rice and climate change: significance for food security and vulnerability. International Rice Research Institute

  • Nguyen NV (2002) Global climate changes and rice food security. Ed, Vol FAO, Rome, Italy, pp 24–30

  • Pachauri RK, Reisinger A (eds) (2007) Climate change 2007 synthesis report: summary for policymakers. IPCC Secretariat

  • Pan WB (2009) Research on rice potential productivity and development strategy in Northeast China. Dissertation, Shenyang Agricultural University

  • Rudorff BF, Adami M, Risso J, Aguiar DA, Pires B, Amaral D, Cecarelli I (2012) Remote sensing images to detect soy plantations in the amazon biome—the soy moratorium initiative. Sustainability 4(5):1074–1088

    Article  Google Scholar 

  • Szalai G, Tari I, Janda T, Pestenacz A, Páldi E (2000) Effects of cold acclimation and salicylic acid on changes in ACC and MACC contents in maize during chilling. Biol Plant 43(4):637–640

    Article  CAS  Google Scholar 

  • Tao JD, Li YF, Zeng GJ (2011) Scale and distribution variation of paddy fields and its response to climate change in Heilongjiang Province in recent 30 years. China Land Sci 25(4):26–30

    Google Scholar 

  • Tucker CJ, Slayback DA, Pinzon JE, Los SO, Myneni RB, Taylor MG (2001) Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999. Int J Biometeorol 45(4):184–190

    Article  CAS  PubMed  Google Scholar 

  • Wu JJ, Yang QY (2002) Crop monitoring and yield estimation using synthetic methods in arid land. Geogr Res 21(5):593–598

    Google Scholar 

  • Wu BF, Zhang F, Liu CL, Zhang L, Luo ZM (2004) An integrated method for crop condition monitoring. J Remote Sens 6(06):498–514

    Google Scholar 

  • Yan L, Zhang JQ, Wang CY, Yan DH, Liu XP, Tong ZJ (2012) Vulnerability evaluation and regionalization of drought disaster risk of maize in Northwestern Liaoning Province. Chinese J Eco-Agric 20(6):788–794

    Article  Google Scholar 

  • Yoshino K, Kushida K, Ishioka Y (2004) Differences in plant canopy bi-directional reflectance factors among rice varieties. Paddy Water Environ 2(3):153–162

    Article  Google Scholar 

  • Zhang SY, Li DK, Yan SA, Jing YG, Gao B (2006a) Effect of MODIS vegetation index in detection and evaluation of crops in Guanzhong Shaaxi. Shaanxi J Agric Sci 4:71–73

    Google Scholar 

  • Zhang XF, Chen HL, Zheng YF, ZOU CH, Chen D, Fu XJ (2006b) Monitoring the freezing injury of winter wheat by remote sensing. J Nanjing Inst Meteor 29(1):94–100

    CAS  Google Scholar 

  • Zhang JH, Yao FM, Zheng LY (2009) Vegetation variations and causes in alpine ecosystem of the Northern Tibet Plateau based on remote sensing. Acta Scientiarum Naturalium Universitatis Sunyatseni 5:143–147

    Google Scholar 

  • Zhang LW, Wang XZ, Jiang LX, Huang JF (2015) Dynamic monitoring of rice delayed-type chilling damage using MODIS-based heat index in northeast China. J Remote Sens 19(4):690–701

    Google Scholar 

Download references

Acknowledgments

This study was supported by Scientific Research (B), 15H05256 (PI: Prof. Haruhiko Yamamoto, Yamaguchi University, Japan).

Author information

Authors and Affiliations

  1. Graduate School of Agriculture, Hokkaido University, Sapporo, 060-8589, Japan

    Zhongyi Sun, Guosheng Zhong & Shuai Yin

  2. Research Faculty of Agriculture, Hokkaido University, Sapporo, 060-8589, Japan

    Xiufeng Wang & Hiroshi Tani

  3. Faculty of Agriculture, Yamaguchi University, Yamaguchi, 753-8515, Japan

    Haruhiko Yamamoto

  4. Institute of Natural Disaster Research, Northeast Normal University, Changchun, 130024, China

    Jiquan Zhang

Authors
  1. Zhongyi Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiufeng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haruhiko Yamamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jiquan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hiroshi Tani
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guosheng Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Shuai Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhongyi Sun.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, Z., Wang, X., Yamamoto, H. et al. Extraction of rice-planting area and identification of chilling damage by remote sensing technology: a case study of the emerging rice production region in high latitude. Paddy Water Environ 15, 181–191 (2017). https://doi.org/10.1007/s10333-016-0539-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10333-016-0539-x

Keywords

Search

Navigation