Skip to main content

Advertisement

Log in

Dynamic monitoring of drought using HJ-1 and MODIS time series data in northern China

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

From early November 2008 to February 2009, lack of rainfall led to severe drought in northern China. More than 9.3 million ha of wheat in six major crop production provinces, including Henan, Anhui, Shandong, Shanxi, Gansu, and Shaanxi, were hit by drought. Supported by Chinese HJ-1 satellite images together with NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data, dynamic monitoring of the drought was conducted. HJ-1 CCD data with 30-m resolution were used to identify cropland information. Spatialtemporal variation of drought was detected using Vegetation Index and Water Index time series data derived from MODIS visible, infrared, and short-wave infrared bands. The influences of drought were classified into five levels based on MODIS-derived 8-day composite Anomaly Water Index (AWI) and field survey data. The results indicated that the drought deteriorated beginning in November 2008 and became most serious in late January 2009. HJ-1 data together with MODIS data proved to be valuable data sources for monitoring soil moisture and drought at a both regional and national scale.

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

Access this article

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

Instant access to the full article PDF.

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

Similar content being viewed by others

References

  • Ceccato P, Flasse S, Gregoire JM (2002) Designing a spectral index to estimate vegetation water content from remote sensing data: part 2. Validation and applications. Remote Sens Environ 82(2):198–207

    Article  Google Scholar 

  • Corresponding DJ, Yang X, Clinton N, Wang N (2004a) An artificial neural network model for estimating crop yields using remotely sensed information. Int J Remote Sens 25(9):1723–1732

    Article  Google Scholar 

  • Corresponding ZW, Wang P, Li X (2004b) Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains USA. Int J Remote Sens 25(1):61–72

    Article  Google Scholar 

  • Delbart N, Kergoat L, Le Toan T, Lhermitte J, Picard G (2005) Determination of phenological dates in boreal regions using normalized difference water index. Remote Sens Environ 97(1):26–38

    Article  Google Scholar 

  • Gao BC (1996) NDWI—a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens Environ 58(3):257–266

    Article  Google Scholar 

  • Gao M, Qin Z, Zhang H, Lu L, Zhou X, Yang X (2008) Remote sensing of agro-droughts in Guangdong province of China using MODIS satellite data. Sensors 8(8):4687–4708

    Article  Google Scholar 

  • Ghulam A, Qin Q, Teyip T, Li ZL (2007a) Modified perpendicular drought index (MPDI): a real-time drought monitoring method. ISPRS J Photogramm Remote Sens 62(2):150–164

    Article  Google Scholar 

  • Ghulam A, Qin Q, Zhan Z (2007b) Designing of the perpendicular drought index. Environ Geol 52(6):1045–1052

    Article  Google Scholar 

  • Gu Y, Hunt E, Wardlow B, Basara JB, Brown JF, Verdin JP (2008) Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data. Geophys Res Lett 35(22):L22401

    Article  Google Scholar 

  • Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83(1):195–213

    Article  Google Scholar 

  • Hwang T, Kang S, Kim J, Kim Y, Lee D, Band L (2008) Evaluating drought effect on MODIS Gross Primary Production (GPP) with an eco-hydrological model in the mountainous forest East Asia. Glob Change Biol 14(5):1037–1056

    Article  Google Scholar 

  • Jackson TJ, Chen D, Cosh M, Li F, Anderson M, Walthall C, Doriaswamy P, Hunt E (2004) Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sens Environ 92(4):475–482

    Article  Google Scholar 

  • Ji L, Peters AJ (2003) Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sens Environ 87(1):85–98

    Article  Google Scholar 

  • Jiang-yong WJGUO, Lan-fang ZYY (2007) Progress and prospect on drought indices research [J]. Arid Land Geogr 1

  • Jianping ZXZXL, Ning SZC (2007) Progress in drought monitoring by remote sensing in China [J]. Meteorological, Science and Technology 4

    Google Scholar 

  • Maki M, Ishiahra M, Tamura M (2004) Estimation of leaf water status to monitor the risk of forest fires by using remotely sensed data. Remote Sens Environ 90(4):441–450

    Article  Google Scholar 

  • Malingreau J, Belward A (1992) Scale considerations in vegetation monitoring using AVHRR data. Int J Remote Sens 13(12):2289–2307

    Article  Google Scholar 

  • Mongkolsawat C, Thirangoon P, Suwanwerakamtorn R, Karladee N, Paiboonsak S, Champathet P (2001) An evaluation of drought risk area in Northeast Thailand using remotely sensed data and GIS. Asian J Geoinformatics 1(4):33–44

    Google Scholar 

  • Nai-bin W (1996) Wheat growth monitoring and yield estimation by remote sensing in China. Science and Technology Press, Beijing

    Google Scholar 

  • Ordoyne C, Friedl MA (2008) Using MODIS data to characterize seasonal inundation patterns in the Florida Everglades. Remote Sens Environ 112(11):4107–4119

    Article  Google Scholar 

  • Qiang ZXZ (2008) Preliminary studies on variations in droughts over China During past 50 Years [J]. J Appl Meteorol Sci 6

  • Rasmussen MS (1998) Developing simple, operational, consistent NDVI-vegetation models by applying environmental and climatic information. Part II: crop yield assessment. Int J Remote Sens 19(1):119–139

    Article  Google Scholar 

  • Thenkabail PS, Gamage M, Smakhtin VU (2004) The use of remote sensing data for drought assessment and monitoring in Southwest Asia, vol 85. Iwmi

  • Townshend JRG, Justice CO (2002) Towards operational monitoring of terrestrial systems by moderate-resolution remote sensing. Remote Sens Environ 83(1–2):351–359

    Article  Google Scholar 

  • Wilhite DA (2000) Drought as a natural hazard: concepts and definitions. Drought, A glob assess 1:3–18

    Google Scholar 

  • Xiao X, Zhang Q, Hollinger D, Aber J, Moore B III (2005) Modeling gross primary production of an evergreen needle leaf forest using MODIS and climate data. Ecol Appl 15(3):954–969

    Article  Google Scholar 

  • Zarco-Tejada PJ, Rueda C, Ustin S (2003) Water content estimation in vegetation with MODIS reflectance data and model inversion methods. Remote Sens Environ 85(1):109–124

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Chinese Academy of Sciences (Grant No. KZZD-EW-08), the Ministry of Environmental Protection of China, and State Key Laboratory of Resources and Environment Information System. The authors would like to thank Professor Qiao Wang and his teams for their valuable suggestions.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jingying Fu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jiang, D., Fu, J., Zhuang, D. et al. Dynamic monitoring of drought using HJ-1 and MODIS time series data in northern China. Nat Hazards 68, 337–350 (2013). https://doi.org/10.1007/s11069-013-0626-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-013-0626-x

Keywords

Navigation