Drought Monitoring of Winter Wheat in Henan Province Based on LAI-Ts Space

doi:10.3969/j.issn.1000-6362.2018.02.007

Abstract

Abstract: Drought has become the main natural disasters affecting winter wheat production in Henan province and it is very important to monitor drought conditions. The leaf area index (LAI) and land surface temperature (Ts) data from MODIS/Terra between February 26 and June 1 in 2000, 2005, 2010 and 2015 were used to evaluate applicability of Temperature LAI Dryness Index (TLDI) based on LAI-Ts space for drought monitoring when NDVI was not saturated. Comparing with soil moisture in 10cm depth from the meteorological stations in Henan province, there was a highly significant correlation between TLDI and 10cm-depth soil moisture(P＜0.05), and their correlation coefficient varied between 0.5212 and 0.7467, which indicated that TLDI, coming from LAI-Ts space, could effectively detect the agriculture drought when NDVI was not saturated. In addition, LAI-Ts space is triangular in the early stage of vegetation and it gradually evolved into a trapezoid with the increase of vegetation coverage. The drought events of Henan Province from February 26 to June 1 in 2000, 2005, 2010 and 2015 were assessed by TLDI. Drought in Henan Province was mainly occurred in the central and western regions, the southwest and the northern region. The drought occurred frequently at the beginning of the March which was the turning green stage of winter wheat and May which was the stage from flowering to filling of winter wheat, every year.

Key words: MODIS product, Temperature LAI dryness index, Triangle LAI-Ts space, Trapezoid LAI-Ts space

LIU Ying, YUE Hui, ZHANG Feng, YANG Kun. Drought Monitoring of Winter Wheat in Henan Province Based on LAI-Ts Space[J]. Chinese Journal of Agrometeorology, 2018, 39(02): 129-139.

References

[1]刘勤,严昌荣,何文清.黄河流域干旱时空变化特征及其气候要素敏感性分析[J].中国农业气象,2016,37(6):623-632. Liu Q, Yan C R, He W Q. Drought variation and its sensitivity coefficients to climatic factors in the Yellow River Basin[J]. Chinese Journal of Agrometeorology,2016,37(6): 623-632.(in Chinese) [2]Du L,Song N,Liu K,et al.Comparison of two simulation methods of the temperature vegetation dryness index (TVDI) for drought monitoring in semi-arid regions of China[J]. Remote Sensing,2017,9(2):177-196. [3]Sandholt I,Rasmussen K,Andersen J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J].Remote Sensing of Environment,2002,79(2):213-224. [4]Naira C,Robert L,Ramata M.Surface soil moisture status over the Mackenzie River Basin using a temperature/vegetation index[A].Geoscience and Remote Sensing Symposium, 2007[C].IEEE,2007:1846-1848. [5]Patel N R,Anapashsha R,Kumar S,et al.Assessing potential of MODIS derived temperature/vegetation condition index (TVDI) to infer soil moisture status[J].International Journal of Remote Sensing,2009,30(1):23-39. [6]Dhorde A G,Patel N R.Spatio-temporal variation in terminal drought over western India using dryness index derived from long-term MODIS data[J].Ecological Informatics,2016,32: 28-38. [7]Cao X,Feng Y,Wang J.An improvement of the Ts-NDVI space drought monitoring method and its applications in the Mongolian plateau with MODIS,2000-2012[J].Arabian Journal of Geosciences,2016,9(6):1-14. [8]Zhang L,Jiao W,Zhang H,et al.Studying drought phenomena in the Continental United States in 2011 and 2012 using various drought indices[J].Remote Sensing of Environment, 2017,190:96-106. [9]沈润平,郭佳,张婧娴,等.基于随机森林的遥感干旱监测模型的构建[J].地球信息科学学报,2017,19(1):125-133. Shen R P,Guo J,Zhang J X,et al.Construction of a drought monitoring model using the random forest based remote sensing[J].Journal of Geo-information Science,2017,19(1): 125-133.(in Chinese) [10]薄燕飞,白建军,刘永林.基于TVDI及气象干旱指数的河北省春旱时空变化特征[J].兰州大学学报(自科版),2016, 52(2):188-195. Bo Y F,Bai J J,Liu Y L.The spatial-temporal variations of spring drought in Hebei province based on TVDI and meteorological drought index[J].Journal of Lanzhou University: Natural Science,2016,52(2):188-195.(in Chinese) [11]王莺,王劲松,姚玉璧,等.基于温度植被干旱指数的广东省旱情动态监测[J].草业学报,2014,23(2):98-107. Wang Y,Wang J S,Yao Y B,et al.Dynamic monitoring of drought based on temperature vegetation dryness index in Guangdong province[J].Acta Prataculturae Sinica,2014,23 (2):98-107.(in Chinese) [12]孙丽,王飞,李保国,等.基于多源数据的武陵山区干旱监测研究[J].农业机械学报,2014,45(1):246-252. Sun L,Wang F,Li B G,et al.Study on drought monitoring of Wuling Mountain Area based on multisource data[J]. Transactions of the Chinese Society for Agricultural Machinery, 2014,45(1):246-252.(in Chinese) [13]随欣欣,秦其明,董恒,等.基于LST_LAI特征空间的农田干旱监测研究[J].光谱学与光谱分析,2013,33(1):201-205. Sui X X,Qin Q M,Dong H,et al.Monitoring of farmland drought based on LST-LAI spectral feature space[J]. Spectros- copy and Spectral Analysis,2013,33(1): 201-205.(in Chinese) [14]Han L J,Wang P X,Yang H,et al.Study on NDVI-Ts space by combining LAI and evapotranspiration[J].Science in China (D Series):Earth Sciences,2006,49(7):747-754. [15]Liu Y,Wu L X,Yue H.Biparabolic NDVI-Ts space and soil moisture remote sensing in an arid and semiarid area[J]. Canadian Journal of Remote Sensing,2015,41(3): 159-169. [16]Fan X,Liu Y.A global study of NDVI difference among moderate-resolution satellite sensors[J].Isprs Journal of Photogrammetry & Remote Sensing,2016,121:177-191. [17]刘英,马保东,吴立新,等.基于NDVI-ST双抛物线特征空间的冬小麦旱情遥感监测[J].农业机械学报,2012,43(5): 55-63. Liu Y,Ma B D,Wu L X,et al.Drought remote sensing for winter wheat based on double parabola NDVI-ST space[J]. Transactions of the Chinese Society for Agricultural Machinery, 2012, 43(5):55-63.(in Chinese)