参考文献/References:
[1]刘凯,张耗,张慎凤,等. 结实期土壤水分和灌溉方式对水稻产量与品质的影响及其生理原因[J]. 作物学报,2008,34(2):268-276.
[2]陈超,李荣,李芬,等.不同沟垄覆盖下土壤水热效应对旱作马铃薯生长及产量的影响[J].排灌机械工程学报,2020,38(11):1160-1166.
[3]王斌,何文寿,耿世杰.粉垄耕作对土壤水分利用效率和马铃薯产量的影响[J].江苏农业科学,2020,48(21):93-96.
[4]高佳,张宏斌,张恒嘉,等.绿洲灌区膜下滴灌调亏对辣椒品质及产量的影响[J].排灌机械工程学报,2021,39(4):404-409.
[5]王唯逍,刘小军,田永超,等. 不同土壤水分处理对水稻光合特性及产量的影响[J]. 生态学报,2012,32(22):7053-7060.
[6]赵嘉涛,马玉诏,范艳丽,等.生物可降解地膜对棉花产量及水分利用效率的影响[J].排灌机械工程学报,2021,39(1):96-101.
[7]MANABE S,SMAGORINSKY J,STRICKLER R F. Simulated climatology of a general circulation model with a hydrologic CYCLE1[J]. Monthly Weather Review,1965,93(12):155-169.
[8]BAIER W,ROBERTSON G W. A new versatile soil moisture budget[J]. Canadian Journal of Plant Science,1966,46(3):299-315.
[9]徐梅,隋吉东,刘振忠.土壤水分含量的理论分析及预测模型[J]. 生物数学学报,1999, 14 (1):95-99.
[10]邵晓梅,严昌荣,徐振剑.土壤水分监测与模拟研究进展[J]. 地理科学进展,2004(3):58-66.
[11]尹健康,陈昌华,邢小军,等. 基于BP神经网络的烟田土壤水分预测[J]. 电子科技大学学报,2010,39(6):891-895.
[12]刘建栋,王馥棠,于强,等. 华北地区冬小麦叶片光合作用模型在农业干旱预测中的应用研究[J]. 应用气象学报,2003,14(4):469-478.
[13]ARMAND R,WAMBEKE V. The Newhall simulation model for estimating soil moisture & temperature regimes [D].New York:Cornell University,Ithaca,2000.
[14]尚松浩,雷志栋,杨诗秀. 冬小麦田间墒情预报的经验模型[J].农业工程学报,2000, 16 (5):31-33.
[15]GONG Y S,CAO Q H,SUN Z J. The effects of soil bulk density,clay content and temperature on soil water content measurement using time-domain reflectometry[J].Hydrological Processes,2003,17(18):3601-3614.
[16]熊世为,李卫国,贾天山,等.基于HJ卫星数据的土壤含水量反演及其旱情预测[J].江苏农业学报,2014,30(5):1044-1050.
[17]WHALLEY W R,LEEDS-HARRISON P B,BOWMAN G E. Estimation of soil moisture status using near infrared reflectance[J]. Hydrological Processes,1991,5(3):321-327.
[18]HOSSEINI M,SARADJIAN M R. Multi-index-based soil moisture estimation using MODIS images[J]. International Journal of Remote Sensing,2011,32(21):6799-6809.
[19]刘洪斌,武伟,魏朝富. 基于神经网络的土壤水分预测建模研究[J]. 水土保持学报,2003,17(5):59-62.
[20]尚松浩,毛晓敏,雷志栋,等. 冬小麦田间墒情预报的BP神经网络模型[J]. 水利学报,2002,33(4):60-63.
[21]ELSHORBAGY A,PARASURAMAN K. On the relevance of using artificial neural networks for estimating soil moisture content[J]. Journal of Hydrology,2008,362(1/2):1-18.
[22]ADEYEMI O,GROVE I,PEETS S,et al. Dynamic neural network modelling of soil moisture content for predictive irrigation scheduling[J]. Sensors,2018,18(10):1-22.
[23]LI W G,LIU Y,CHEN H,et al. Estimation model of winter wheat disease based on meteorological factors and spectral information[J]. Food Production Processing and Nutrition,2020,2(1):77-82.
[24]李卫国,王纪华,赵春江,等. 冬小麦抽穗期长势遥感监测的初步研究[J]. 江苏农业学报,2007,23(5):499-500.
[25]JORDAN C F. Derivation of leaf‐area index from quality of light on the forest floor[J]. Ecology,1969,50(4):663-666.
[26]林子晶,李卫国,申双和,等. HJ星和GF1号数据在水稻种植面积提取中的应用[J].江苏农业学报,2016,32(1):111-117.
[27]王嵘冰,徐红艳,李波,等. BP神经网络隐含层节点数确定方法研究[J].计算机技术与发展,2018,28(4):31-35.
[28]汪四水,张孝羲.基于神经网络的稻纵卷叶螟长期预测[J].植物保护学报,2000, 27(4):313-316.
[29]李卫国,黄文江,董莹莹,等.基于温湿度与遥感植被指数的冬小麦赤霉病估测[J].农业工程学报,2017,33(23):203-210.
[30]刘平. 人工神经网络用于化学数据解析的研究(Ⅰ):逼近规律与过拟合[J]. 高等学校化学学报,1996,20(6):861-865.
[31]李俭川,秦国军,温熙森,等. 神经网络学习算法的过拟合问题及解决方法[J]. 振动,测试与诊断,2002(4):16-20,76.
[32]ZHANG R H,SUN X M,ZHU Z L,et al. A remote sensing model for monitoring soil evaporation based on differential thermal inertia and its validation[J]. Science in China. Series D,Earth sciences,2003,46(4):342-355.
[33]余涛,田国良. 热惯量法在监测土壤表层水分变化中的研究[J]. 遥感学报,1997,1(1):24-31.
[34]GOWARD S N,XUE Y,CZAJKOWSKI K P. Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements:an exploration with the simplified simple biosphere model[J]. Remote Sensing of Environment,2002,79(2/3):225-242.
[35]MALLICK K,BHATTACHARYA B K,PATEL N K. Estimating volumetric surface moisture content for cropped soils using a soil wetness index based on surface temperature and NDVI[J]. Agricultural & Forest Meteorology,2009,149(8):1327-1342.
[36]WIGNERON J P,WALDTEUFEL P,CHANZY A,et al. Two-dimensional microwave interferometer retrieval capabilities over land surfaces (SMOS Mission)[J]. Remote Sensing of Environment,2017,73(3):270-282.
[37]NOTARNICOLA C,ANGIULLI M,POSA F. Soil moisture retrieval from remotely sensed data:neural network approach versus Bayesian method[J]. IEEE Transactions on Geoscience & Remote Sensing,2008,46(2):547-557.
[38]张坤,刘永强,阿依尼格尔·亚力坤,等.塔克拉玛干沙漠腹地土壤热通量的陆面过程与卫星遥感研究[J].江苏农业科学,2020,48(20):256-264.