[1]陈仲新,任建强,唐华俊,等.农业遥感研究应用进展与展望[J].遥感学报,2016,20(05):748-767.
[2]陈硕博.无人机多光谱遥感反演棉花光合参数与水分的模型研究[D].咸阳:西北农林科技大学,2019.
[3]宋勇,陈兵,王琼,等.无人机遥感监测作物病虫害研究进展[J].棉花学报,2021,33(03):291-306.
[4]魏青,张宝忠,魏征,等.无人机多光谱遥感反演冬小麦植株含水率[J].节水灌溉,2019(10):11-14,19.
[5]汤秋鸿,张学君,戚友存,等.遥感陆地水循环的进展与展望[J].武汉大学学报(信息科学版),2018,43(12):1872-1884.
[6]廖小罕,肖青,张颢.无人机遥感:大众化与拓展应用发展趋势[J].遥感学报,2019,23(06):1046-1052
[7]樊湘鹏,周建平,许燕.无人机低空遥感监测农情信息研究进展[J].新疆大学学报(自然科学版)(中英文),2021,38(05):623-631.
[8]史博,马祖凯,刘小军,等.小麦植株水分状况遥感监测研究进展与展望[J].麦类作物学报,2022,42(04):495-503.
[9]刘忠,万炜,黄晋宇,等.基于无人机遥感的农作物长势关键参数反演研究进展[J].农业工程学报,2018,34(24):60-71.
[10]Taaner C N.Plant temperatures [J].Agronomy Joumal,1963,55(2):210-211.
[11]Idso S B,Jackson R D,Pinter Jr P J,et al.Normalizing thestress-degree-day parameter for environmental variability J].Agricultural meteorology,1981,24:45-55.
[12]Wanjura D F,Upchurch D R.Canopy temperature characteriza-tions of com and cotton water status [J].Transactions of theASAE,2000,43(4):867.
[13]尚晓英,张智韬,边江,等.基于无人机热红外的水分胁迫指数与土壤含水率关系研究[J].节水灌溉,2019(04):16-21.
[14]关红杰,李久生,栗岩峰.干旱区棉花水分胁迫指数对滴灌均匀系数和灌水量的响应[J].干旱地区农业研究,2014,32(01):52-59
[15]El-Shirbeny M A,Alsersy M A M,Saleh N H,et al.Changesin irrigation water consumption in the Nile Delta of Egypt assessedby remote sensing [J].Arabian Joural of Geosciences,2015,8(12):10509-10519.
[16]Wu X,Shi J,Zhang T,et al.Crop yield estimation and irriga-tion scheduling optimization using a root-weighted soil water avail-ability based water production function [J].Field Crops Re-search,2022,284:108579.
[17]Pei W,Fu Q,Ren Y,et al.Study on the agricultural cropdrought index based on weights of growth stages [J].HydrologicalProcesses,2022,36(6):e14590.
[18]曹言,王杰,李尤亮,等.基于作物水分亏缺指数的云南省夏玉米不同生育期干旱时空特征分析[J].灌溉排水学报,2019,38(08):97-106.
[19]王连喜,王田,李琪,等。基于作物水分亏缺指数的河南省冬小麦干旱时空特征分析[J].江苏农业科学,2019,47(12):83-88.
[20]Zhang Z,Fu Y,Li H,et al.Monitoring the leaf equivalent waterthickness of kiwifruit in high temperature using leaf spectral reflec-tance [J].Spectroscopy Letters,2022:1-14.
[21]Danson F M,Steven M D,Malthus T J,et al.High-spectralresolution data for determining leaf water content [J].Internation-al Joural of Remote Sensing,1992,13 (3):461-470.
[22]Traore A,Ata-Ul-Karim S T,Duan A,et al.Predicting Equiv-alent Water Thickness in Wheat Using UAV Mounted MultispectralSensor through Deep Learning Techniques [J].Remote Sensing,2021,13(21):4476.
[23]马岩川,刘浩,陈智芳,等.基于高光谱指数的棉花冠层等效水厚度估算[J].中国农业科学,2019,52(24):4470-4483.
[24]Jones H G.Irrigation scheduling:advantages and pitfalls of plant-based methods J].Journal of experimental botany,2004,55(407):2427-2436.
[25]Bellvert J,Zarco-Tejada P J,Marsal J,et al.Vineyard iriga-tion scheduling based on airbome thermal imagery and water poten-tial thresholds [J].Australian Joumal of Grape and Wine Re-search,2016,22(2):307-315.
[26]Argyrokastritis I G,Papastylianou P T,Alexandris S.Leaf waterpotential and crop water stress index variation for full and deficit ir-rigated cotton in Mediterranean conditions J].Agriculture andAgricultural Science Procedia,2015,4:463-470.
[27]Elsayed S,Mistele B,Schmidhalter U.Can changes in leaf waterpotential be assessed spectrally?[J].Functional Plant Biology,2011,38(6):523-533.
[28]Lacerda L N,Snider J L,Cohen Y,et al.Using UAV-basedthermal imagery to detect crop water status variability in cotton[J].Smart Agricultural Technology,2022,2:100029.
[29]Rosenberg 0,Alchanatis V,Cohen Y,et al.Are thermal imagesadequate for irrigation Management C].12th International Con-ference on Precision Agriculture,Sacramento,Califomia,USA.2014.
[30]Cohen Y,Alchanatis V,Sela E,et al.Crop water status estima-tion using thermography:multi -year model development usingground-based thermal images [J].Precision Agriculture,2015,16(3):311-329.
[31]李志铭.基于高光谱遥感的棉花淹水胁迫程度监测模型研究[D].淄博:山东理工大学,2020.
[32]兰玉彬,邓小玲,曾国亮.无人机农业遥感在农作物病虫草害诊断应用研究进展[J].智慧农业,2019,1(02):1-19. |