个人简历

教育背景
1980.9-1984.7 南京气象学院（现南京信息工程大学）农业气象专业本科
2001.9-2002.9 加拿大多伦多大学地理系硕士
2002.9-2006.9 加拿大多伦多大学地理系博士
工作经历
1980.8-1989.3 江苏省气象科学研究所助理工程师
1989.4-1994.12 江苏省气象科学研究所工程师
1995.1-2000.5 江苏省气象科学高级工程师、副所长
2006.10-2007.1 加拿大多伦多大学地理系博士后
2007.1- 2008.4 南京大学国际地球系统科学研究所教授、硕士生导师
2008.4-南京大学国际地球系统科学研究所教授、博士生导师
科研项目
（11）FY-3在全球碳收支估算中的应用示范”，国家卫星气象中心科技项目，2017年6月-2018年5月，主持。
（10）基于多源卫星遥感的高分辨率全球碳同化系统研究，“全球变化及应对”国家重点研发计划项目，2016年7月-2021年6月，主持。
（9）陆地生态系统模型与遥感数据同化研究，“全球变化及应对”国家重点研发计划课题，2016年7月-2021年6月，主持。
（8）阴叶和阳叶对冠层叶绿素荧光的贡献及其与光合作用关系，国家自然科学基金面上项目，2017年1月-2020年12月，主持。
（7）近30年1全球陆地生态系统碳源汇动态及预测研究，973项目课题， 2010年6月-2014年12月，主持。
（6）地表覆盖数据在陆面生态水文模型中的应用示范及示范系统开发，863重点项目子课题，2010年1月-2012年12月，主持。
（5）鄱阳湖流域碳水循环对植被恢复的响应，国家自然科学基金，2009年1月-2011年12月，主持。
（4）植被叶片聚集度系数和叶面积指数多角度遥感反演方法，863项目，2009年1月-2010年12月，主持。
（3）不同气候背景下植被气孔阻抗对地表水循环的控制作用，国家自然科学基金，2008年1月-2010年12月，参加。
（2）亚洲季风区陆地碳循环模拟研究，国家自然科学基金国际合作项目子课题，2007年8月-2012年8月，参加。
（1）“十一五”国家支撑项目“农村生态环境监测和整治关键技术”子课题“农村生态环境预警技术和应急预案决策系统研究”， 2006-2010，主持。
奖励荣誉
省部级：
2017年，江西省气候变化影响评估金和适应关键技术研究，江西省科学技术进步二等奖，6/8。
2009年，中国草原植被遥感监测关键技术研究与应用，中国农业科技奖一等奖，15/15。
1998年，江苏省农业气象与卫星遥感业务系统，江苏省政府重大农业成果推广二等奖（3/15）。
1998年，极轨气象卫星遥感资料微机图像处理系统台站实用技术，凃长望青年气象科技二等奖（独立）。
1997年，江苏省农业遥感业务系统研制与应用，中国气象局科技进步二等奖（2/7）。
1996年，江苏省气象卫星农业遥感业务系统研制与应用—气象卫星遥感资料处理系统 (V.32)，江苏省优秀软件一等奖（2/3）。
厅局级：
2001年，农业气象诊断预测与信息可视化服务系统，江苏省气象局科技进步一等奖（2/7）。
2001年，沪宁高速公路 (江苏段) 秋冬季雾害预防研究，江苏省气象局科技进步一等奖(7/7)。
2000年，干旱实时分析预警及其在人工天气中的应用，江苏省气象局科技进步二等奖(1/5)。
1999年，气象卫星遥感旱涝自动分类识别解译系统，干旱实时分析预警及其在人工天气中的应用，江苏省气 象局科技进步二等奖(1/5)。

研究领域

生态环境遥感、遥感模型数据同化、生态系统碳水耦合循环模拟、气候变化影响评估""

近期论文

2019
127. Chen JM, Ju WM*, Ciais P, Viovy N, Liu RG, Liu Y, Lu XH, 2019. Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink. Nature Communications, doi.org/10.1038/s41467-019-12257-8.
126. Wang SH, Ju WM, J Peñuelas, Cescatti A, Zhou YY, Fu YS, Huete A, Liu M, and Zhang YG*, 2019. Urban−rural gradients reveal joint control of elevated CO2 and temperature on extended photosynthetic seasons. Nature Ecology and Evolution, https://doi.org/10.1038/s41559-019-0931-1.
125. Qiu B, Chen JM, Ju WM, Zhang Q, Zhang YG*, 2019. Simulating emission and scattering of solar-induced chlorophyll fluorescence at far-red band in global vegetation with different canopy structures. Remote Sensing of Environment, 233: DOI: 10.1016/j.rse.2019.111373.
124. Dai SP, Ju WM*, Zhang YG, He QN, Song L, and Li J, 2019. Variations and drivers of methane fluxes from a rice-wheat rotation agroecosystem in eastern China at seasonal and diurnal scales. Science of the Total Environment,690: 973-990.
123. Qiu F, Chen JM, Croft H, Li Jing, Zhang Q, Zhang YG, Ju WM*, 2019. Retrieving leaf chlorophyll content by incorporating variable leaf surface reflectance in the PROSPECT model. Remote Sensing, 11, 1572; doi:10.3390/rs11131572.
122. Zhu SH, Li GF, Shao H, Ju WM*, Lv NN, 2019. The response of carbon stocks of drylands in Central Asia to changes of CO2 and climate during past 35 years. Science of the Total Environment, 687: 330-340.
120. Li J, Ju WM*, He W, Wang HM, Zhou YL, Xu MZ, 2019. An algorithm differentiating sunlit and shaded leaves for improving canopy conductance and evapotranspiration estimates. Journal of Geophysical Research: Biogeosciences, 124, 807–824. https://doi.org/10.1029/2018JG004675.
119. Chen YZ*, Ju WM, Mu SJ, Fei XR, Cheng Y, Propastin P, Zhou W, Liao CJ, Chen LX, Tang RJ, Qi JG, Li JL, Ruan1 HH, 2019. Explicit representation of grazing activity in a diagnostic terrestrial model: a data-process combined scheme. Journal of Advances in Modeling Earth Systems, 11, 957–978. https://doi.org/10.1029/ 2018MS001352.
118. Wang HM, Jiang F*, Wang J, Ju WM, and Chen JM, 2019.Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 XCO2 retrievals. Atmosphere and Chemistry Physics, 19,12067–12082.
117. Shan N, Ju WM, Migliavacca M, Martini D, Guanter L, Chen JM, Goulas Y, and Zhang YG*, 2019. Modeling canopy conductance and transpiration from solar-induced chlorophyll fluorescenc. Agricultural and Forest Meteorology, 268: 189-201.
116. Xu MZ, Liu RG*, Chen JM, Liu R, Shang R, Ju WM, Wu CY, and Huang WJ, 2019. Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach. Remote Sensing of Environment, 224, 60-73.
115. Lu XH, Ju WM*, Jiang H, Zhanga XY, Liu JX, Sherb J, 2019. Effects of nitrogen deposition on water use efficiency of global terrestrial ecosystems simulated using the IBIS model. Ecological Indictors, 101: 954-962.
114. Huang Q, Ju WM*, Zhang FY, and Zhang Q, 2019. Roles of climate change and increasing CO2 in driving changes of net primary productivity in China simulated using a dynamic global vegetation model. Sustainability, 11, 4176, doi:10.3390/su11154176.
2018
113. Liu YB, Xiao JF*, Ju WM, Zhu GL, Wu XC, Fan WL, Li DQ, and Zhou YL, 2018. Satellite-derived LAI products exhibit large discrepancies and can lead to substantial uncertainty in simulated carbon and water fluxes. Remote Sensing of Environment, 206: 174-188.
112. Lai JM, Zhan WF*, Huang F, Quan JL, Hu LQ, Gao L, and Ju WM, 2018. Does quality control matter? Surface urban heat island intensity variations estimated by satellite-derived land surface temperature products. ISPRS Journal of Photogrammetry and Remote Sensing, 139: 212-227.
111. Wang J, Wu CY*, Zhang CH, Ju WM,Wang XY, Chen Z, Fang B, 2018.Improved modeling of gross primary productivity (GPP) by better representation of plant phenological indicators from remote sensing using a process model. Ecological Indicators, 88: 332-340.
110. Chen YZ, Tao YW, Cheng Y, Ju WM, Ye JY, Hickler T, Liao CJ, Feng L, and Ruan HH*, 2018. Great uncertainties in modeling grazing impact on carbon sequestration: a multi-model inter-comparison in temperate Eurasian Steppe. Environmental Research Letters, 13(7): 075005, DOI: 10.1088/1748-9326/aacc75.
109. Zhou L,Wang SQ*, Chi YG, Ju WM, Huang K, Mickler RA, Wang MM, Yu, QZ. Changes in the carbon and water fluxes of subtropical forest ecosystems in south-western China related to drought. Water, 10(7): 821,DOI: 10.3390/w10070821.
108. Wang J, Zeng N*, Wang MR, Jiang F, Chen JM, Friedlingstein P, Jain AK, Jiang ZQ, Ju WM, Lienert S, Nabel J, Sitch S, Viovy N, Wang HM,Wiltshire AJ. Contrasting interannual atmospheric CO2 variabilities and their terrestrial mechanisms for two types of El Ninos.Atmospheric Chemistry and Physics, 18(14): 10333-10345.
107. He W, van der Velde IR, Andrews AE, Sweeney C, Miller J, Tans P, van der Laan-Luijkx IT, Nehrkorn T, Mountain M, Ju WM, Peters W, and Chen HL*, 2018. CTDAS-Lagrange v1.0: a high-resolution data assimilation system for regional carbon dioxide observations. Geoscientifc Model Development, 11(8): 3515-3536.
106.Wang SH, Zhang YG, Hakkarainen J, Ju WM, Liu YX, Jiang F, He W, 2018. Distinguishing anthropogenic CO2 emissions from different energy intensive industrial sources using OCO-2 observations: A case study in Northern China. Journal of Geophysical Research-atmosphere, 123(17): 9462-9473.
105. Zhang CH, Ju WM, Chen JM, Fang MH, Wu MQ, Chang XL, Wang T, and Wang XQ, 2018. Sustained biomass carbon sequestration by China's forests from 2010 to 2050. Forests, 9(11): 689,DOI: 10.3390/f9110689.
104. Luo XZ, Keenan TF, Fisher JB, Jimenez-Munoz JC, Chen, JM, Jiang CY,Ju WM, Perakalapudi NV,Ryu Y, Tadic JM, 2018. The impact of the 2015/2016 El Nino on global photosynthesis using satellite remote sensing. Philosophical Transactions of the Royal Society B-Biological Sciensces, 373(1760),20170409.,http://dx.doi.org/10.1098/rstb.2017.0409
103.Wu CY, Wang XY, Wang HJ, Ciais P, Peñuelas J, Myneni RB,Desai AR, Gough CM, Gonsamo A, Black AT, Jassal RS, Ju WM, Yuan WP, Fu YS, Shen MG, Li SH, Liu RG, Chen JM, and Ge QS, 2018. Contrasting responses of autumn-leaf senescence to daytime and night-time warming. Nature Climate Change, doi.org/10.1038/s41558-018-0346-z.
102. Jiang L, Zhan WF, Voogt J, Zhao LM, Gao L, Huang F, Cai Z, and Ju WM, 2018. Remote estimation of complete urban surface temperature using only directional radiometric temperatures. Building and Environment, 135: 224-236.
101. He W, Ju WM*, Schwalm CR, Sippel S, Wu XC, He QN, Zhang CH, Li J, Stich S, Viovy, N, Friedlingstein P, and Jain AK, 2018. Large-scale droughts responsible for dramatic reductions of terrestrial net carbon uptake over North America in 2011 and 2012. Journal of Physical Reseach-Biogeosciences,123, 10.1029/2018JG004520.
100.Lai J, Zhan WF, Huang F , Quan, JL, Hu LQ, Gao L, Ju WM, 2018.Does quality control matter? Surface urban heat island intensity variations estimated by satellite-derived land surface temperature products. ISPRS Journal of Photogrammetry and Remote Sensing, 139: 212-227.
99. Song L, Guanter L, Guang KY, You LZ, Huete A, Ju WM, and Zhang YG, 2018. Satellite sun-induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo-Gangetic Plains. Global Chang Biology, 24(9): 4023-4037.
98. Ma LX, Zheng G, Wang XF, Li SM, Lin Y, and Ju WM, 2018. Retrieving forest canopy clumping index using terrestrial laser scanning data. Remote Sensing of Environment, 210: 452-472.
97. Qiu F, Chen JM, Ju WM*, Wang J, Zhan Q, and Fang MH, 2018, Improving the PROSPECT model to consider anisotropic scattering of leaf internal materials and its use for retrieving leaf biomass in fresh leaves. IEEE Transactions on Geosciences and Remote Sensing, 99, 1-19.
96. Zan M, Zhou YL*, Ju WM, Zhang YG, Zhan LM, and Liu YB, 2018. Performance of a two-leaf light use efficiency model for mapping gross primary productivity against remotely sensed sun-induced chlorophyll fluorescence data. Science of the Total Environment, 613-614: 977-989.
2017
95. Huang F, Zhan WF*, Wang ZH, Wang KC, Chen JM, Liu YX, Lai JM , Ju WM, 2017. Positive or Negative? Urbanization-induced variations in diurnal skin-surface temperature range detected using satellite data. Journal of Geophysical Research-Atmospheres,122(24): 13229-13244.
94. Chen YZ, Ju WM, Groisman P, Li JL, Propastin P, Xu X, Zhou W., and Ruan HH, 2017. Quantitative assessment of carbon sequestration reduction induced by disturbances in temperate Eurasian steppe. Environmental Research Letters, 12: 11505.
93. Chen YZ, Li JL, Ju WM, Ruan HH, Qin ZH, Huang YY, Jeeiani N, Padarian J, Propastin P, 2017. Quantitative assessments of water-use efficiency in Temperate Eurasian Steppe along an aridity gradient. 2017,PLoS ONE 12(7): e0179875.
92. Chen ZQ, Chen JM, Zhang SP, Zheng XG, Ju WM, Mo G, and LU XL, 2017. Optimization of terrestrial ecosystem model parameters using atmospheric CO2 concentration data with the global carbon assimilation system (GCAS). Journal of Geophysical Research: Biogeosciences,122, 3218–3237.
91. Fang MH, Ju WM*, Zhan WF, Chen T, Qiu F, and Wang J, 2017. A new spectral similarity water index for the estimation of leaf water content from hyperspectral data of leaves. Remote Sensing of Environemnt,196: 13-27.
90.Sun SL*,Chen HS, Ju WM,Wang GJ, Sun G,Huang J, Ma HD, Gao CJ, Hua WJ, andYan, GX, 2017. On the coupling between precipitation and potential evapotranspiration: contributions to decadal drought anomalies in the Southwest China. Climate Dynamics, 48(11): 3779-3797.
89. Sun SL*, Chen HS ,Sun G, Ju WM,Wang GJ, Li X, Yan GX, Gao CJ, Huang J, and Zhang, FM, 2017.Attributing the changes in reference evapotranspiration in southwestern China using a new separation method. Journal of Hydrometeorology, 18(3): 777-798.
88. Zhan Q, Chen JM, Ju WM*, Wang HM, Qiu F, Yang FT, Fan WL, Huang Q, Wang YP, Feng YK, Wang XJ, and Zhang FM, 2017. Improving the ability of the photochemical reflectance index to track canopy light use efficiency through differentiating sunlit and shaded leaves. Remote Sensing of Environement, 194:1-15.
87. Wang J, Chen JM, Ju WM*, Qiu F, Zhang Q, Fang MH, and Chen FG, 2017. Limited effects of water absorption on reducing the accuracy of leaf nitrogen estimation. Remote Sensing, 9, 291; doi:10.3390/rs9030291.
86. Gao L, Zhan WF, Huang F, Quan JL, Lu XM, Wang F, Ju WM, and Zhou J, 2017. Localization or globalization? Determination of the optimal regression window for disaggregation of land surface temperature. IEEE Transactions on Geosciences and Remote Sensing, 55(1):477-490.
85. Wang BJ, and Ju WM*, 2017.Limitations and improvements of the leaf optical properties model leaf incorporating biochemistry exhibiting reflectance and transmittance yields (LIBERTY). Remote Sensing, 9, 431; doi:10.3390/rs9050431
84 Zhou YL, Hilker T, Ju WM, Coops NC, Black TA, Chen JM, and Wu XC, 2017. Modeling gross primary production for sunlit and shaded canopies across an evergreen and a deciduous site in Canada. IEEE Transactions on Geosciences and Remote Sensing, 55(4):1859-1873.
2016
83. Shi XL*, Nie SP, Ju WM, and Yu L, 2016. Climate effects of the globalLand30 land cover dataset on the Beijing center climate model simulations. Science China-Earth Sciences, 59: 1754-1764.
82. Zhan WF*, Huang F, Quan JL, Zhu XL, Gao L, Zhou J, and Ju WM, 2016. Disaggregation of remotely sensed land surface temperature: A new dynamic methodology. Journal of Geophysical Research-Atmospheres, 121, doi:10.1002/2016JD024891.
81. Huang F, Zhang WF, Voogt J, Hu Leiqiu, Wang ZH, Quan JL, Ju WM, Gao Z, 2016. Temporal upscaling of surface urban heat island by incorporating an annual temperature cycle model: A tale of two cities. Remote Sensing of Environemnt, 186:1-12.
80. Liu YB, Xiao JF*, Ju WM, Xu K, Zhou YL, and Zhao YT, 2016. Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield. Environmental Research Letters, 11, doi:10.1088/1748-9326/11/9/094010.
79. Zhou YL, Wu XC, Ju WM*, Chen JM, Wang SQ, Wang HM, Yunan WP, Black TA, Jassal R, Ibrom A, Han SJ, Yan JH, Margolis H, Roupsard O, Li YN, Zhao FH, Kiely G, Starr G, Pavelka M, Montagnani L, Wohlfahrt G, D’Odorico P, Cook D, Arain MA, Bonal D, Beringer J, Blanken PD, Loubet B, Leclerc MY, Matteucci G, Nagy Z, Olejnik J, Paw KT, Varlagin A, 2016. Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites. Journal of Geophysical Research-Biogeosciences, 121: 1045–1072.
78. Jiang F*, Chen JM , Zhou LX, Ju WM, Zhang HF, Machida T, Ciais P , Peters W,Wang HM, Chen BZ, 2016. A comprehensive estimate of recent carbon sinks in China using both top-down and bottom-up approaches. Scientific Reports, 6,DOI: 10.1038/srep22130.
77. Zhang Q, Ju WM, Chen JM*, Wang HM, Yang FT, Fan WL, Huang Q, Zheng T, Feng YK, Zhou YL, He MZ, Qiu F, Wang, XJ, Wang J, Zhang FM, Chou SR, 2015. Ability of the photochemical reflectance index to track light use efficiency for a sub-tropical planted coniferous forest. Remote Sensing, 7(12): 16938-16962.
2015
76. Zhang CH, Ju WM*, Chen JM, Wang XQ, Yang L, Zheng G, 2015. Disturbance- induced reduction of biomass carbon sinks of China's forests in recent years. Environmental Research Letters, 10(11), Doi: 10.1088/1748-9326/10/11/114021.
75. Chen ZQ*, Chen JM, Zheng XG, Jiang F, Qin J, Zhang SP, Yuan WP, Ju WM, Mo G, 2015. Optimizing photosynthetic and respiratory parameters based on the seasonal variation pattern in regional net ecosystem productivity obtained from atmospheric inversion. Science Bulletin, 60(22): 1954-1961.
74. Li DQ, Ju WM*, Lu DS, Zhou YL, Wang HM. Impact of estimated solar radiation on gross primary productivity simulation in subtropical plantation in southeast China
53. Sun SL, Chen HS*, Ju WM, Yu M, Hua WJ, and Yin Y, 2014. On the attribution of the changing hydrological cycle in Poyang Lake Basin, China. Journal of Hydrology, 514: 214-225.
52. Fan WL, Chen JM*, Ju WM, and Nesbitt N, 2014. Hybrid geometric optical radiative transfer model suitable foe forests on slopes. IEEE Transaction on geosciences and remote sensing, 52(9): 5579-5586.
51. Fan WL, Chen JM*, Ju WM, and Zhu GL, 2014. GOST: A geometric-optical model for sloping terrains. IEEE Transaction on geosciences and remote sensing, 52(9): 5469-5482.
50. Zhan WF*, Zhou J, Ju WM, Li MC, Sandholt I, Voogt J, and Yu C, 2014. Remotely sensed soil temperatures beneath snow-free skin-surface using thermal observations from tandem polar-orbiting satellites: An analytical three-time-scale model. Remote Sensing of Environment, 143: 1-14.
2013
49. Mu SJ, Zhou SX, Chen YZ, Li JL*, Ju WM, and Odeh I, 2013.Assessing the impact of restoration-induced land conversion and management alternatives on net primary productivity in Inner Mongolia grassland, China. Global and Planetary Chang,108: 29-41.
48. Fan WL, Ju WM*, and Gu ZJ, 2013. Method for reconstructing the pixel missing region on remote sensing images. Journal of Applied Remote Sensing, 073536-1.
47. Liu YB, Zhou YL*, Ju WM, Chen JM, Wang SQ, He HL, Wang HM, Guan DX, Zhao FH, Li YL, Hao YB, 2013. Evapotranspiration and water yield over China’s landmass from 2000 to 2010. Hydrol. Earth Syst. Sci, 13, 17:4957–4980.
46. Chen JM*, Chen X, and Ju WM, 2013. Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity. Biogeosciences, 10:4879-4896.
45. Sun SL, Chen HS*, Ju WM, Son J, Zhan H,Sun J, and Fang YJ, 2013. Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China. Theoretical and Applied Climatology, 112:169-183.
44. He MZ, Ju WM*, Zhou YL, Chen JM, He HL, Wang SQ, Wang HM, Guan DX, Yan JH, Li YN, Hao YB, Zhao FH, 2013. Development of a two-leaf light use efficiency model for improving the calculation of terrestrial gross primary productivity. Agricultural and Forest Meteorology ,173:28-39.
43. Zhang Z, Jiang H*, Liu JX, Ju WM, Zhang XY, 2013. Effect of heterogeneous atmospheric CO2 on simulated global carbon budget. Global and Planetary Change, 101:33-51.
42. Zhang CH, Ju WM*, Chen JM, Zan M, Li DQ, Zhou YL, Wang XQ, 2013. China’s forest biomass carbon sink based on seven inventories from 1973 to 2008. Climatic Chang, 118: 933-948.
41. Liu YB, Ju WM*, He HL, Wang SQ, Sun R, and Zhang YD, 2013. Changes of net primary productivity in China during recent 11 years using an ecological model driven by MODIS data. Frontier of Earth Sciences, DOI 10.1007/s11707-012-0348-5.
40. Gu ZJ, Ju WM*, Li L, Li DQ, Liu YB, Fan WL, 2013. Using vegetation indices and texture measures to estimate vegetation fractional coverage (VFC) of planted and natural forests in Nanjing City, China. Advances in Space Research, 51:1186-1194.
39.He MZ, Zhou YL, Ju WM*, Chen JM, Zhang L, Wang SQ, Saigusa N, Hirata R, Murayama S, Liu YB, 2013. Evaluation and improvement of MODIS gross primary productivity in typical forest ecosystems of East Asia based on eddy covariance measurements. Journal of Forest Research, 18: 31-40.
2012
38. Liu Y, Liu RG*, Chen JM, Ju WM, 2012. Expanding MISR LAI products to high temporal resolution with MODIS observations. IEEE Transactions on Geosciences and Remote Sensing, 50(10Part1): 3915-3927.
37. Zhou YL, Sun XM*, Ju WM, Wen XF, Guan DX, 2012. Seasonal, Diurnal and wind-direction-dependent variations of the aerodynamic roughness length in two typical forest ecosystems of China. Terrestrial Atmospheric and Oceanic Sciences, 23(2):181-191.
36. Sun XL,Chen HS*, Ju WM, Song J, Li JJ, Ren YJ, and Sun J, 2012. Past and future changes of streamflow in Poyang Lake Basin, Southeastern China. Hydrological Earth System Sciences, 16: 2005-2020.
35. Zhang FM*, Chen JM, Pan YD, Birdsey RA, Shen SH, Ju WM, He LM, 2012. Attributing carbon changes in conterminous U.S. forests to disturbance and non-disturbance factors from 1901 to 2010. Journal of Geophysical Research-Biogeosciences, 117: DOI: 10.1029/2011jg001930.
34. Zhang FM*, Ju WM, Shen SH, Wang SQ, YU GR, Han SJ, 2012. Variations of Terrestrial Net Primary Productivity in East Asia. Terrestrial Atmospheric and Oceanic Sciences, 23(4): 425-437.
33. Gu ZJ, Ju WM*, Liu YB, Li DQ, Fan WL, 2012. Applicability of spectral and spatial information from IKONOS-2 imagery in retrieving leaf area index of forests in the urban area of Nanjing, China. Journal of Applied Remote Sensing, 6,063556.
32. Zhou YL, Ju WM*, Sun XM, Wen XF, and Guan DX, 2012. Significant decrease of uncertainties on sensible heat flux simulation using temporally variable aerodynamic roughness in two typical forest ecosystems of China. Journal of Applied Meteorology, 51(6): 1099-1110.
31. Liu YB, Ju WM*, Chen JM, Zhu GL, Xing BL, Zhu JF, 2012. Spatial and temporal variations of forest LAI in China during 2000-2010. Chinese Science Bulletin, 57(22): 2846-2856.
30. Zhu GL, Ju WM*, Chen JM, Gong P, Xing BL, Zhu JF, 2012. Foliage Clumping Index Over China's Landmass Retrieved From the MODIS BRDF Parameters Product. IEEE Transactions on Geosciences and Remote Sensing, 50(6): 2122-2137.
2011
29. Wang SQ, Zhou L, Chen JM, Ju WM, Feng XF, Wu WX, 2011.Relationships between net primary productivity and stand age for several forest types and their influence on China’s carbon balance. Journal of Environmental Management, 92: 1651-1662.
2010
28. Ju WM*, Chen JM, Black TA, Barr AG, and McCaughey H. 2010. Spatially simulating changes of soil water content and their effects on carbon sequestration in Canada’s forests and wetlands. Tellus 62B: 140-159.
27. Ju WM*, Wang SQ, Yu GR, Zhou YL, and Wang HM, 2010. Modelling the impact of drought on canopy carbon and water fluxes for a subtropical evergreen coniferous plantation in southern China through parameter optimization using an ensemble Kalman filter. Biogeosciences. 7: 845-857.
26. Ju WM*, Gao P, Zhou YL, Chen JM, Chen S, and Li XF, 2010. Prediction of summer grain crop yield with a process-based ecosystem model and remote sensing data for the northern area of Jiangsu Province, China. International Journal of Remote Sensing, 31(6):1573-1587.
25. Ju WM*, Gao P, Wang J, and Zhang XH, 2010. Combing an ecological model with remote sensing and GIS techniques to monitor soil water content of croplands with a monsoon climate. Agricultural Water Management, 97: 1221-1231.
24. Wang J*, Chen JM, Ju WM, Li MC, 2010. IA-SDSS: A-GIS-based land use decision support system with consideration of carbon sequestration. Environmental Modelling and Software ,25: 539-553.
23. Ma RH*, Duan HT, Hu CM, Feng XZ, Li AN, Ju WM, Jiang JH, and Yang GS, 2010. A half-dentury of changes in China’s lakes: Global warning or human influces? Geophysical Research Letters, 37: L24106, doi: 10.1029/2010GL045514.
2009
22. Govind A*, Chen JM, and Ju WM. 2009.Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem. Journal of Geophyscial Research,114: G02006, doi:10.1029/2008JG000728.
2008
21. Chen JM*, Huang S, Ju WM, Goumont-Guay D, Black TA. 2008. Daily heterotrophic respiration model considering the non-linear effect of diurnal temperature variability. Journal of Geophysical Research-Biogeosciences, 114: G01022, doi:10.1029/2008JG000834, 2009.
20. Govind A*, Chen JM, Margolis H, Ju WM, Sonnentag O, and Giasson M-A, 2009. A spatially explicit hydro-ecological modeling framework (BEPS-TerranLab V2.0): Model description and test in a boreal ecosystem in Eastern North America. Journal of Hydrology ,367: 200-216.
19. Sonnentag O*, Chen JM, Ju WM, and A Govind, 2008. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography. Journal of Geophysical Research, 113: G02005, doi: 10.1029/2007JG000605.
18. Mo XG*, Chen JM, Ju WM, and Black TA, 2008. Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filer. Ecological Modelling, 217: 157-173.
17. Ju WM* and Chen JM, 2008. Simulating the effects of past changes in climate, atmospheric composition, and fire disturbance on soil carbon in Canada’s forests and wetlands. Global biogeochemical Cycles, 22, GB3010, doi:10.1029/2007GB002935.
2007
16. Chen B*，Chen JM, and Ju WM , 2007. Remote sensing-based ecosystem-atmosphere simulation scheme (EASS)-Model formulation and test with multiple-year data.Ecological Modell ing, 2007, 209: 277-300.
15. Wang SQ*, Chen JM, Ju WM, Feng XF, Chen MZ, Chen PQ, and Yu GR., 2007. Carbon sinks and sources of China’s forests during 1901-2001. Journal of Environmental Management, 85: 524-537.
14. Ju WM*, Chen JM, Harvey D, and Wang S, 2007. Future carbon balance of China’s forests under climate change and increasing CO2. Journal of Environmental Management, 85: 538-562.
13. Caldwell I, Maclaren V*, Chen JM, Ju WM, Zhou S, and Yin Y, 2007. An integrated assessment model of carbon sequestration benefits: a case study of Liping County, China. Journal of Environmental Management, 85: 757-773.
12. Chen XF, Chen JM*, An SQ, and Ju WM, 2007. Effects of topography on simulating net primary productivity at landscape scale. Journal of Environmental Management, 85: 585-596 .
11. Zheng G*, Chen JM, Tian QJ, Ju WM, and Xia XQ, 2007. Combing remote sensing imagery and forest age inventory for biomass mapping, Journal of Environmental Management, 85: 616-623.
10. Shao YH, Pan JJ*, Yang LX, Chen JM, Ju WM, and Shi XZ, 2007. Validation of soil organic carbon density using the InTEC model. Journal of Environmental Management, 85: 696-701).
9. Feng XF*, Liu GH, Chen JM, Chen MZ, Liu J, Ju WM, Sun R, Zhou W, 2007. Simulating net primary productivity of terrestrial ecosystems in China. Journal of Environmental Management, 85: 562-575.
8. Yang LX, Pan JJ*, Shao YH, Chen JM, Ju WM, Shi XZ, Yuan SF, 2007. Soil organic decomposition and carbon pools in temperate and sub-tropical forests in China. Journal of Environmental Management, 85: 690-695.7.
2006
7. Ju WM*, Chen JM, Black TA, Barr AG, Liu J, and Chen B, 2006. Modelling multi-year coupled carbon and water fluxes in a boreal aspen forest. Agricultural and Forest Meteorology, 140: 136-151.
6. Ju WM*, Chen , JMBlack TA, Barr AG, McCaughey H, and Roulet NT, 2006. Hydrological effects on carbon cycles of Canada’s forests and wetlands. Tellus 58B: 16-30.
2005
5. Wang QF*, Niu D, Yu GR, Ren CY, Wen XF, Chen JM, and Ju WM, 2005. Simulating the exchanges of carbon dioxide, water vapor and heat over Changbai Mountains temperate broadleaved Korean pine mixed forest ecosystem. Science in China Series, D48: 148-159 Supp l.1.
4. Ju WM*, Chen JM, 2005. Distribution of soil carbon stocks in Canada’s forests and wetlands simulated based on drainage class, topography and remotely sensed vegetation parameters. Hydrological Processes, 19: 77-94.
3. Chen JM*, Chen X, Ju WM ,Geng, X, 2005. Distributed hydrological model for mapping evapotranspiration using remote sensing inputs. Journal of Hydrology, 305: 15-39.
2. Chen JM, Ju WM*, Cihlar J, Price D, Liu J, Chen WJ, Pan J, Blcak A and Barr A, 2003, Spatial distribution of carbon sources and sinks in Canada’s forests. Tellus 55B: 622-641.
2000
1. Jin L*, Ju WM, and Miao QL, 2000. Study on ANN-based multi-step prediction model of short-term climatic variation. Advances in Atmospheric Sciences 17:157-164.
EI论文
14. Liu YB, Ju WM, He MZ, Zhu GL, Zhou YL, 2012.Decrease of net primary productivity in China's terrestrial ecosystems caused by severe droughts in 2009. Proceedings of the 2nd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2012, 59-63.
13. Xu JH, Ju WM, Hu ZW, 2012.Object-oriented land cover classification of HJ-1B CCD image through multiple classifier fusion. Proceedings –the 20th International Conference on Geoinformatics, Geoinformatics 2012.
12. Zhu YJ,Ju WM, Zhou YL.2011.Impacts of ice storm on forest gross primary productivity detected using multi-source remote sensing data.Proceedings of Geoinformatics 2011.
11. Fang WL,Chen JM,Ju WM.2011. A pixel missing patch inpainting method for remote sensing image.Proceedings of Geoinformatics 2011.
10. Li DQ,Li XF,Ju WM.2011.Interaction between water and carbon cycles in Lushui River simulated using an ecological model driven by remote sensing. Proceedings of Geoinformatics 2011.
9. Ma JD,Ju WM.2011. Mapping leaf index for the urban area of Nanjing city, China using IKONOS remote sensing data. Proceedings of Geoinformatics 2011.
8. Zhu GL, Ju WM, Chen JM, Zhou YL, Li XF, Xu XX. Comparison of Forest Leaf Area Index Retrieval Based on Simple Ratio and Reduced Simple Ratio. 2010, Proceedings of Geoinformatics 2010.
7. Xing BL, Ju WM, Zhou YL, Zhu GL, Li XF, Liu YB, Zhu JF. The Comparison of different methods to measure leaf area index of forests in Maoershan Mountain, northeastern China. 2010, Proceedings of Geoinformatics 2010 .
6. Zhu JF, Ren Y, Ju WM. Effects of land cover types and forest age on evapotranspiration detected by remote sensing in Xiamen City, China. 2010, Proceedings of Geoinformatics 2010.
5. He MZ, Zhou YL, Liu GH, Weimin Ju, Li XF, Zhu GL. Validation of MODIS gross primary productivity for a subtropical coniferous plantation in southern China. 2010, Proceedings of Geoinformatics 2010.
4. Wang J, Ju WM, Li MC, 2009. Characterizing urban growth of Nanjing, China, by using multi-stage remote sensing images and landscape metrics. Proceedings of 2009 Urban Remote Sensing Joint Event .
3. Ju WM, Gao P, Wang J, Li XF, and Chen S, 2008. Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands. Proceedings of SPIE 0277-786X, v.7145, 714517, Geoinfomatics 2008 and Joint Conference on GIS and Built Environment.
2. Zhang CL, Yu H, Gong P, Ju WM, and Pei H, 2008. Remote sensing-based study on the relationship between land brightness temperature and vegetation abundance in Wuhan city. Proceedings of SPIE 0277-786X, v.7147, dx.doi.org/10.1117/12.8133251 Geoinfomatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images.
1. Wang J, Chen JM, Li MC, Ju WM, 2007. GIS-based integrated assessment and decision support system for land use planning in consideration of carbon sequestration benefits.. Proceedings of SPIE 0277-786X, v.6754, Geoinfomatics 2007 : Geospatial information Technology and Applications.
中文论文
60.张乾，居为民*，杨凤婷，曹林，冯永康，2016. 森林冠层多角度高光谱观测系统的实现与分析.南京林业大学学报（自然科学版），40(3): 101-107.
59.康婷婷，居为民*，张春华，2016.2001-2011年中国农田最大光能利用率参数时空变化特征.遥感技术与应用，31（4）：663-672.
58.杨琳，高苹，居为民*，2016.基于MODIS NDVI数据的江苏省冬小麦物候期提取.江苏农业科学，44（1）：315-320.
57.贺巧宁，王怀清，孔萍，戴声佩，杨琳，居为民，2016.江西省森林活动的时空变化及其对干旱的响应. 江西农业学报，28（2）：78-84.
56.李登秋，张春华，居为民，刘丽娟,2016.江西省森林净初级生产力动态变化特征及其驱动因子分析.植物生态学报，40（7）：643-657.
55.柳艺博，王怀清，居为民，2016.干旱对江西省森林生产力的影响特征.自然灾害学报，25（3）：67-76.
54.马利霞，郑光，何维，居为民，程亮，2015.叶方向3维空间分布的地面激光雷达反演与分析.遥感学报，19（4）：609-617.
53.康婷婷，居为民*，李秉柏，2015.水稻叶面积指数遥感反演方法对比分析.江苏农业科学，43（5）：366-371.
52. 康婷婷,高苹,居为民*,黄金龙,2014. 江苏省农作物最大光能利用率时空特征及影响因子. 生态学报，34(2): 410-420.
51.李登秋,周艳莲, 居为民,王辉民,柳艺博,吴小翠,2014. 太阳辐射变化对亚热带人工常绿针叶林总初级生产力影响的模拟分析.植物生态学报 ,2014, 38 (3): 219–230.
50.昝梅,李登秋，居为民，王希群，陈蜀江,2013.新疆喀纳斯国家自然保护区植被叶面积指数观测与遥感估算. 生态学报, 33 (15):4744-4757.
48.昝梅，李登秋，居为民，王希群, 2013. 基于HJ-CCD影像数据的新疆喀纳斯自然保护区植被叶面积指数估算. 冰川冻土, 35(4):1-10.
47.黄金龙， 居为民，郑光，康婷婷, 2013. 基于高分辨率遥感影像的森林地上生物量估算. 生态学报，33(20): 6497-6508.
46.朱高龙，柳艺博，居为民，陈镜明，2013. 4种常用植被指数的地形效应评估. 遥感学报，17(1): 222-234.
45.吴国训，阮宏华，李显风，居为民，耿君，2013. 基于MODIS反演的2000-2011年江西省植被叶面积指数时空变化特征. 南京林业大学学报(自然科学版)，37(1): 11-17.
44.张春华，王宗明，居为民，任春颖, 2012. 松嫩平原玉米带农田土壤氮密度时空格局.应用生态学报, 23(4):1220-1229.
43. 张方敏, 居为民, 陈镜明, 王绍强, 于贵瑞, 韩士杰, 2012. 基于遥感和过程模型的亚洲东部陆地生态系统初级生产力分布特征. 应用生态学报, 23(2):307-318.
42. 邢白灵，居为民，朱高龙，柳艺博，朱敬芳，何明珠,2012.呼伦贝尔草原植被覆盖度地面实测与遥感估算研究.江西农业学报, 24(5): 142-147.
41. 刘昭，周艳莲，居为民,高平,2011. 基于BEPS生态模型模拟农田土壤水分动态模拟.农业工程学报，27(3):67-72.
40.刘昭，周艳莲，居为民,高平,2011. 基于集合卡尔曼滤波同化方法的农田土壤水分模拟.应用生态学报，22(11):2943-2593.
39.张春华，王宗明，居为民,任春颖,2011.松嫩平原玉米带土壤碳氮比的时空变异特征，环境科学，32(5):1407-1414.
38.朱高龙，李明泽，居为民，陈镜明，吴中忠,2011.HJ-1CCD与Landsat-5 TM在森林叶面积指数反演中的比较分析. 东北林业大学学报，39(1):127-130.
37.陈崇，朱延钧，居为民，2011.基于赤池信息准则和人工神经网络的亚热带森林郁闭度遥感估算.江西农业学报，23（5）：149-153.
36.陈崇，朱延钧，李显风，居为民, 2011. 不同叶面积指数遥感反演方法对红壤丘陵区森林的适用性分析. 江西农业大学学报, 33（3）：0508-0513.
35.朱敬芳，邢白灵，居为民，朱高龙，柳艺博，2011.内蒙古草原植被覆盖度遥感估算，植物生态学报，35(6): 615-622.
34.朱高龙, 居为民, 陈镜明, 柳艺博, 朱敬芳, 邢白灵,2011. 利用POLDER数据验证MODIS BRDF模型参数产品及Ross-Li模型. 遥感学报, 15, 875-894.
33.柳艺博, 居为民, 朱高龙, 陈镜明, 邢白灵, 朱敬芳, 周艳莲,2011. 内蒙古不同类型草地叶面积指数遥感估算. 生态学报, 31, 5159-5170.
32.张方敏，居为民，陈镜明，王绍强，于贵瑞，李英年，韩士杰， J.Asanuma,2010.基于BEPS生态模型对亚洲东部地区蒸散量的模拟.自然资源学报，25(9):1596-1606.
31朱高龙，居为民，JingM. Chen，范文义，周艳莲，李显风，李明泽, 2010.帽儿山地区森林冠层叶面积指数的地面观测与遥感反演.应用生态学报, 21(8):2117-2124.
30.张琳琳，孔繁花，尹海伟，孙振如，庄艳美，居为民, 2010. 基于景观空间指标与移动窗口的济南城市空间格局变化. 生态学杂志, 29(8): 1591-1598.
29.李显风，居为民，陈姝，周艳莲, 2010.地表覆盖分类数据对区域森林叶面积指数反演的影响. 遥感学报,14(5):974-989.
28.曾凯，居为民，涂良瑛，王尚明，张崇华，张清霞,2010.2006—2007年南昌市城郊地带的酸雨特征.农业环境科学学报，29(3):609-612.
27.陈　姝，居为民, 2010,. 常熟市土地利用覆盖变化研究.江苏农业科学, 1: 352-355.
26.周蕾，王绍强，陈镜明，冯险峰，居为民，伍卫星，2009.1991年至2000年中国陆地生态系统蒸散时空分布特征. 资源科学,31(6):962-972.
25.陈新芳，居为民，陈镜明，任立良，陆地生态系统碳水循环的相互作用及其模拟，生态学杂志，28(8):1630-1639.
24.曾凯，王尚明，张崇华，胡逢春，张清霞，居为民，2009，南方稻田生态系统产量形成期CO2通量的研究，中国农学通报，25(15):219-222.
23.张春玲，余华，宫鹏，居为民，基于遥感的土地利用空间格局分布与地表温度的关系，遥感技术与应用，23(4): 378-384.
22.郑光，田庆久，陈镜明，居为民，夏学齐，2006，结合树龄信息的遥感森林生态系统生物量制图，遥感学报，10(6):932-941.
21.高苹，居为民，武金岗，吴洪颜，2002，气象型病虫害预报系统，江苏农业科学，3: 45-48.
20.高苹，居为民，陈宁，金龙，2001.人工神经网络在赤霉病预报中的应用研究. 中国农业气象, 21(4), 21-24.
19.居为民，高苹，武金岗，2001. 太湖地区小麦赤霉病与南方涛动的关系及其预报, 科技通报, 17(3), 22-26.
18.居为民，高苹，陈宁，金龙，2000，神经网络预报模型参数对赤霉病预报精度的影响，气象，26(12), 12-15.
17.居为民，高苹，2000，气象条件对小麦纹枯病发生影响的研究，气象，26(2), 50-53.
16.张旭辉，居为民，2000，近40年江苏省干旱发生规律的研究，灾害学，15(3), 42-45.
15.居为民，高苹，武金岗，2000，菌核病预报方法的预计，植保技术与推广，20(1), 4-6.
14.居为民，高苹，武金岗，2000，气候条件对麦类纹枯病发生趋势影响的研究，植物保护，26(2), 20-22.
13.张中义，刘聪，居为民，2000，南京长江二桥设计风速计算，气象科学，20(2), 200-205.
12.居为民，高苹，2000，赤道太平洋海温异常与太湖地区赤霉病，气象科学，20(4), 511-515.
11.徐萌，居为民，唐勇，1999，应用遥感图像城市惹到效应检测沪宁高速公路大雾，遥感信息, 14, 45-46.
10.孙涵，居为民，1998，气象卫星遥感在农业上应用效益回顾，地方遥感协会年会文集，宇航出版社.
9. 高苹，居为民，1998小麦赤霉病长期预报模型，气象，23(6), 55-57.
8. 孙涵，居为民，汤志成，1997，应用气象卫星遥感资料监测江苏洪涝灾害，地方遥感协会年会文集，宇航出版社.
7. 孙涵，居为民，汤志成，1997，江苏省气象卫星遥感业务系统，地方遥感协会年会文集，宇航出版社.
6. 孙涵，居为民，汤志成，1997，气象卫星遥感业务系统(V3.2)简介，气象，23(12), 18-20.
5. 居为民，孙涵，张中义，徐萌，1997，气象卫星遥感资料在沪宁高速公路大雾检测上的初步应用，遥感信息，13,25-27.
4. 居为民，孙涵，汤志成，1997，应用气象卫星遥感估计洪涝面积，气象科学，17(2), 131-136.
3. 居为民，孙涵，汤志成，1996，应用气象卫星遥感监测干旱，灾害学，11(4),25-29.
2.孙涵，居为民，汤志成，1995，在微机上实现气象卫星遥感与地理信息系统一体化，南京气象学报增刊.
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江苏地理信息技术重点实验室副主任
Journal of Geophysical Research-Associate Editor