孙亮

孙亮研究员，中国农业科学院青年英才计划入选者。毕业于北京师范大学地图学与地理信息系统专业，2015年-2018年于美国农业部水文遥感实验室工作。目前主要研究方向为基于多源遥感数据融合开展近实时农情监测与预测研究。共计发表SCI论文30余篇，其中第一\通讯作者身份20余篇。

教育/工作经历

2018至今，研究员，中国农业科学院，农业资源与农业区划研究所

2015-2018，博士后，美国农业部水文遥感实验室

2012-2015，博士后，中国农业科学院，农业资源与农业区划研究所

2010-2012，博士后，北京师范大学，全球变化与地球系统科学研究院

2005-2010，博士，北京师范大学  专业：地图学与地理信息系统

2001-2005，本科，中国地质大学（北京）  专业：土地资源管理

研究方向

1.近实时农情监测与预测；

2.多源遥感数据融合算法及应用；

3.时序遥感数据信息提取。

主要科研项目

国家重点研发计划—粮食生产大数据平台研发与应用（“玉米生产全程大数据挖掘与智能分析算法”课题负责人，2023-2028）

农牧交错带休耕与撂荒耕地监测方法研究及其质量评价（所重点基金，主持，2023）

国家重点研发计划—农情信息空天地高精度高时效智能监测系统研发与应用（“农情异常风险主动感知技术研究”子课题负责人，2022-2027）

苹果花期预报及生物量估算（技术开发类，主持，2021-2023）

高分辨率对地观测系统重大专项（民用部分）应用示范系统项目（骨干，2021-2023）

高分航空载荷农田利用与保护应用示范（骨干，2021-2022）

国际杰青计划外国青年科学家来华工作（主持，2019-2021）

风云三号03批卫星工程(重庆)（技术开发类，主持，2020）

基于MODIS数据的地温重建技术应用（技术开发类，主持，2020）

国家自然科学青年基金“基于地表温度-植被指数特征空间进行土壤水分监测研究（主持，2014-2016）

农业部农业信息技术重点实验室开放基金“农田水量平衡遥感估算研究”（主持，2013-2014）

遥感科学国家重点实验室重点基础研究类课题“水循环关键要素的遥感模拟与反演”（主持，2012-2014）

第一/通讯作者代表论文

Sun, L.*, Gao, F., Xie, D., Anderson, M., Chen, R., Yang, Y., ... & Chen, Z. (2021). Reconstructing daily 30 m NDVI over complex agricultural landscapes using a crop reference curve approach. Remote Sensing of Environment, 253, 112156.

Crusiol, L. G. T., Sun, L*., et al, (2023). Assessing the sensitive spectral bands for soybean water status monitoring and soil moisture prediction using leaf-based hyperspectral reflectance. Agricultural Water Management.

Liu, Y., Sun, L*., Liu, B., Wu, Y., Ma, J., Zhang, W., Wang, B., (2023). Estimation of Winter Wheat Yield Using Multiple Temporal Vegetation Indices Derived from UAV-Based Multispectral and Hyperspectral Imagery. Remote Sensing. 15(19):4800.

Wuyun, D., Sun, L*., Chen, Z., Hou, A, Crusiol, L, & Yu, L., et al. (2022). The spatiotemporal change of cropland and its impact on vegetation dynamics in the farming-pastoral ecotone of northern China. Science of The Total Environment, 805, 150286.

Wuyun, D., Sun, L.*, Sun, Z., Chen, Z., Hou, A., Teixeira Crusiol, L. G., & Zhao,H. (2022). Mapping fallow fields using Sentinel-1 and Sentinel-2 archives over farming-pastoral ecotone of Northern China with Google Earth Engine. GIScience & Remote Sensing, 59(1): 333-353.

Crusiol, L. G. T., Sun, L*., Sibaldelli, R. N. R., Junior, V. F., Furlaneti, W.X., Chen, R., ... & Farias, J. R. B. (2022). Strategies for monitoring within-field soybean yield using Sentinel-2 Vis-NIR-SWIR spectral bands and machine learning regression methods. Precision Agriculture,1-31.

Crusiol, L. G. T.., Sun, L*., Chen, R., Sun, Z., Zhang, D., Chen, Z., & Bouças Farias, J. R. (2021). Assessing the potential of using high spatial resolution daily NDVI-time-series from planet CubeSat images for crop monitoring. International Journal of Remote Sensing, 42(18), 7114-7142.

Yongqian W, Dejun Z, Sun, L*, et al. (2021). Evaluating FY3C-VIRR reconstructed land surface temperature in cloudy regions. European Journal of Remote Sensing, 2021, 54(1): 266-280.

Yang, S., Zhang, D., Sun, L*., Wang, Y., & Gao, Y. (2020). Assessing drought conditions in cloudy regions using reconstructed land surface temperature. Journal of Meteorological Research, 34, 264-279.

Sun, L., Anderson, M. C., Gao, F., Hain, C., Alfieri, J. G., Sharifi, A., ... & McKee, L. (2017). Investigating water use over the C hoptank R iver W atershed using a multisatellite data fusion approach. Water Resources Research, 53(7), 5298-5319.

Sun, L., Chen, Z., Gao, F., Anderson, M., Song, L., Wang, L., ... & Yang, Y. (2017). Reconstructing daily clear-sky land surface temperature for cloudy regions from MODIS data. Computers & Geosciences, 105, 10-20.

Sun, L., Gao, F., Anderson, M. C., Kustas, W. P., Alsina, M. M., Sanchez, L., ... & Post, K. (2017). Daily mapping of 30 m LAI and NDVI for grape yield prediction in California vineyards. Remote Sensing, 9(4), 317.

Sun, L., Liang, S., Yuan, W., & Chen, Z. (2013). Improving a Penman–Monteith evapotranspiration model by incorporating soil moisture control on soil evaporation in semiarid areas. International Journal of Digital Earth, 6(sup1), 134-156.

Sun, L., Sun, R., Li, X., Liang, S., & Zhang, R. (2012). Monitoring surface soil moisture status based on remotely sensed surface temperature and vegetation index information. Agricultural and Forest Meteorology, 166, 175-187.

Sun Liang, Sun Rui, LI Xiaowen. （2011）.Estimating Evapotranspiration Using Improved Fractional Vegetation Cover and Land Surface Temperature Space, Journal of Resources and Ecology, 2(3): 289-299.

孙亮，陈仲新，应用Penman-Monteith公式和土壤湿度指数估算区域地表蒸散，农业工程学报，2013，29 (10)：101-108.

孙亮，孙睿，杨世琦，李小文，利用MODIS数据计算地表蒸散，农业工程学报，2009,25：23-28.

孙亮，孙睿，贾成刚，等，MODIS数据反演地表温度劈窗算法比较，北京师范大学学报(自然科学版)，2008，44：434-438.

合作学术论文

Xie, D., Gao, F., Sun, L., & Anderson, M.. (2018). Improving spatial-temporal data fusion by choosing optimal input image pairs. Remote Sensing, 10(7).

Yang Yang,Martha C. Anderson,Feng Gao,Brian Wardlow,Christopher R. Hain,Jason A. Otkin,Joseph Alfieri,Yun Yang,Liang Sun,Wayne Dulaney.（2018） Field-scale mapping of evaporative stress indicators of crop yield: An application over Mead, NE, USA. Remote Sensing of Environment,210 ,387-402.

Zhu, W., Lv, A., Jia, S., Sun, L.,(2017). Development and evaluation of the MTVDI for soil moisture monitoring. Journal of Geophysical Research: Atmospheres, 122, 5533–5555.

Yang, Y., Anderson, M., Gao, F., Hain, C., Kustas, W., Meyers, T., Crow, W., Finocchiaro, R., Otkin, J., Sun, L., Yang, Y.（2017）. Impact of Tile Drainage on Evapotranspiration in South Dakota , USA , Based on High Spatiotemporal Resolution Evapotranspiration Time Series From a Multisatellite Data Fusion System. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, PP (6)1-15.

Yao, Y., Liang, S., Yu, J., Chen, J., Liu, S., Lin, Y., Fisher, J. B., McVicar, T. R., Cheng, J., Jia, K., Zhang, X., Xie, X., Jiang, B. and Sun, L.,(2017). A simple temperature domain two-source model for estimating agricultural field surface energy fluxes from Landsat images, Journal of Geophysical Research: Atmospheres, 122(10), 5211–5236.

Yao, Y., Liang, S., Yu, J., Zhao, S., Lin, Y., Jia, K., Zhang, X., Cheng, J., Xie, X., Sun, L., Wang, X. and Zhang, L.,(2017). Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms, International Journal of Applied Earth Observation and Geoinformation, 56, 1–12.

Li, H., Chen, Z., Jiang, Z., Sun, L., Liu, K. and Liu, B.,(2015). Temporal-spatial variation of evapotranspiration in the Yellow River Delta based on an integrated remote sensing model, Journal of Applied Remote Sensing, 9(1), 96047.

Chen, Y., Xia, J., Liang, S., Feng, J., Fisher, J.B., Li, X., Li, X., Liu, S., Ma, Z., Miyata, A., Mu, Q., Sun, L., Tang, J., Wang, K., Wen, J., Xue, Y., Yu, G., Zha, T., Zhang, L., Zhang, Q., Zhao, T., Zhao, L., & Yuan, W. (2014). Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China. Remote Sensing of Environment, 140, 279-293.

Jiang, Z., Chen, Z., Chen, J., Liu, J., Ren, J., Li, Z., Sun, L. and Li, H.,(2014). Application of Crop Model Data Assimilation With a Particle Filter for Estimating Regional Winter Wheat Yields, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(11), 4422–4431.

Jiang, Z., Chen, Z., Chen, J., Ren, J., Li, Z. and Sun, L.,(2014). The estimation of regional crop yield using ensemble-based four-dimensional variational data assimilation, Remote Sensing, 6(4), 2664–2681.

Yao, Y. J., Liang, S. L., Li, X. L., Hong, Y., Fisher, J. B., Zhang, N. N., Chen, J. Q., Cheng, J., Zhao, S. H., Zhang, X. T., Jiang, B., Sun, L., Jia, K., Wang, K. C., Chen, Y., Mu, Q. Z. and Feng, F.,(2014). Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations, Journal of Geophysical Research: Atmospheres, 119(8), 4521–4545.

姚云军，程洁，赵少华，贾坤，谢先红，孙亮，基于热红外遥感的农田蒸散估算方法研究综述，地球科学进展，2012,27(12):1308-1318.

张廷龙，孙睿，胡波，党一诺，孙亮，北京西北部典型城市化地区不同土地利用类型土壤碳特征分析，北京师范大学学报（自然科学版），2010,46（1）：97-102.

胡波, 孙睿, 陈永俊, 冯丽超, 孙亮，遥感数据结合Biome-BGC模型估算黄淮海地区生态系统生产力，自然资源学报, 2011,26(12),2061-2071.

张廷龙, 孙睿, 胡波, 党一诺, 孙亮，北京西北部典型城市化地区不同土地利用类型土壤碳特征分析，北京师范大学学报(自然科学版),2010,46(1), 97-102.

专利

孙亮，王钊，孙政，权文婷。基于作物参考曲线和积温校正的苹果的始花期预测方法，2023. 专利号：ZL 202210823946.2

孙亮，张德军，杨世琦，陈仲新。一种云下像元真实地表温度重建方法，2022.4， 专利号：CN201910609171.7

孙亮，王晨丞，杨世琦，王永前。一种基于数据挖掘的地表温度降尺度方法，2022.1，专利号：CN202110878728.4

Sun Liang，Zhang Dejun，Yang Shiqi，Chen Zhongxin. Method for reconstructing true land surface temperature of cloudy pixel.2020.7，澳大利亚，专利号：2020101048

孙亮，陈瑞卿，谢东辉，陈仲新。基于作物参考曲线进行高时空分辨率植被指数数据融合的方法与流程，2019.12，中国专利批准号：CN201911217214.3

专著

Tang Huajun, Li Zhao-Liang, Quantitative Remote Sensing in Thermal Infrared-Theory and Application. Berlin, Springer Berlin Heidelberg, 2014（编写 Chapter 7）

通信地址：北京市海淀区中关村南大街12号，资源楼507

邮箱：sunliang@caas.cn