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（1）北非地區(qū)水資源及農(nóng)業(yè)用水監(jiān)測(cè)與評(píng)估，“一帶一路”國(guó)際科學(xué)組織聯(lián)盟項(xiàng)目，負(fù)責(zé)人，2022-2025。

（2）全球陸地生態(tài)系統(tǒng)耗水及水分利用效率估算方法及產(chǎn)品，可持續(xù)發(fā)展大數(shù)據(jù)國(guó)際研究中心卓越科學(xué)家項(xiàng)目，負(fù)責(zé)人，2022-2024。

（3）陸地水循環(huán)關(guān)鍵參量時(shí)空多尺度智慧化遙感，國(guó)家自然基金委重大基金項(xiàng)目課題，負(fù)責(zé)人，2021-2025.

（4）西風(fēng)-季風(fēng)作用區(qū)非均勻下墊面地氣相互作用機(jī)載通量觀測(cè)試驗(yàn)研究，科技部“第二次青藏高原綜合科學(xué)考察研究”專項(xiàng)子專題，負(fù)責(zé)人，2019-2024。

（5）一帶一路水循環(huán)要素監(jiān)測(cè)，中國(guó)科學(xué)院戰(zhàn)略性先導(dǎo)專項(xiàng)(A類)“地球大數(shù)據(jù)科學(xué)工程”項(xiàng)目子課題，負(fù)責(zé)人，2018-2022。

（6）OPERANDUM: OPEn-air laboRAtories for Nature baseD solUtions to Manage environmental risks, 歐盟地平線2020計(jì)劃項(xiàng)目，Co-PI, 2018-2022.

（7）薩赫勒地區(qū)土地覆蓋與土地利用變化驅(qū)動(dòng)機(jī)制及其影響， 國(guó)家自然科學(xué)基金國(guó)際(地區(qū))合作與交流項(xiàng)目，負(fù)責(zé)人，2017-2021。

（8）Satellite Observations For Improving Irrigation Water Management (Sat4IrriWater), 中歐龍計(jì)劃合作第五期項(xiàng)目，負(fù)責(zé)人，2020-2024。

（9）冰凍圈與陸表水循環(huán)遙感，科技部-國(guó)家外國(guó)專家局項(xiàng)目，負(fù)責(zé)人，2016-2019。

（10）高亞洲典型環(huán)境要素?cái)?shù)據(jù)集產(chǎn)品生成研究，中國(guó)科學(xué)院《泛第三極環(huán)境與“一帶一路”協(xié)同發(fā)展》項(xiàng)目專題，負(fù)責(zé)人，2016-2020。

（11）高分辨率陸表能量水分交換過程的機(jī)理與尺度轉(zhuǎn)換研究，國(guó)家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃項(xiàng)目課題, 負(fù)責(zé)人，2015-2019。

（12）地球系統(tǒng)過程的空間信息模擬，中國(guó)科學(xué)院“一三五”規(guī)劃重點(diǎn)培育方向項(xiàng)目，負(fù)責(zé)人，2013-2015。

（13）黑河流域水-生態(tài)-經(jīng)濟(jì)系統(tǒng)的集成模擬與預(yù)測(cè)，國(guó)家自然科學(xué)基金重大研究計(jì)劃《黑河流域生態(tài)-水文過程集成研究》項(xiàng)目，參加，2015-2018。

（14）基于遙感和數(shù)據(jù)同化的黑河中-下游植被與陸表水循環(huán)的相互作用研究, 國(guó)家自然科學(xué)基金面上項(xiàng)目，負(fù)責(zé)人, 2011-2013。

（15）亞歐合作長(zhǎng)期觀測(cè)系統(tǒng)－通過地面/衛(wèi)星觀測(cè)和數(shù)值模擬研究青藏高原水文氣象過程和亞洲季風(fēng)的關(guān)系 (CEOP-AEGIS)，歐盟第七框架項(xiàng)目，負(fù)責(zé)人，2008-2013。

(1)測(cè)繪科學(xué)技術(shù)獎(jiǎng), 一等獎(jiǎng), 部委級(jí), 2021

(2)非均勻下墊面地表蒸散發(fā)觀測(cè)與遙感估算的理論與方法, 二等獎(jiǎng), 部委級(jí), 2017

（1）學(xué)術(shù)論文

[1]Ren S.T., Jia L.*, Menenti M., Zhang J., 2023, Spatiotemporal variability of glacier surface albedo and driving factors in the Western Nyainqentanglha Mountains in 2001–2020, Journal of Hydrology, 603, Part D, 127145. https://doi.org/10.1016/j.jhydrol.2021.127145.

[2]Zeng Y.L., Jia L.*, Menenti M., Jiang M., Asenso Barnieh B., Bennour A., Lv Y.Z., 2023, Changes in vegetation greenness related to climatic and non-climatic factors in the Sudano-Sahelian region, Regional Environmental Change, 23, 92(2023); https://doi.org/10.1007/s10113-023-02084-5.

[3]Asenso Barnieh B.; Jia L.*; Menenti M.; Yu L.; Nyantakyi E.K.; Kabo-Bah A.T.; Jiang, M.; Zhou J.; Lv, Y.; Zeng Y.; et al., 2023, Spatiotemporal Patterns in Land Use/Land Cover Observed by Fusion of Multi-Source Fine-Resolution Data in West Africa. Land, 2023, 12, 1032. https://doi.org/10.3390/land12051032.

[4]Mi P.; Zheng C.*; Jia L.; Bai Y., 2023, Reconstruction of Global Long-Term Gap-Free Daily Surface Soil Moisture from 2002 to 2020 Based on a Pixel-Wise Machine Learning Method. Remote Sens. 2023, 15, 2116. https://doi.org/10.3390/rs15082116.

[5]Bai Y., Jia L., Zhao T.J., 2023, A Soil Moisture Retrieval Method for Weakening Topographic Effect: A Case Study on the Qinghai-Tibetan Plateau with SMOS data, IEEE JSTARS, VOL. 16, 4276-4286; Digital Object Identifier 10.1109/JSTARS.2023.3264572.

[6]Chen Q.T., Jia L.*, Menenti M., Hu G.C., Wang K., Yi Z., Zhou J., Peng F., Ma S.X., You Q., Chen X., Xue X., 2023, A data-driven high spatial resolution model of biomass accumulation and crop yield: application to a fragmented desert-oasis agroecosystem, Ecological Modelling, 2023, 475, 110182; https://doi.org/10.1016/j.ecolmodel.2022.110182.

[7]Bennour A., Jia L.*, Menenti M., Zheng C., et al., 2023, Assessing impacts of climate variability and land use/land cover change on the water balance components in the Sahel using Earth observations and hydrological modelling, Journal of Hydrology: Regional Studies, 47, 101370.

[8]Zheng C., Jia L., Zhao T.J., 2023, A 21-year dataset (2000-2020) of gap-free global daily surface soil moisture at 1- km resolution, Scientific Data, 10:139; https://doi.org/10.1038/s41597-023-01991-w.

[9]Jiang M., Jia L.*, Menenti M., Zeng Y., 2022, Understanding spatial patterns in the drivers of greenness trends in the Sahel-Sudano-Guinean region, Big Earth Data, 1-20; https://doi.org/10.1080/20964471.2022.2146632.

[10]Yi Z., Jia L., Chen Q.*, Jiang M., Zhou D., Zeng Y., 2022, Early-season crop identification in the Shiyang River Basin using a deep learning algorithm and time-series Sentinel-2 data, Remote Sensing, 14(21), 5625; https://doi.org/10.3390/rs14215625.

[11]Khuong H Tran, Massimo Menenti, Li Jia, 2022, Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold, Remote Sensing, 14(22), 5721; DOI: 10.3390/rs14225721.

[12]Xie Q.X., Jia L.*, Menenti M., Hu G.C., 2022, Global Soil Moisture Data Fusion by Triple Collocation Analysis from 2011 to 2018, Scientific Data, 2022, 9:687; https://doi.org/10.1038/s41597-022-01772-x.

[13]Zheng C.L.*, Jia L.*, Hu G.C., 2022, Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations, Journal of Hydrology, 2022, 128444; https://doi.org/10.1016/j.jhydrol.2022.128444.

[14]Bai Y., Zhao T.J.*, Jia L.*, Cosh M. H, Shi J.C., Zhiqing Peng, Xiaojun Li, Jean-Pierre Wignerone, 2022, A multi-temporal and multi-angular approach for systematically retrieving soil moisture and vegetation optical depth from SMOS data, 2022, 280, 113190; https://doi.org/10.1016/j.rse.2022.113190.

[15]Lu J., L. Jia, J. Zhou, M. Jiang, Y. Zhong, M. Menenti, 2022, Quantification and Assessment of Global Terrestrial Water Storage Deficit Caused by Drought Using GRACE Satellite Data, IEEE JSTARS, 15, 5001-5012; doi: 10.1109/JSTARS.2022.3180509.

[16]Du, D.; Zheng, C.; Jia, L.*; Chen, Q.; Jiang, M.; Hu, G.; Lu, J. Estimation of Global Cropland Gross Primary Production from Satellite Observations by Integrating Water Availability Variable in Light-Use-Efficiency Model. Remote Sens. 2022, 14, 1722. https://doi.org/10.3390/rs14071722.

[17]Shen C., Jia L.*, Ren S.T., 2022, Inter and Intra Annual Glacier Elevation Change Over High Mountain Asia Based on ICESat-1/2 Data by Elevation-Aspect Bin Analysis Method, Remote Sensing, 2022, 14(7): 1630; DOI: 10.3390/rs14071630.

[18]Bennour A.; Jia L.*; Menenti M.; Zheng,C.; Zeng Y.; Asenso Barnieh B.; Jiang M., 2022, Calibration and validation of SWAT model by using hydrological remote sensing observables in the Lake Chad Basin, Remote Sensing, 2022, 14(6), 1511; https://doi.org/10.3390/rs14061511. Published: 21 March 2022.

[19]Yuan X.T., Jia L.*, Menenti M., Jiang M., 2022, Consistent nighttime light time series in 1992-2020 in Northern Africa by combining DMSP-OLS and NPP-VIIRS data, Big Earth Data, DOI: 10.1080/20964471.2022.2031542.

[20]Barnieh A.B., L. Jia*, M. Menenti, M. Jiang, J. Zhou, Y.Z. Lv, Y.L. Zeng, and A. Bennour, 2022, Quantifying spatial reallocation of land use/land cover categories in West Africa, Ecological Indicators, 135, 108556.

[21]Menenti M., Li X., Jia L., et al., 2021, Multi-Source Hydrological Data Products to Monitor High Asian River Basins and Regional Water Security, Remote Sensing, 2021, 13, 5122. https://doi.org/10.3390/rs13245122.

[22]Zhang J., L. Jia*, M. Menenti, Zhou J, and S.T. Ren, 2021, Glacier Area and Snow Cover Changes in the Range System Surrounding Tarim from 2000 to 2020 Using Google Earth Engine, Remote Sensing, 2021, 13, 5117. https://doi.org/10.3390/rs13245117.

[23]Cui Y., Jia L.*, 2021, Estimation of evapotranspiration of “soil-vegetation” system with a scheme combining a dual-source model and satellite data assimilation, Journal of Hydrology, December 2021, 603, Part D, 127145; https://doi.org/10.1016/j.jhydrol.2021.127145.

[24]Zhou J.*, Li Jia, Massimo Menenti, Xuan Liu, 2021, Optimal estimate of global biome – specific parameter settings to reconstruct NDVI time series with the Harmonic ANalysis of Time Series (HANTS) method, Remote Sensing, 2021, 13, 4251; https://doi.org/10.3390/rs13214251.

[25]Cui Y.K., Jia L., Fan W.J., 2021, Estimation of Actual Evapotranspiration and Its Components in an Irrigated Area by Integrating the Shuttleworth-Wallace and Surface Temperature-Vegetation Index Schemes using the Particle Swarm Optimization Algorithm, Agricultural and Forest Meteorology, May 24, 2021, 307, 108488; https://doi.org/10.1016/j.agrformet.2021.108488.

[26]Shaoting Ren, Evan S. Miles, Li Jia*, Massimo Menenti, Marin Kneib, Pascal Buri, Michael J. McCarthy, Thomas E. Shaw, Wei Yang, Francesca Pellicciotti, 2021, Anisotropy parameterization development and evaluation for glacier surface albedo retrieval from satellite observations, Remote Sensing, 2021, 13, 1714; https://doi.org/10.3390/rs13091714.

[27]Barnieh A.B., L. Jia*, M. Menenti, M. Jiang, J. Zhou, Y.L. Zeng, and A. Bennour, 2021, Modelling the Underlying Drivers of Natural Vegetation’s Occurrence in West Africa with Binary Logistic Regression, Sustainability 2021, 13(9), 4673; https://doi.org/10.3390/su13094673; 22 Apr 2021.

[28]Zhang J., L. Jia*, M. Menenti and S.T. Ren, 2021, Interannual and Seasonal Variability of Glacier Surface Velocity in the Parlung Zangbo Basin, Tibetan Plateau. Remote Sensing, 2021, 13, 80; https://doi.org/10.3390/rs13010080.

[29]Yi ZW; Jia L; Chen QT, 2020, Crop classification using multi-temporal Sentinel-2 data in Shiyang River Basin of China, Remote Sensing, 12, 4052; https://doi.org/10.3390/rs12244052.

[30]Barnieh A.B., L. Jia*, M. Menenti, J. Zhou, Y.L. Zeng, 2020, Mapping Land Use Land Cover Transitions at Different Spatiotemporal Scales in West Africa, Sustainability, 2020, 12, 8565; doi:10.3390/su12208565.

[31]Zhou J., L. Jia*, M. Menenti, M. van Hoek, J. Lu, C.L. Zheng, X.T. Yuan, Characterizing vegetation response to rainfall at multiple temporal scales in the Sahel-Sudano-Guinean region using transfer function analysis, Remote Sensing of Environment, 2021, 252, 112108, https://doi.org/10.1016/j.rse.2020.112108.

[32]Lu J., L. Jia, C. L. Zheng, R. L. Tang, Y. Z. Jiang, A Scheme to Estimate Diurnal Cycle of Evapotranspiration from Geostationary Meteorological Satellite Observations, Water, 2020, 12(9), 2369.

[33]Ren S.T., M. Menenti, L. Jia*, J. Zhang, J. Zhang, X. Li, 2020, Glacier mass balance in the Nyainqentanglha Mountains between 2000 and 2017 retrieved from ZiYuan-3 stereo images and the SRTM DEM, Remote Sensing, 2020, 12, 864; doi:10.3390/rs12050864.

[34]Zheng C.L.*, L. Jia*, 2020, Global canopy rainfall interception loss derived from satellite earth observations, Ecohydrology, https://doi.org/10.1002/eco.2186.

[35]Xie Q., M. Menenti, L. Jia*, 2019, Improving the AMSR-E/NASA soil moisture data product using in-situ measurements in the Tibetan Plateau, Remote Sensing, 2019, 11, 2748; doi:10.3390/rs11232748.

[36]Yuan X.T., L. Jia*, M.Menenti, J. Zhou, X. Yuan, 2019,  Filtering the NPP-VIIRS Nighttime Light Data for improved detection of settlements in developing Africa, Remote Sensing, 2019, 11, 3002; doi:10.3390/rs11243002.

[37]Chen Q., L. Jia*, M. Menenti, R. Hutjes, G. Hu, C. Zheng, K. Wang, 2019, A Numerical Analysis of Aggregation Error in Evapotranspiration Estimates Due to Heterogeneity of Soil Moisture and Leaf Area Index, Agricultural and Forest Meteorology, Volumes 269–270, 15 May 2019, Pages 335-350. https://doi.org/10.1016/j.agrformet.2019.02.017.

[38]van Hoek M, J. Zhou, L. Jia*, J. Lu, C. Zheng, G. Hu and M. Menenti, 2019, A prototype web-based analysis platform for drought monitoring and early warning, International Journal of Digital Earth, DOI: 10.1080/17538947.2019.1585978.

[39]Zhang J., L. Jia*, M. Menenti, and G. Hu, 2019, Glacier Facies Mapping Using a Machine-Learning Algorithm: The Parlung Zangbo Basin Case Study, Remote Sensing, 2019, 11, 452; doi:10.3390/rs11040452. 

[40]Sun Y., L. Jia*, Q. Chen, and C. Zheng, Optimizing Window Length for Turbulent Heat Flux Calculations from Airborne Eddy Covariance Measurements under Near Neutral  to Unstable Atmospheric Stability Conditions, Remote Sensing, 2018, 10, 670; doi:10.3390/rs10050670.

[41]Lu J., L. Jia*, M. Menenti, Y. Yan, C. Zheng, and J. Zhou, 2018, Performance of the Standardized Precipitation Index Based on the TMPA and CMORPH Precipitation Products for Drought Monitoring in China, IEEE  Journal of Selected Topics In Applied Earth Observations And Remote Sensing (IEEE JSTARS), 11(5), 1387-1396; DOI: 10.1109/JSTARS.2018.2810163。

[42]Wang N., L. Jia*, C. Zheng, M. Menenti, 2017, Estimation of subpixel snow sublimation from multispectral satellite observations, Journal of Applied Remote Sensing, 11(4), 046017 (2017), doi: 10.1117/1.JRS.11.046017.

[43]Huang T., L. Jia*, M. Menenti, J. Lu, J. Zhou and G. Hu, 2017, A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat-GLAS Footprints, Sensors, 2017, 17, 1803; doi:10.3390/s17081803.

[44]Lu S., L. Jia, L. Zhang, Y. Wei, M. H. A. Baig, Z. Zhai, J. Meng, X. Li, G. Zhang, 2017, Lake water surface mapping in the Tibetan Plateau using the MODIS MOD09Q1 product, Remote Sensing Letters, 8(3), 224-233, 2017. http://dx.doi.org/10.1080/2150704X.2016.1260178,

[45]Li N.N., L. Jia*, J. Lu, M. Menenti, J. Zhou, 2017, Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semi-arid basin, Journal of Applied Remote Sensing, 11(1), 016028 (Feb 17, 2017). doi: 10.1117/1.JRS.11.016028.

[46]Gao B., H. Gong, T. Wang, and L. Jia, Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition, Remote Sensing, 2016, 8(9), 727; doi:10.3390/rs8090727.

[47]Shang H.L., L. Jia*, M. Menenti*, 2016, Modeling and Reconstruction of Time Series of Passive Microwave Data by Discrete Fourier Transform Guided Filtering and Harmonic Analysis, Remote Sensing, 2016, 8, 970; doi: 10.3390/rs8110970.

[48]Zhou J., Jia L.*, Menenti M., Gorte B., 2016, On the performance of remote sensing time series reconstruction methods – a spatial comparison, Remote Sensing of Environment, 187, 367–384.

[49]Song C., Jia L.*, 2016, A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia, Remote Sensing, 8, 703; doi:10.3390/rs8090703.

[50]Roupioz L., L. Jia, F. Nerry, M. Menenti, 2016, Estimation of Daily Solar Radiation Budget at Kilometer Resolution over the Tibetan Plateau by Integrating MODIS Data Products and a DEM, Remote Sensing, 2016, 8(6), 504; doi:10.3390/rs8060504.

[51]van Hoek M, L. Jia*, J. Zhou, C. Zheng, M., Menenti, 2016, Early Drought Detection by Spectral Analysis of Satellite Time Series of Precipitation and Normalized Difference Vegetation Index (NDVI). Remote Sensing, 8(422): 1-17. doi:10.3390/ rs8050422.

[52]Roupioz L., J. Colin, L. Jia, F. Nerry, and M. Menenti, 2015, Quantify the impact of cloud cover on radiation fluxes ground measurements from hemispherical images, International Journal of Remote Sensing, Vol. 36, Nos. 19–20, 5087–5104, http://dx.doi.org/10.1080/01431161.2015.1084440.

[53]Zhou J., L. Jia*, and M. Menenti, 2015, Reconstruction of Global MODIS Vegetation Index Time Series: Performance of Harmonic ANalysis of Time Series (HANTS), Remote Sensing of Environment, 163, 217-228; 10.1016/j.rse.2015.03.018.

[54]Shang H.L., L. Jia*, M. Menenti, 2015, Analyzing the Inundation Pattern of the Poyang Lake Floodplain by Passive Microwave Data. Journal of Hydrometeorology, 16(2), 652–667; doi: http://dx.doi.org/10.1175/JHM-D-14-0022.1.

[55]Li N.N., L. Jia*, J. Lu, 2015, An improved algorithm to estimate the surface soil heat flux over a heterogeneous surface: a case study in the Heihe River Basin, Science in China, 58(7), 1169-1181; doi: 10.1007/s11430-014-5041-y.

[56]Chen Q.T., L. Jia*, R. Hutjes, M. Menenti, 2015, Estimation of Aerodynamic Roughness Length over Oasis in the Heihe River Basin by Utilizing Remote Sensing and Ground Data, Remote Sensing, 2015, 7(4), 3690-3709; doi:10.3390/rs70403690.

[57]Hu G.C. and L. Jia*, 2015, Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations, Remote Sensing, 7(3), 3056-3087; doi:10.3390/rs70303056.

[58]Li Z.S., L. Jia*, G. C. Hu, J. Lu, Q.T. Chen, J.X. Zhang and K. Wang, 2015, Estimation of Growing Season Daily ET in the Middle Stream and Downstream Areas of the Heihe River Basin Using HJ-1 Data, IEEE Geoscience and Remote Sensing Letters, 12(5), 948 – 952, DOI:  10.1109/LGRS.2014.2368694.

[59]Hu G.C., L. Jia*, Menenti M., 2015, Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011. Remote Sensing of Environment, 156, 510–526, doi:10.1016/j.rse.2014.10.017.

[60]Li Z.S., L. Jia*, J. Lu, 2015, On Uncertainties of the Priestley-Taylor/LST-Fc Feature Space Method to Estimate Evapotranspiration: Case Study in An Arid/Semiarid Region in Northwest China, Remote Sensing, 7(1), 447-466, doi:10.3390/rs70100447.

[61]Cui Y.K., L. Jia*, G.C. Hu, and J. Zhou, 2015, Mapping of Interception Loss of Vegetation in the Heihe River Basin of China Using Remote Sensing Observations, IEEE Geoscience and Remote Sensing Letters, 12(1), 23 – 27; doi:10.1109/LGRS.2014.2324635.

[62]Roupioz L, F. Nerry, L. Jia, and M. Menenti, 2014, Improved Surface Reflectance from Remote Sensing Data with Sub-Pixel Topographic Information, Remote Sensing, 2014, 6(11), 10356-10374; doi: 10.3390/rs61110356.

[63]Cui Y.K., L. Jia*, 2014, A Modified Gash Model for Estimating Rainfall Interception Loss of Forest Using Remote Sensing Observations at Regional Scale, Water, 2014, 6(4), 993-1012; doi:10.3390/w6040993.

[64]Song CY, L. Jia*, M. Menenti, 2014, Retrieving High-Resolution Surface Soil Moisture by Downscaling AMSR-E Brightness Temperature Using MODIS LST and NDVI Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(3), 935 – 942; doi: 10.1109/JSTARS.2013.2272053.

[65]Gao, B., L. Jia*, M. Menenti, 2014, An improved method of retrieving land surface albedo over rugged terrain, IEEE Geoscience and Remote Sensing Letters, 11(2): 554 - 558, doi: 10.1109/LGRS.2013.2275072.

[66]Jia L., H. Shang, G. Hu, and M. Menenti, 2011, Phenological response of vegetation to upstream river flow in the Heihe River basin by time series analysis of MODIS data, Hydrology and Earth System Sciences, 15, 1047–1064.

[67]Jia L., G. Xi, S. Liu, C.  Huang, Y. Yan, G. Liu, 2009, Regional estimation of Daily to Annual Regional Evapotranspiration with MODIS data in the Yellow River Delta wetland, Hydrology and Earth System Sciences, 13, 1775-1787.

[68]Verhoef W., L. Jia, Q. Xiao, Z. Su, 2007. Unified optical-thermal four-stream radiative transfer theory for homogeneous vegetation canopies. IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, no.6, 1808-1822.

[69]Jia L., Z.-L. Li, M. Menenti, Z. Su, W. Verhoef and Z. Wan, 2003, A practical algorithm to infer soil and foliage component temperatures from bi-angular ATSR-2 data, International Journal of Remote Sensing, International Journal of Remote Sensing, 24 (23), 4739–4760.

[70]Jia L., Su Z., van den Hurk B. J.J.M., Menenti M., et al, 2003, Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements, Journal of Physics and Chemistry of the Earth, 28, 75-88.

[71]鄭超磊, 賈立, 胡光成, 高分一號(hào)衛(wèi)星遙感數(shù)據(jù)驅(qū)動(dòng)ETMonitor模型估算16 m分辨率蒸散發(fā)及驗(yàn)證．遙感學(xué)報(bào)，2023, 27(3): 758-768. DOI： 10.11834/jrs.20232477.

[72]謝秋霞, 賈立*, 陳琪婷, 尹燕旻, M. Menenti, 2021，閃電河流域農(nóng)牧交錯(cuò)帶微波遙感土壤水分產(chǎn)品評(píng)價(jià)．遙感學(xué)報(bào)，25(4): 974-989.

[73]盧善龍, 賈立, 蔣云鐘, 王宗明, 段洪濤, 沈明, 田雨, 盧靜. 2021. 聯(lián)合國(guó)可持續(xù)發(fā)展目標(biāo)6（清潔飲水與衛(wèi)生設(shè)施）監(jiān)測(cè)評(píng)估：進(jìn)展與展望．中國(guó)科學(xué)院院刊, 36(8): 904-913.

[74]鄭超磊, 胡光成, 陳琪婷, 賈立, 2021.遙感土壤水分對(duì)蒸散發(fā)估算的影響．遙感學(xué)報(bào)，25(4)：990-999.

[75]盧靜, 賈立, 鄭超磊, 胡光成, 2019.遙感水分收支對(duì)區(qū)域水資源估算潛能．遙感技術(shù)與應(yīng)用，2019，34(3): 630-638. doi:10.11873/j.isnn.1004-0323.2019.3.0630.

[76]黃田進(jìn), 梁丁丁, 賈立*, 張靜瀟, 盧靜, 周杰，2017. 青藏高原地區(qū)湖泊面積插補(bǔ)迭代自動(dòng)提?。b感技術(shù)與應(yīng)用，2017, 32 (2) : 289-298.

[77]王寧, 賈立*, 李占勝, 李娜娜, 胡光成, 2016. 非參數(shù)化蒸散發(fā)方法在黑河流域的適用性分析. 高原氣象, 35(1): 118- 128。

[78]李娜娜, 賈立*, 盧靜，2015. 復(fù)雜下墊面地表土壤熱通量算法改進(jìn):以黑河流域?yàn)槔? 中國(guó)科學(xué): 地球科學(xué), 2015, 45(4): 494-507。

[79]潘穎琪, 賈立*, 2015. 基于MTSAT-1R數(shù)據(jù)的地表溫度反演．遙感技術(shù)與應(yīng)用, 30(4): 626 - 637。

[80]楊錦鑫, 賈立*, 2014. 基于雙角度AATSR遙感數(shù)據(jù)的組分溫度反演．遙感技術(shù)與應(yīng)用, 2014, 29 (2): 247-257。

[81]賈立, 王介民, M.Menenti, 1999. 衛(wèi)星遙感結(jié)合地面資料對(duì)區(qū)域表面動(dòng)量粗糙度的估算．大氣科學(xué)，1999, 23(5): 632-640。

[82]賈立, 王介民, 1999. 綠洲和沙漠復(fù)合地表?xiàng)l件下的局地和有效粗糙度. 氣象學(xué)報(bào), 1999, 57(3): 346-357。

[83]賈立, 王介民, 胡澤勇，2000. 干旱區(qū)熱力學(xué)粗糙度特征及對(duì)感熱通量估算的影響. 高原氣象, 2000, 19(4): 495-503。

[84]賈立, 王介民，1999. 黑河實(shí)驗(yàn)區(qū)地表植被指數(shù)的區(qū)域分布及季節(jié)變化.高原氣象, 1999, 18(2): 245-249。

[85]賈立, 王介民, 劉巍，1994. 黑河試驗(yàn)區(qū)春小麥田間的環(huán)境因子對(duì)蒸騰和光合作用的影響. 高原氣象, 1994, 13(3):359-368。

（2）專著（參與編寫）

[1]《陸表能量與水分交換過程的遙感觀測(cè)與模擬》，科學(xué)出版社，2023，ISBN 978-7-03-074897-3. （施建成，賈立，盧麾，蔣玲梅著）

[2]《地球大數(shù)據(jù)支撐可持續(xù)發(fā)展目標(biāo)報(bào)告（2019）》，科學(xué)出版社，2020.

[3]《地球大數(shù)據(jù)支撐可持續(xù)發(fā)展目標(biāo)報(bào)告（2020）：一帶一路篇》，科學(xué)出版社，2021.

[4]《地球大數(shù)據(jù)支撐可持續(xù)發(fā)展目標(biāo)報(bào)告（2021）：中國(guó)篇》，科學(xué)出版社，2022.

[5]《地球大數(shù)據(jù)支撐可持續(xù)發(fā)展目標(biāo)報(bào)告（2021）：一帶一路篇》，科學(xué)出版社，2022.

[6]遙感監(jiān)測(cè)綠皮書《中國(guó)可持續(xù)發(fā)展遙感監(jiān)測(cè)報(bào)告（2016）》,社會(huì)科學(xué)文獻(xiàn)出版社,2017.

[7]遙感監(jiān)測(cè)綠皮書《中國(guó)可持續(xù)發(fā)展遙感監(jiān)測(cè)報(bào)告（2017）》,社會(huì)科學(xué)文獻(xiàn)出版社,2018.

[8]遙感監(jiān)測(cè)綠皮書《中國(guó)可持續(xù)發(fā)展遙感監(jiān)測(cè)報(bào)告（2019）》,社會(huì)科學(xué)文獻(xiàn)出版社,2020.

[9]遙感監(jiān)測(cè)綠皮書《中國(guó)可持續(xù)發(fā)展遙感監(jiān)測(cè)報(bào)告（2021）》,社會(huì)科學(xué)文獻(xiàn)出版社,2022.(副主編)

[10]遙感監(jiān)測(cè)綠皮書《中國(guó)可持續(xù)發(fā)展遙感監(jiān)測(cè)報(bào)告（2022）》,社會(huì)科學(xué)文獻(xiàn)出版社,2022.(副主編)

[11]Jia L., C. Zheng, G.C. Hu, and M. Menenti, 2017. Evapotranspiration, Chapter in book ‘Comprehensive Remote Sensing’, edited by S. Laing et al., Elsevier, ISBN-10: 0128032200, ISBN-13: 978-012803220; pp.3134.

[12]Jia, L., M. Menenti, 2010. Thermal infrared observations of heterogeneous soil-vegetation systems, Chapter in book ‘Remote Sensing Optical Observations of Vegetation Properties’, Editors: Maselli, F., Menenti, M., and Brivio, A., Research Signpost, Kerala, India, pp. 227-274, 2010.