水环境遥感学科组
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  学科组简介

  一、学科组简介 

  1、学科目标:系统研究内陆水体表观与固有光学特性,为内陆水体水色遥感模型的构建奠定基础;构建内陆水体富营养化与碳组分遥感反演模型,为实现内陆水体水色反演与碳储量估算提供算法支持。 

  2、研究方向:水体生物光学特性与水质遥感模型;内陆水体碳组分遥感反演与时空格局演变;地表水富营养化遥感与水文参数遥感反演。 

  二、队伍组成 

  组长:宋开山 (研究员) 

  成员:杜嘉、温志丹、刘阁 (助理研究员) 

  项目聘用人员:李晓东、吕丽丽、吴海曼、刘欣婷、侯军斌、王丽娜、彭瑞、杜晓 

  研究生队伍:杨倩、王晓迪、赵莹、房冲、尚盈辛、杜云霞、沙林伟、李晟铭、马学垚、张东方、孟庆吉、王强、尹炀、王良玉 

  三、在研项目 

  1. 国家自然科学基金重点项目“咸水湖泊固有光学-偏振-介电特性研究”(41730104),宋开山,2018-2022. 

  2. 国家科技部重点研发项目子课题“全球湿地动态变化检测及环境变化研究”
(2016YFB0501502),宋开山,2016-2020. 

  3. 国家重点研发计划专题“1900s-1960s黑龙江流域景观空间分布数据集及分析”
(2016YFA0602301-1),杜嘉,2016-2021. 

  4. 国防科工局高分系统重大专项“GF-5高光谱载荷的内陆水体参量反演技术-东北共性技术”
(41-Y20A31-9003-15/17),宋开山,2016-2018. 

  5. 国家自然科学基金面上项目“湖冰生物光学特性研究”(41471293),宋开山,
2015-2018. 

  6. 国家自然基金青年项目“基于水体光学分类的内陆湖泊水体大气校正研究 ”
(41701423),刘阁,2018-2020. 

  7. 国家自然基金青年项目“光化学与微生物降解对高原湖泊CDOM光学特性影响机理研究”
(41501387),温志丹,2016-2018. 

  8. 吉林省科技厅领军人才及创新团队项目吉林省“城市及饮用水体水质遥感创新团队”
(20150519006JH),宋开山,2015-2017. 

  9. 中国科学院“百人计划”项目“内陆水体光学特性与水质遥感研究”,宋开山,
2014-2018. 

  10. 中国科学院东北地理与农业生态研究所优秀青年人才基金区域湖泊温室气体排放及影响机制”,温志丹,2017-2021. 

  四、科研成果 

  自2010年以来共发表论文150余篇,专著2部,获得奖励4项,软件登记11项。 

  1. 论文 

  [1]  Song, K., Wen, Z., Shang, Y., et al. 2018. Quantification of dissolved organic carbon (DOC) storage in lakes and reservoirs of mainland China. Journal of Environmental Management, 217, 391-402. 

  [2]  Fang, C., Song, K., Li, L., et al. 2018. Spatial variability and temporal dynamics of HABs in Northeast China. Ecological Indicators, 90, 280-294. 

  [3]  Wen, Z., Song, K., Shang, Y., et al. 2018. Differences in the distribution and optical properties of DOM between fresh and saline lakes in a semi-arid area of Northern China. Aquatic Sciences, 80(22), 1-12. 

  [4]  Wen, Z., Huang X., Gao D., et al. 2018. Phthalate esters in surface water of Songhua River watershed associated with land use types, Northeast China, Environmental Science and Pollution Research, DOI: 10.1007/s11356-017-1119-3. 

  [5]  Shang, Y., Song, K., Wen, Z., et al. 2018. Characterization of CDOM absorption of reservoirs with its linkage of regions and ages across China. Environmental science and pollution research. DOI: 10.1007/s11356-018-1832-6. 

  [6]  Fang, C., Song, K.S., Shang, Y.X., et al., 2018. Remote sensing of harmful algal blooms variability for Lake Hulun using adjusted FAI (AFAI) algorithm. J. Environ. Inf. http://dx.doi.org/10.3808/jei.201700385.  

  [7]  Jin, X., Song, K., Du, J., et al. 2017. Comparison of different satellite bands and vegetation indices for estimation of soil organic matter based on simulated spectral configuration. Agricultural and Forest Meteorology, 244, 57-71. 

  [8]  Jin, X., Li Z., Yang, G., et al. 2017. Winter wheat yield estimation based on multi-source medium resolution optical and radar imaging data and the AquaCrop model using the particle swarm optimization algorithm. ISPRS Journal of Photogrammetry and Remote Sensing, 126:24-37 

  [9]  Song, K., Ma, J., Wen, Z., et al. 2017. Remote estimation of Kd (PAR) using MODIS and Landsat imagery for turbid inland waters in Northeast China. ISPRS Journal of Photogrammetry and Remote Sensing, 123, 159-172. 

  [10] Song, K., Zhao, Y., Wen, Z., et al. 2017. A systematic examination of the relationships between CDOM and DOC in inland waters in China. Hydrology and Earth System Sciences, 21(10), 5127-5141. 

  [11] Wen, Z., Song, K., Shang, Y., et al. 2017. Carbon dioxide emissions from lakes and reservoirs of China: A regional estimate based on the calculated pCO2. Atmospheric Environment, 170, 71-81. 

  [12] Zhao, Y., Song, K., Wen, Z., et al. 2017. Evaluation of CDOM sources and their links with water quality in the lakes of Northeast China using fluorescence spectroscopy. Journal of Hydrology, 550, 80-91. 

  [13] Zhao, Y., Song, K., Shang, Y., et al. 2017. Characterization of CDOM of river waters in China using fluorescence excitation-emission matrix and regional integration techniques. Journal of Geophysical Research-Biogeosciences, 122(8), 1940-1953. 

  [14] Liu G, Simis SH, Li L, et al. 2017. A Four-Band Semi-Analytical Model for Estimating Phycocyanin in Inland Waters From Simulated MERIS and OLCI Data. IEEE Transactions on Geoscience and Remote Sensing, 56: 1374-1385. 

  [15] Li, S., Chen, Y., Zhang J., et al. 2017. The relationship of chromophoric dissolved organic matter parallel factor analysis fluorescence and polycyclic aromatic hydrocarbons in natural surface waters. Environmental Science and Pollution Research. DOI: 10.1007/s11356-018-1832-6. 

  [16] Jin, X., Du, J., Liu, H., et al. 2016. Remote estimation of soil organic matter content in the Sanjiang Plain, Northest China: The optimal band algorithm versus the GRA-ANN model. Agricultural and Forest Meteorology, 218, 250-260.  

  [17] Wen, Z., Wu, W., Ren, N., et al. 2016. Synergistic effect using vermiculite as media with a bacterial biofilm of Arthrobacter sp. for biodegradation of di-(2-ethylhexyl) phthalate. Journal of Hazardous Materials, 304: 118- 125. 

  [18] Wen, Z., Song, K., Zhao, Y., et al. 2016. Carbon dioxide and methane supersaturation in lakes of semi-humid/semi-arid region, Northeastern China. Atmospheric Environment, 138, 65-73. 

  [19] Wen, Z., Song, K., Zhao, Y., et al. 2016. Influence of environmental factors on spectral characteristics of chromophoric dissolved organic matter (CDOM) in Inner Mongolia Plateau, China. Hydrology and Earth System Sciences, 20(2), 787-801. 

  [20] Song, K., Wang, M., Du, J., et al. 2016. Spatiotemporal Variations of Lake Surface Temperature across the Tibetan Plateau Using MODIS LST Product. Remote Sensing, 8(10). 

  [21] Li, S., Song, K., Mu, G., et al. 2016. Evaluation of the Quasi-Analytical Algorithm (QAA) for Estimating Total Absorption Coefficient of Turbid Inland Waters in Northeast China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(9), 4022-4036. 

  [22] Ma, J., Song, K., Wen, Z., et al. 2016. Spatial Distribution of Diffuse Attenuation of Photosynthetic Active Radiation and Its Main Regulating Factors in Inland Waters of Northeast China. Remote Sensing, 8(11). 

  [23] Jin, X., Kumar, L, Li, Z., et al. 2016. Estimation of winter wheat biomass and yield by combining the aquacrop model and field hyperspectral data. Remote sensing, 8(12),972. 

  [24] Jin, X., Yang, G., Li, Z., et al. 2016. Estimation of water productivity in winter wheat using the AquaCrop model with field hyperspectral data. Precision Agriculture, doi:10.1007/s11119-016-9469-2. 

  [25] Zhao, Y., Song, K., Wen, Z., et al. 2016. Seasonal characterization of CDOM for lakes in semiarid regions of Northeast China using excitation–emission matrix fluorescence and parallel factor analysis (EEM–PARAFAC). Biogeosciences, 13(5), 1635-1645. 

  [26] Zhao, Y., Song, K., Li, L., et al. 2016. Characterization of CDOM from urban waters in Northern-Northeastern China using excitation-emission matrix fluorescence and parallel factor analysis. Environmental Science and Pollution Research, 23(15), 15381-15394. 

  [27] Shao, T., Song, K., Jacinthe, P.-A., et al. 2016. Characteristics and sources analysis of riverine chromophoric dissolved organic matter in Liaohe River, China. Water Science and Technology, 74(12), 2843-2859. 

  [28] Shao, T., Song, K., Du, J., et al. 2016. Retrieval of CDOM and DOC Using In Situ Hyperspectral Data: A Case Study for Potable Waters in Northeast China.Journal of the Indian Society of Remote Sensing, 44: 77-89.  

  [29] Shao, T., Song, K., Du, J., et al., 2016. Seasonal Variations of CDOM Optical Properties in Rivers Across the Liaohe Delta. Wetlands, 36,:181–192. 

  [30] Jin, X., Ma, J., Wen, Z., et al. 2015. Estimation of Maize Residue Cover Using Landsat-8 OLI Image Spectral Information and Textural Features. Remote Sensing, 7(11), 14559-14575. 

  [31] Shang, Y., Yu, X., Romero-González M. 2015. Screening of algae material as a filter for heavymetals in drinking water. Algal Research-Biomass Biofuels and Bioproducts,12:258-261. 

  [32] Du, J., Song, K., Wang Z. 2015. Estimation of water consumption and productivity for rice through integrating remote sensing and census data in the Songnen Plain, China. Paddy and Water Environment,13(1):91-99. 

  [33] Song, K., Li, L., Lenore, T., et al. 2015. Spectral characterization of colored dissolved organic matter for productive inland waters and its source analysis. Chinese Geographical Science, 5: 25(3): 295-308. 

  [34] Lu D., Song K., Zang S., et al. 2015. The Effect of Urban Expansion on Urban Surface Temperature in Shenyang, China: an Analysis with Landsat Imagery, Environmental Modeling Assessment, 20(3): 197-210. 

  [35] Zhao, Y., Song, K., Du, J., et al. 2015. Fluorescence Excitation-emission Matrices Characterization of DOM for Urban Waters across the Changchun City, Northeast China, 2014 International Conference on water resource and environmental protection. 

  [36] Song, K., Li, L., Tedesco, L., et al. 2014. Remote quantification of phycocyanin in potable water sources through an adaptive model. ISPRS Journal of Photogrammetry and Remote Sensing, 95, 68-80. 

  [37] Song, K., Li, L., Tedesco, L., et al. 2014. Using Partial Least Squares-Artificial Neural Network for Inversion of Inland Water Chlorophyll-a. IEEE Transactions on Geoscience and Remote Sensing, 52: 1502-1517 

  [38] Song, K., Li, L., Duan, H., et al. 2014. Remote quantification of total suspended matter through empirical approaches for inland waters. Journal of Environmental Informatics, 23(1): 23-36. 

  [39] Song, K., Wang, Z., Du, J., et al. 2014. Wetland degradation, driving forces and its environmental impacts in the Sanjiang Plain, China. Environmental Management, 54:255-271. 

  [40] Song, K., Li, L., Tedesco, L., et al. 2014. Remote Estimation of Nutrients for a Drinking Water Source Through Adaptive Modeling. Water Resources Management, 28(9), 2563-2581. 

  [41] Song, K., Li, L., Tedesco, L., et al. 2013. Remote estimation of chlorophyll-a in turbid inland waters: Three-band model versus GA-PLS model. Remote Sensing of Environment, 136, 342-357. 

  [42] Song, K., Zang, S., Zhao, Y., et al. 2013. Spatiotemporal characterization of dissolved carbon for inland waters in semi-humid/semi-arid region, China. Hydrology and Earth System Sciences, 17(10), 4269-4281. 

  [43] Song, K., Li, L., Li, Z., et al. 2013. Remote detection of cyanobacteria through phytocyanin for water supply source using three-band model. Ecological Informatics, 15, 22-33. 

  [44] Song, K., Li, L., Tedesco, L., et al. 2013. Remote estimation of phycocyanin (PC) for inland waters coupled with YSI PC fluorescence probe. Environmental Science and Pollution Research, 20:5330-5340. 

  [45] Song, K., Li, L., Tedesco, L., et al. 2012. Hyperspectral determination of eutrophication for a water supply source via genetic algorithm-partial least squares (GA-PLS) modeling. Science of the Total Environment, 426, 220-232. 

  [46] Song, K., Li, L., Li, S., et al. 2012. Hyperspectral Remote Sensing of Total Phosphorus (TP) in Three Central Indiana Water Supply Reservoirs. Water Air and Soil Pollution, 223(4), 1481-1502. 

  [47] Song, K.S., Wang, Z.M., Li, L., Xu, J.P. 2012. Retrieval of total suspended matter and chlorophyll-a using remote sensing data for drinking water resources. Environmental Monitoring and assessment, 184: 1449–1470. 

  [48] Song, K.S., Wang, Z. M., Blackwell, J., Zhang, B., Zhang, Y. 2011. Water quality monitoring using Landsat Thematic Mapper data with empirical algorithms in Chagan Lake, China. Journal of Applied Remote Sensing, 5. Doi:10.1117/1.3559497.  

  [49] Song, K.S., Wang, Z. M., Liu, Q. F., Liu, D. W., Ermoshin, V. V., Ganzei, S. S., Zhang, B., Ren, C. Y., Zeng, L. H., Du, J., 2011. Land Use/Land Cover (LULC) Classification with MODIS Time Series Data and Validation in the Amur River Basin. Geography and Natural Resources, 2011, 32(1), 9-15.  

  [50] Zeng, L. H., Song, K. S*., Zhang, B., Li, L., Wang, Z. 2011. Evaportranspiration estimation using moderate resolution imaging spectroradiometer products through a surface energy balance algorithm for land model in Songnen Plain, China. Journal of Applied Remote Sensing, 5. Doi: 10.1117/1.3609840. 

  2. 专著 

  [1]  刘殿伟、张柏、宋开山、王宗明. 区域景观遥感信息研究. 科学出版社,北京,2006. 

  [2]  宋开山、刘殿伟、张柏、王宗明. 东北地区典型地物光谱特征分析与组分反演. 吉林大学出版社,长春,2009. 

  3. 奖励 

  [1]  湖沼湿地生态环境演变过程与机理研究,黑龙江省科学技术奖,二等奖,2017.10. 

  [2]  水体光学特性与自适应算法的水色遥感应用,吉林省自然科学学术成果奖,一等奖,
2014.9. 

  [3]  中国东北地区土地资源动态与生态环境变化,吉林省科学技术奖,二等奖,
2013.12.16. 

  [4]  宋开山,第十二届全国青年地理科技奖,中国地理协会,2013.10. 

  4. 软件登记 

  [1]  多源传感器波段融合及像素频率统计软件,2017SR 683136,2017.12.12 

  [2]  多传感器水体边界及藻华信息自动提取软件,2017SR16753,2017.5.10 

  [3]  Shape文件批量裁剪遥感影像软件,2017SR387285,2017.7.20 

  [4]  基于时间序列遥感影像的云雾去除软件,2017SR360639,2017.5.15 

  [5]  GOCI卫星数据处理及水体动态监测软件V1.0,软著登字第1423699号,2016.8.22  

  [6]  MODIS地表温度数据处理及分析软件V1.0,软著登字第1406529号,2016.9.1  

  [7]  Landsat系列卫星数据水体批量提取软件V1.0,2016SR176450,2016.7.12  

  [8]  高光谱遥感影像处理与分析系统,2016SR128145,2016.6.1 

  [9]  水色遥感实验室数据处理软件,2015R11S277342,2015.12.18  

  [10] 高效节水空间管理信息系统,2014SR040047,2014.2.18 

  [11] 水质监测评价系统,2011SR006664,2011.2.14 

 
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