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陆灯盛

陆灯盛,男,1965年02月出生。浙江省“千人计划”入选者、浙江省高等学校“钱 江学者”特聘教授、浙江农林大学环境与资源学院教授。2001年毕业于美国印第安那州立大学,获自然地理博士学位,后在美国印第安纳大学从事遥感博士后研 究,2011年开始先后在印第安纳大学全球环境变化研究中心、奥本大学林业与野生动物学院、密歇根州立大学全球变化与对地观测中心工作,任研究员、教授。 主持或参与美国NASA、NSF、NIH 及巴西CNPq,以及中国的NSF 及863 等项目,自2002年以来在《Remote Sensing of Environment》等刊物发表近60篇SCI论文,另外在专著中发表14篇(章节)。先后担任《Remote Sensing of Environment》、《Photogrammetric Engineering and Remote Sensing》、《International Journal of Remote Sensing》等30种遥感/地理信息系统期刊和组织机构的审稿专家。

研究领域包括土地利用/覆盖分类和变化监测、森林生物量/碳储量遥感定量估算、土地退化评估、城市不透水地表提取以及植被干扰遥感监测等。

教学工作:

研究生:遥感技术与应用

本科生:森林经理学;森林资源监测与信息管理

近五年主持和参与的科研项目:

1. Land use changes and their interactions with forest degradation processes in Amazonia. Brazil CNPq–LBA, 1/2014-12/2016, R$ 926,656.00.

2. Integration of Multi-sensor and Multi-scale Remote Sensing Data for Examining Land Use/Cover Disturbance at a Regional Scale in the Brazilian Amazon.Brazilian Science without Borders Program, Brazil CNPq(401528/2012-0),10/2012-9/2015, R$414,855.80.

3. Amazonian Deforestation and the Structure of Households, National Institutes of Health /NICHD(#HD35811-08), 7/2008– 6/2014.USD $2,685,599.

4. Advancing Land Use and Land Cover Analysis by Integrating Optical and Polarimetric Radar Platforms, NSF(#BCS-0850615), 2009– 2012. USD $199,613.

近五年发表的期刊论文:

(1)Lu, D., Li, G., Moran, E., and Kuang, W., 2014. A Comparative Analysis of Approaches for Successional Vegetation Classification in the Brazilian Amazon. GIScience and Remote Sensing. http://dx.doi.org/10.1080/15481603.2014.983338.

(2)Lu, D., Chen, Q., Wang, G., Liu, L., Li, G., and Moran, E., 2014. A Survey of Remote Sensing-Based Aboveground Biomass Estimation Methods in Forest Ecosystems. International Journal of Digital Earth. http://dx.doi.org/10.1080/17538947.2014.990526.

(3)Lu, D., Li, G., Moran, E., Dutra, L., and Batistella, M., 2014. The roles of textural images in improving land-cover classification in the Brazilian Amazon. International Journal of Remote Sensing. 35(24), 8818-8207. http://dx.doi.org/10.1080/01431161.2014.980920.

(4)Lu, D., Li. G., and Moran, E., 2014. Current situation and needs of change detection techniques. International Journal of Image and Data Fusion, 5(1), 13-38. doi.org/10.1080/19479832.2013.868372.

(5)Lu, D., Li. G., Kuang, W., and Moran, E., 2014. Methods to extract impervious surface areas from satellite images. International Journal of Digital Earth, 7(2), 93-112. doi.org/10.1080/17538947.2013.866173.

(6)Kuang, W., Chi, W., Lu, D.,* and Dou, Y., 2014. A comparative analysis of megacity expansions in China and the U.S.: Patterns, rates and driving forces. Landscape and Urban Planning, 132, 121-135. http://dx.doi.org/10.1016/j.landurbplan.2014.08.015.

(7)Sun, X., Du, H., Han, N., Zhou, G., Lu, D., Ge, H., Xu, X., and Liu, L., 2014. Synergistic use of Landsat TM and SPOT 5 imagery for object-based forest classification. Journal of Applied Remote Sensing. 8(1):083550. doi: 10.1117/1.JRS.8.083550.

(8)Tian, Y., Yin, K., Lu, D., Hua, L., Zhao, Q., and Wen, M., 2014. Examining Land-Use and Land-Cover Spatiotemporal Change and Driving Forces in Beijing from 1978 to 2010. Remote Sensing. 6, 10593-10611; doi:10.3390/rs61110593.

(9)Lu, D., Li, G., Moran, E., and Hetrick, S., 2013. Spatiotemporal analysis of land-use and land-cover change in the Brazilian Amazon. International Journal of Remote Sensing. 34:16, 5953-5978.

(10)Li, G., Lu, D*., Moran, E., and Hetrick, S., 2013. Mapping impervious surface area in the Brazilian Amazon using Landsat imagery. GIScience & Remote Sensing. 50(2), 172-183. http://dx.doi.org/10.1080/15481603.2013.780452.

(11)Kuang, W., Liu, J., Zhang, Z., Lu, D., and Xiang, B., 2013. Spatiotemporal dynamics of impervious surface areas across China during the early 21st century. Chinese Science Bulletin, 58, doi: 10.1007/s11434-012-5568-2.

(12)Pereira, L.O., Freitas, C.C., Sant′Anna, S.J.S., Lu, D., and Moran, E.F., 2013. Optical and radar data integration for land use and land cover mapping in the Brazilian Amazon. GIScience & Remote Sensing, 50(3), 301-321. DOI:10.1080/15481603.2013.805589.

(13)Yang, Y., Yu, S., Li, Y., and Lu, D., 2013. Integration of multi-dimensional parameters of polarimetric SAR images for land use and land cover classification. Journal of Applied Remote Sensing, 7 (1), 073472 (November 27, 2013); doi: 10.1117/1.JRS.7.073472.

(14)Li, G., Lu, D*., Moran, E., and Sant’Anna, S.J.S., 2012. A comparative analysis of classification algorithms and multiple sensor data for land use/land cover classification in the Brazilian Amazon. Journal of Applied Remote Sensing, 6(1), 061706 (Dec 14, 2012). doi:10.1117/1.JRS.6.061706.

(15)Lu, D., Batistella, M., Li, G., Moran, E., Hetrick, S., Freitas, C., Dutra, L., and Sant’Anna, S.J.S., 2012. Land Use/Cover Classification in the Brazilian Amazon Using Satellite Images. Brazilian Journal of Agricultural Research, 47(9), 1185-1208.

(16)Lu, D., Hetrick, S., Moran, E., and Li, G., 2012. Application of time series Landsat images to examining land use/cover dynamic change. Photogrammetric Engineering & Remote Sensing. 78(7), 747-755.

(17)Lu, D., Chen, Q., Wang, G., Moran, E., Batistella, M., Zhang, M., Laurin, G.V., and Saah, D., 2012. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates. International Journal of Forestry Research. Volume 2012, doi:10.1155/2012/436537. Pp. 16.

(18)Li, G., Lu, D*., Moran, E., Dutra, L., and Batistella, M., 2012. A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. ISPRS Journal of Photogrammetry and Remote Sensing, 70, 26-38.

(19)Huang, J., Lu, D*., Li, J., Wu, J., Chen, S., Zhao, W., Ge, H., Huang, X., and Yan, X., 2012. Integration of Remote Sensing and GIS for Evaluating Soil Erosion Risk in Northwestern Zhejiang, China. Photogrammetric Engineering & Remote Sensing, 78(9), 935-946.

(20)Lu, D., Li, G., Moran, E., Batistella, M., and Freitas, C., 2011. Mapping impervious surfaces with the integrated use of Landsat Thematic Mapper and radar data: a case study in an urban-rural landscape in the Brazilian Amazon. ISPRS Journal of Photogrammetry and Remote Sensing. 66(6), 798–808, DOI: 10.1016/j.isprsjprs.2011.08.004.

(21)Lu, D., Li, G., Moran, E., Dutra, L., and Batistella, M., 2011. A Comparison of Multisensor Integration Methods for Land-cover Classification in the Brazilian Amazon. GIScience & Remote Sensing. 48(3), 345-370. DOI: 10.2747/1548-1603.48.3.345.

(22)Lu, D., Batistella, M., Moran, E., Hetrick, S., Alves, D., and Brondizio, E. 2011. Fractional Forest Cover Mapping in the Brazilian Amazon with a Combination of MODIS and TM Images. International Journal of Remote Sensing. 32(22), 7131-7149. DOI: 10.1080/01431161.2010.519004.

(23)Lu, D., Hetrick, S., and Moran, E. 2011. Impervious Surface Mapping with QuickBird Imagery. International Journal of Remote Sensing. 32(9), 2519-2533, DOI: 10.1080/01431161003698393.

(24)Lu, D., Moran, E., and Hetrick, S., 2011. Detection of Impervious Surface Change with Multitemporal Landsat Images in an Urban-rural Frontier. ISPRS Journal of Photogrammetry and Remote Sensing. 66(3), 298-306. doi:10.1016/j.isprsjprs.2010.10.010.

(25)Li, G., Lu, D*., Moran, E., and Hetrick, S., 2011. Land-cover Classification in a Moist Tropical Region of Brazil with Landsat TM Imagery. International Journal of Remote Sensing. 32(23), 8207-8230, DOI:10.1080/01431161.2010.532831.

(26)Zhang, Y., Lu, D*., Yang, B., Sun, C., and Sun, M. 2011. Coastal Wetland Vegetation Classification with a Landsat Thematic Mapper Image. International Journal of Remote Sensing. 32(2), 545–561, DOI: 10.1080/01431160903475241.

(27)Kuang, W., Liu, J., and Lu, D. 2011. Pattern of Impervious Surface Change and Its Effect on Water Environment in the Beijing-Tianjin-Tangshan Metropolitan Area. ACTA GEOGRAPHICA SINICA, 66(11), 11p. (in Chinese).

(28)Lu, D., Hetrick, S., Moran, E., and Li, G., 2010. Detection of Urban Expansion in an Urban-rural Landscape with Multitemporal QuickBird Images. Journal of Applied Remote Sensing, Vol.4, 041880, DOI: 10.1117/1.3501124.

(29)Lu, D., Xu, X., Tian, H., Moran, E., Zhao, M., and Running, S., 2010. The Effects of Urbanization on Net Primary Productivity in Southeastern China. Environmental Management. 46(3), 404–410, DOI: 10.1007/s00267-010-9542-y.

(30)Lu, D., Hetrick, S., and Moran, E. 2010. Land Cover Classification in a Complex Urban-Rural Landscape with QuickBird Imagery. Photogrammetric Engineering and Remote Sensing. 76(10), 1159-1168. DOI: 0099-1112/10/7610–1159.

近五年发表的著作:

(1)Anjos, D., Lu, D., Dutra, L., and Sant’Anna, S., 2015. Change Detection Techniques Using Multisensor Data. In: Remote Sensing Handbook, Data, Characterization, Classification and Accuracies. Prasad S. Thenkabail (Editor).

(2)Li, G., Lu, D., Moran, E., Batistella, M., Freitas, C., Dutra, L., and Sant’Anna, S.J.S., 2013. Land Use/Cover Classification in the Brazilian Amazon with Different Sensor Data and Classification Algorithms (Chapter 6). In: Remote Sensing of Natural Resources. Guangxing Wang and Qihao Weng (eds), pp. 111-125. CRC Press/Taylor and Francis, Boca Raton, Florida.

(3)Lu, D., Li, G., Moran, and Hetrick, S., 2013. Vegetation Change Detection in the Brazilian Amazon with Multitemporal Landsat Images (Chapter 7). In: Remote Sensing of Natural Resources. Guangxing Wang and Qihao Weng (eds), pp. 127-140. CRC Press/Taylor and Francis, Boca Raton, Florida.

(4)Lu, D., Moran, E., Hetrick, S., and Li, G., 2012. Mapping Impervious Surface Distribution with the Integration of Landsat TM and QuickBird Images in a Complex Urban-Rural Frontier in Brazil (Chapter 13). In: Environmental Remote Sensing and Systems Analysis. Ni-Bin Chang (ed.), pp. 277-296, CRC Press/Taylor and Francis, Boca Raton, Florida.

(5)Lu, D., Weng, Q., Moran, E., Li, G., and Hetrick, S., 2011. Remote Sensing Image Classification (Chapter 9). In: Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications. Q. Weng (ed.), 219-240. CRC Press/Taylor and Francis, Boca Raton, Florida.

(6)Lu, D., Moran, E., Hetrick, S., and Li, G., 2011. Land-use and Land-cover Change Detection (Chapter 11). In: Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications. Q. Weng (ed.), pp. 273-288. CRC Press/Taylor and Francis, Boca Raton, Florida.

联系方式:

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电子邮件:luds@zafu.edu.cn


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