近期论文
查看导师最新文章
(温馨提示:请注意重名现象,建议点开原文通过作者单位确认)
[1] Ma, L., Liu, Y., Zhang, X., Ye, Y., Yin, G.,... Johnson, B. A. (2019). Deep learning in remote sensing applications: A meta-analysis and review. ISPRS Journal of Photogrammetry and Remote Sensing, 152, 166-177. (期刊Top 1高下载,ESI高引)https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[2] Ma, L., Li, M. C., Ma, X. X. (2017): A review of supervised object-based land-cover image classification. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 277-293. (ESI 高引, 期刊Top 3高下载)https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[3] Ma, L., Cheng, L., Li, M. C., Liu, Y., Ma, X. X. (2015): Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 102, 14-27.(期刊高引)https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[4] Ma, L., Fu, T. Y., Blaschke, T., Li, M. C., Tiede, D., Zhou, Z. J., Ma, X. X., Chen, D. (2017): Evaluation of feature selection methods for object-based land cover mapping of Unmanned Aerial Vehicle imagery using Random Forest and Support Vector Machine classifiers. ISPRS International Journal of Geo-Information, 6(2), 51/1-51/22.(ESI高引, The Jack Dangermond Award – 国际摄影测量与遥感协会 2017最佳论文)https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[5] Li, M. C., Ma, L.*, Blaschke, T., Cheng, L., Tiede, D. (2016): A systematic comparison of different object-based classification techniques using high spatial resolution imagery. International Journal of Applied Earth Observation and Geoinformation, 49, 87-98. (ESI 高引, 2017年7/8月统计数据)https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[6] Ma, L., Fu, T. Y., Li, M. C. (2018): Active learning for object-based image classification using predefined training objects. International Journal of Remote Sensing, 39:9, 2746-2765.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[7] Zhou, Z., Ma, L.*, Fu, T., Zhang, G., Yao, M.,... Li, M. (2018). Change Detection in Coral Reef Environment Using High-Resolution Images: Comparison of Object-Based and Pixel-Based Paradigms. ISPRS International Journal of Geo-Information, 7(11), 441. https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[8] Fu, T., Ma, L.*, Li, M. C., Johnson, B. A. (2018): Using convolutional neural network to identify irregular segmentation objects from very high-resolution remote sensing imagery. Journal of Applied Remote Sensing, 12(2), 025010.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[9] Ma, L., Li, M. C., Blaschke, T., Ma, X. X., Tiede, D., Cheng, L., Chen, Z. J., Chen, D. (2016): Object-Based Change Detection in urban areas: the effects of segmentation strategy, scale, and feature space on unsupervised methods. Remote Sensing, 8(9), 761.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[10] Ma, L., Gao, Y., Fu, T., Cheng, L., Chen, Z., Li, M. (2017): Estimation of Ground PM2.5 Concentrations using a DEM-assisted Information Diffusion Algorithm: A Case Study in China. Scientific Reports, 7, 15556.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[11] Ma, L., Li, M. C., Gao, Y., Chen, T., Ma, X. X., Qu, L. A. (2017): A novel wrapper approach for feature selection in object-based image classification using ppolygon-based cross-validation. IEEE Geoscience and Remote Sensing Letters, 14(3), 409-413.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[12] Ma, L., Cheng, L., Han, W. Q., Zhong, L. S., Li, M. C. (2014): Cultivated land information extraction from high-resolution unmanned aerial vehicle imagery data. Journal of Applied Remote Sensing, 8, 1-25.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[13] Ma, L., Li, Y. S., Liang, L., Li, M. C., Cheng, L. (2013): A novel method of quantitative risk assessment based on grid difference of pipeline sections. Safety Science, 59, 219-226.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[14]Ma, L., Cheng, L., Li, M. C. (2013): Quantitative risk analysis of urban natural gas pipeline networks using geographical information systems. Journal of Loss Prevention in the Process Industries, 26, 1183-1192.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[15] Gao, Y., Ma, L.*, Liu, J. X., Zhuang, Z. Z., Huang, Q. H., Li, M. C. (2017): Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China. Scientific Reports, 7, 46073.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[16] Cheng, L., Li, S., Ma, L.*,Li, M. C., Ma, X. X. (2015): Fire spread simulation using GIS: Aiming at urban natural gas pipeline. Safety Science, 75, 23-35.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[17] Cheng, L., Ma, L., Yang, K., Liu, Y. X., Li, M. C. (2013): Registration of Mars remote sensing images under the crater constraint. Planetary and Space Science, 2013, 85, 13-23.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[18] Cheng, L., Ma, L., Cai, W. T., Tong, L. H., Li, M. C., Du, P. J. (2013): Integration of Hyperspectral imagery and sparse sonar data for shallow water bathymetry mapping. IEEE Transactions on Geoscience and Remote Sensing, 2014, 53(6), 3235-3249.https://sgos.nju.edu.cn/_ueditor/themes/default/images/icon_pdf.gifpublication.pdf
[19] Ma, X. X., Wang, L. C., Ma, L., Zhang, Y. Q. (2015): Effects on sediments following water–sediment regulations in the Lixia River watershed, China. Quaternary International, 2015, 380/381, 334-341.
[20] Ma, X. X., Wang, L. C., Wu, H., Li, N., Ma, L., Zeng, C. F., Zhou, Y., Yang, J. (2015): Impact of Yangtze river water transfer on the water quality of the Lixia river watershed, China. Plos One, 10, e119720.
[21] Liu, Y., Hu, C., Zhan, W., Sun, C., Murch, B., Ma, L.(2018): Identifying industrial heat sources using time-series of the VIIRS Nightfire product with an object-oriented approach. Remote Sensing of Environment, 204, 347-365.
[22] Cheng, L., Yuan, Y., Xia, N., Chen, S., Chen, Y., Yang, K., Ma, L., Li, M. C. (2018): Crowd-sourced pictures geo-localization method based on street view images and 3D reconstruction. ISPRS Journal of Photogrammetry and Remote Sensing 141, 72-85.