[1] 郭亚鸽, 于信芳, 江东, 等. 面向对象的森林植被图像识别分类方法[J]. 地球信息科学学报, 2012, 14(4):514-522. [2] 郭玉宝, 池天河, 彭玲, 等. 利用随机森林的高分一号遥感数据进行城市用地分类[J]. 测绘通报, 2016(5):73-76. [3] 赵丹平, 顾海燕, 贾莹. 机器学习法在面向对象影像分类中的对比分析[J]. 测绘科学, 2016, 41(10):181-186. [4] QIAN Y, ZHOU W, YAN J, et al. Comparing Machine Learning Classifiers for Object-based Land Cover Classification Using very High Resolution Imagery[J]. Remote Sensing, 2014, 7(1):153-168. [5] DURO D C, FRANKLIN S E, DUBÉ M G. A Comparison of Pixel-based and Object-based Image Analysis with Selected Machine Learning Algorithms for the Classification of Agricultural Landscapes Using SPOT-5 HRG Imagery[J]. Remote Sensing of Environment, 2012, 118(6):259-272. [6] SONG X, DUAN Z, JIANG X. Comparison of Artificial Neural Networks and Support Vector Machine Classifiers for Land Cover Classification in Northern China Using a SPOT-5 HRG Image[J]. International Journal of Remote Sensing, 2012, 33(10):3301-3320. [7] CAMPOMANES F, PADA A V, SILAPAN J. Mangrove Classification Using Support Vector Machines and Random Forest Algorithm:a Comparative Study[R]. Enschede:University of Twente, 2016. [8] LI C, WANG J, WANG L, et al. Comparison of Classifica-tion Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery[J]. Remote Sensing, 2014, 6(2):964-983. [9] CHAN J C W, PAELINCKX D. Evaluation of Random Forest and Adaboost Tree-based Ensemble Classification and Spectral Band Selection for Ecotope Mapping Using Airborne Hyperspectral Imagery[J]. Remote Sensing of Environment, 2008, 112(6):2999-3011. [10] NOVACK T, ESCH T, KUX H, et al. Machine Learning Comparison between WorldView-2 and QuickBird-2-simulated Imagery Regarding Object-based Urban Land Cover Classification[J]. Remote Sensing, 2011, 3(10):2263-2282. [11] DRǍGUŢ L, CSILLIK O, EISANK C, et al. Automated Parameterisation for Multi-scale Image Segmentation on Multiple Layers[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 88(100):119-127. [12] 顾海燕, 闫利, 李海涛, 等. 基于随机森林的地理要素面向对象自动解译方法[J]. 武汉大学学报(信息科学版), 2016, 41(2):228-234. [13] ISPRS.2D Semantic Labeling Contest-Potsdam[DB/OL]. (2001-12-19)[2016-09-15]. http://www2.isprs.org/commissions/comm3/wg4/2d-sem-label-potsdam.html. [14] 张继贤, 魏钜杰, 赵争,等. 基于多方向多源合成孔径雷达数据融合的假彩色正射影像制作[J]. 测绘学报, 2011, 40(3):276-282. |