文献类型：会议论文

英文题名：THE WHEAT BIOMASS ESTIMATION BASED ON GENETIC ALGORITHM FEATURE SELECTION METHOD USING C-BAND POLSAR DATA

作者：Xu, Kunpeng[1] Chen, Erxue[1] Li, Zengyuan[1] Zhao, Lei[1] Zhang, Wangfei[2] Wan, Xiangxing[1]

第一作者：Xu, Kunpeng

通信作者：Chen, EX[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resources Informat Tech, Beijing, Peoples R China;[2]Southwest Forestry Univ, Coll Forestry, Kunming, Yunnan, Peoples R China

会议论文集：IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

会议日期：JUL 28-AUG 02, 2019

会议地点：Yokohama, JAPAN

语种：英文

外文关键词：Biomass estimation; Feature selection; nonparametric estimation; PolSAR; Genetic algorithm

年份：2019

摘要：In this paper, we studied the nonparametric estimation approach of wheat biomass using C-band PolSAR data. We focus on a crucial step of the estimation process, which is feature combination selection. Firstly, the original feature pool was acquired using PolSAR data. Then, using genetic algorithm (GA) as searching engine we selected the feature combination which has the best performance in the estimation model. Finally, the wheat biomass was estimated based on the features combination selected by GA. The experimental results showed that the selected feature combination by GA can outperform the original feature pool and the feature combination selected based on Pearson correlation coefficient (PCC) between feature and biomass.