3种时序N_(dvi)重构方法对比分析  

Comparison and analysis of three sequential N_(dvi) reconstruction methods

作　　者：丁灿彧 胡希军[1] 吴德政 刘伟乐 DING Canyu;HU Xijun;WU Dezheng;LIU Weile(School of landscape architecture, Central South University of Forestry and Technology, Changsha 410004, Hunan, China;Xiamen City University, Xiamen 361000, Fujian, China;Jimei University, Academy of Fine Arts, Xiamen 361000, Fujian, China;Central South University, Changsha 410004, Hunan, China)

机构地区：[1]中南林业科技大学风景园林学院,湖南长沙410004 [2]厦门城市职业学院,福建厦门361000 [3]集美大学美术学院,福建厦门361000 [4]中南大学,湖南长沙410004

出　　处：《中南林业科技大学学报》2018年第4期10-15,共6页Journal of Central South University of Forestry & Technology

基　　金：林业公益性行业科研专项(201404710)

摘　　要：针对MODIS 16 d合成的N_(dvi)时间序列数据的重构问题,以厦门岛为实验区,以林地为实验类型,基于双Logistic函数拟合法、非对称高斯函数拟合法和Savitzky-Golay滤波法,进行区域时间序列N_(dvi)数据的重构措施及验证研究。结果表明,3种重建方法均可以整体提高时序N_(dvi)平均值,有效地避免异常值及噪声的干扰,A-G函数与D-L函数拟合法重建的时序N_(dvi)更能反映林地成长的曲线特征;S-G滤波法和A-G函数拟合法在保持高质量N_(dvi)真实值特征方面比D-L法效果较好;在生长季峰期内,S-G滤波法拟合效果要优于A-G函数和D-L函数拟合算法,更能反映林地成长的最佳情况。For the reconstruction problem of MODIS 16 d synthetic time-series of Ndvi data, we carried out the researches on reconstruction method of regional Ndvi time-series data and validation studies with the experimental area of Xiamen Island, which was based on double Logistic function fitting, symmetric Gaussian fitting and Savitzky-Golay filter. The results showed that the three reconstruction methods can improve the overall time-series Ndvi average value, effectively avoid noise interference and outliers, A-G and D-L fitting reconstruction of Ndvi time-series could reflect the characteristics of the vegetation growth curve better; S-G filtering method and A-G function fitting are better than D-L method in the aspects of maintaining the real high quality Ndvi value characteristics; During the growing season peak period, the fitting effect of S-G filtering function was better than A-G and D-L function fitting algorithm, which could reflect the growth of vegetation in the best condition better.

关 键 词：MODIS NDVI 时间序列拟合重建 厦门岛 林地 

分 类 号：S771.8[农业科学—森林工程]