浙江农业学报

• 园艺科学 • 上一篇    下一篇

基于叶片光谱特征的南疆盆地主栽果树树种遥感识别

  

  1. (1 新疆农业大学 林学与园艺学院,新疆 乌鲁木齐 830052; 2 新疆教育厅干旱区林业生态与产业技术重点实验室,新疆 乌鲁木齐 830052)
  • 出版日期:2015-12-25 发布日期:2016-01-05

Remote sensing identification of main fruit tree species based on leaf spectral feature in southern Xinjiang basin

  1. (1 Collage of Forestry and Horticulture, Xinjiang Agricultural University, Urumqi 830052, China; 2 Key Laboratory of Forestry Ecological and Industrial Technology in Arial Region, Education Department of Xinjiang, Urumqi 830052, China)
  • Online:2015-12-25 Published:2016-01-05

摘要: 随着新疆南疆林果业的飞速发展,对于果树树种的分类与提取逐渐成为研究热点。试验选取了新疆南疆盆地主栽的5种果树作为试验对象,利用光谱仪测定不同树种的叶片高光谱反射率数据,旨在找到一种快捷、精确、大范围、适时、动态的果树监测与分类方法,以期为星载高光谱遥感水平上的树种智能识别提供必要的技术支撑。在对不同树种叶片光谱特征分析的基础上,采用不同步长间隔的平滑滤值处理及5种数据变换方式,开展了5种果树树种识别研究。结果表明:在步长间隔为5 nm的平滑处理下,经过一阶微分变换的树种识别精度最高,达99.3%。此方法为新疆南疆主栽果树树种的遥感识别提供了新的途径。

关键词: 高光谱, 叶片, 南疆, 特征波段, 树种识别

Abstract: With the rapid development of fruit industry in southern Xinjiang, the classification and extraction of fruit tree has become a hot topic. As the experimental object, this paper selected five kinds of fruit in the southern basin of Xinjiang. In order to find a fast, accurate, large scale, timely, dynamic monitoring of fruit trees and classification method, hyperspectral reflectance data of different leaf species were measured by spectrometer. It would provide necessary technical support to species recognition at the level of spaceborne hyperspectral remote sensing. Based on analysis on the spectral characteristics of five fruit tree species, it employed a way of smoothing filter value treatment under different step sizes and five data transformation methods. The results showed that the species recognition accuracy was the highest after the first derivative transformation, which reached 99.3% under smoothing processing with the step interval of 5 nm. It indicated that this method of remote sensing identification provided a new way for the main tree species in southern Xinjiang.

Key words: hyperspectral, leaf, Southern Xinjiang, feature bands, species identification