基于植被丰度分析的城市植被胁迫遥感监测

林业资源管理 ›› 2010›› Issue (6): 97-101.

基于植被丰度分析的城市植被胁迫遥感监测

潘灼坤^1,2, 王芳¹, 夏丽华¹, 王晓轩¹, 刘汉湖²

1.广州大学地理科学学院,广州 510006;
2.成都理工大学地球科学学院,成都 610009

收稿日期:2010-09-21 修回日期:2010-11-01 发布日期:2020-12-14
通讯作者: 王芳,女,副教授,博士。Email:wfdili@163.com
作者简介:潘灼坤(1986-),男,广东东莞人,硕士研究生,主要研究方向为遥感与GIS应用。Email:xyslz114@sina.com
基金资助:
国家自然科学基金项目(40801034);广州市高校科技计划项目(08C025)

Remote Sensing Monitoring of Urban Vegetation Stress Based on Vegetation Abundance Analysis

PAN Zhuokun^1,2, WANG Fang¹, XIA Lihua¹, WANG Xiaoxuan¹, LIU Hanhu²

1. Guangzhou University, School of Geographical Sciences, Guangzhou 510006, China;
2. Chengdu University of Technology, College of Earth Sciences, Chengdu 610009, China

Received:2010-09-21 Revised:2010-11-01 Published:2020-12-14

摘要/Abstract

摘要： 以混合像元分解提取植被丰度作为主要手段,研究基于广州市区东边建成区的Hyperion高光谱遥感影像,以遥感影像预处理—特征选择—SMACC混合像元分解的步骤提取出植被丰度图,再进行PPI迭代运算纯化,提取出7种表征植被健康状况差异端元的PPI影像。经实地考察植被胁迫位置的周边人类活动的情况,结合植物生理学和光谱学分析反射率波谱曲线的变化,解释植物受到胁迫的原因,以期为城市绿地调查管理提供参考。

关键词: 植被胁迫, 特征提取, 混合像元分解, 植被丰度

Abstract: This study is mainly based on mixed pixel decomposing to extract vegetation abundance. The Hyperion hyperspectral remotely sensed image was used for eastern part of Guangzhou City. The steps such as image preprocessing, feature extraction and SMACC mixed pixel decomposing were taken to obtain vegetation abundance images. Furthermore the PPI iteration was used to purify these images, and then 7 kinds of vegetation endmembers which present defferent health state extracted. On-site survey was conducted to check out the human activities around the vegetation stress area, combined with other discipline just as plant physiology and spectroscopy to analyze the plant reflectance spectral curve changes and explain the causes. The research provides accurate information for urban green space survey and management.

Key words: vegetation stress, feature extraction, mixed pixel decomposing, vegetation abundance

中图分类号:

TP79

潘灼坤, 王芳, 夏丽华, 王晓轩, 刘汉湖. 基于植被丰度分析的城市植被胁迫遥感监测[J]. 林业资源管理, 2010,(6): 97-101.

PAN Zhuokun, WANG Fang, XIA Lihua, WANG Xiaoxuan, LIU Hanhu. Remote Sensing Monitoring of Urban Vegetation Stress Based on Vegetation Abundance Analysis[J]. FOREST RESOURCES WANAGEMENT, 2010,(6): 97-101.

参考文献

[1] 潘瑞炽.植物生理学[M].北京:高等教育出版社,2004.
[2] 张杰林.基于Hyperion高光谱数据的植被污染信息识别技术研究[C].第二届全国国土资源遥感技术应用交流会,2006.
[3] Davids C,Tyler A N.Detecting contamination-induced tree stress within the Chernobyl exclusion zone[J]. Remote Sensing of Environment,2003(85):30-38.
[4] 童庆禧,张兵,郑兰芬.高光谱遥感的多学科应用[M].北京:电子工业出版社,2006.
[5] 褚海峰.一种多/高光谱遥感图像端元提取的凸锥分析算法[J].遥感学报,2007, 11(4): 460-467.
[6] 吕杰.基于Hyperion高光谱遥感数据的城市绿地信息提取办法的研究[D].北京:中国地质大学,2009.
[7] 苏红军,杜培军.高光谱数据特征选择与特征提取研究[J].遥感技术与应用,2006,21(4):288-293.
[8] 耿修瑞.高光谱遥感图像目标探测与分类技术研究[D].北京:中国科学院遥感应用研究所,2005.
[9] 王芳,黎夏,卓莉,等.基于Hyperion高光谱数据的城市植被胁迫评价[J].应用生态学报,2007,18(6):1286-1292.
[10] 王芳,卓莉,黎夏,等.基于高光谱特征选择和RBFNN的城市植被胁迫程度监测[J].地理科学,2008,28(1):712-716.
[11] 卓莉.基于多源遥感数据和GIS的生态环境监测研究[D].广州:中山大学,2007.
[12] Weng Q H, Lu D S,Schubring J. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies [J].Remote Sensing of Environment, 2004,89:467-483.
[13] Small C. Estimation of urban vegetation abundance by spectral mixture analysis [J].International Journal of Remote Sensing,2001(22):1305-1334.
[14] Jensen J R. 遥感数字影像处理导论[M].陈晓玲,龚威,李平湘,等译.北京:机械工业出版社,2007.
[15] Gruninger J, Ratkowski A J,Hoke M L.The sequential maximum angle convex cone (SMACC) endmember model[J]. Proceedings SPIE, Algorithms for Multispectral and Hyper-spectral and Ultraspectral Imagery, 2004(4):54-62.
[16] 万余庆,谭克龙,周日平.高光谱遥感应用研究[M].北京:科学出版社,2007.
[17] 赵英时,陈冬梅,杨立明,等.遥感应用分析原理与方法[M].北京:科学出版社,2003.
[18] Karaska M A,Hugenin R L,Beacham J L,et al.AVIRIS measurements of chlorophyll, suspended minerals,dissolved organic carbon, and turbidity in the Neuse River, North Carolina[J].Photogrammetric Engineering & Remote Sensing, 2004,70(1):125-133.
[19] Lin L, Ustin S L, Lay M. Application of AVIRIS data in detection of oil-induced vegetation stress and cover change at Jornada, New Mexico[J]. Remote Sensing of Environment,2005,94:1-16.
[20] Chen Y H,Shi P J,Li X B,et al.Combined approaches for estimating vegetation cover in urban/suburban environments from remotely sensed data[J].Computers & Geosciences,2006,32:1299-1309.
[21] 耿修瑞,张兵,张霞,等.一种基于高维空间凸面单形体体积的高光谱图像解混算法[J].自然科学进展,2004(7):613-618.
[22] 薛绮,匡纲要,李智勇.基于线性混合模型的高光谱图像端元提取[J].遥感技术与应用,2004,19(3):197-201.
[23] Winter M E,Schlangen M,Winter E M. Comparison of autonomous hyperspectral endmember determination methods[J].American Society for Photogrammetry & Remote Sensing, 1999:444-451.