农业工程学报2012，Vol.28Issue(12)：176-182,封3,8.DOI:10.3969/j.issn.1002-6819.2012.12.029
水稻重金属污染胁迫光谱分析模型的区域应用与验证
Regional application and verification of spectral analysis model for assessing heavy-metal stress of rice
摘要
Abstract
It is a key issue for identifying crops under heavy-metal contamination on a large scale using satellite remote sensing data based on ground-sample spectral analysis model for evaluating crops with heavy-metal stress level. In this paper, hyperspectral data and leaf chlorophyll concentration of rice, heavy-metal concentration of soil were collected from three different polluted paddies in Changchun city, Jilin province, China, at mean time, Hyperion data were obtained. Spectral indices sensitive to heavy-metal contamination were selected by multiple stepwise regressions, and BP neural network models were created to estimate chlorophyll concentrations in rice under heavy-metal stress, which indicated the level of heavy-metal contamination. It was founded that an optimum ground-sample spectral analysis model was 4-11-7-1 network architecture with logsig thansfer function, and the classification accuracy for each pollution level was 100%. Moreover, it was successful to apply the ground-sample spectral analysis model to Hyperion data, and then achieve large-scale application in monitoring rice under heavy-metal contamination, the classification accuracy for each pollution level was more than 80%. This research may provide important references for large-scale application in the spectral model for assessing rice under heavy-metal contamination.关键词
遥感/污染/模型/Hyperion/水稻/BP神经网络/区域污染评价Key words
remote sensing/ pollution/ models/ Hyperion/ rice/ BP neural network/ regional contamination assessment分类
农业科技引用本文复制引用
李婷,刘湘南,刘美玲..水稻重金属污染胁迫光谱分析模型的区域应用与验证[J].农业工程学报,2012,28(12):176-182,封3,8.基金项目
国家自然科学基金项目(40771155) （40771155）
国家高技术研究发展计划(863项目)专项经费资助(2007AA122174) （863项目）
