项目名称: 多源遥感数据反演农作物叶面积指数中的冠层模型改进与信息量评价方法研究
项目编号: No.40801125
项目类型: 青年科学基金项目
立项/批准年度: 2009
项目学科: 金属学与金属工艺
项目作者: 姚延娟
作者单位: 北京大学
项目金额: 19万元
中文摘要: 如何应用多源遥感数据反演农作物叶面积指数是国际遥感科学研究中的难点问题。为了解决这一问题,本项目首先针对农作物中最常见的行播种植方式、建立既适用于作物成行结构又适用于水平均一结构的冠层模型,以适合行播作物的关键生长期;以此模型为基础,本项目基于信息熵和冠层模型,发展评价遥感数据中含有相对于确定地表参数信息量的方法;从而解决目前遥感数据信息量评价方法研究比较薄弱的问题,提高多源遥感数据的利用率。同时开展对多源遥感数据的优化分析和对反演算法的改进,提高农作物叶面积指数的反演精度。项目提出的信息量评价方法,对于促进多源遥感信息的综合反演和应用、推动定量遥感在资源环境和地学领域的应用,有重要的科学意义和应用价值。
中文关键词: 遥感数据信息量;冠层模型;多源遥感数据;叶面积指数;反演
英文摘要: It is a difficult problem to invert leaf area index (LAI) using multi-angular and multi-spectral remote sensing data in the international scientific research domain. To solve this problem, firstly, we proposed a canopy reflectance model for the row-planted crop in this project, and this model is suitable for the canopy of row structure and continuous structure. Based on this canopy reflectance model, we also proposed a technique called the entropy-difference analysis, which is based on the information theory, to evaluate the information content of remote sensing data for the LAI inversion. The proposed information evaluation method is not only a supplement for information evaluation in current, but also can make full use of remote sensing data. The LAI can be inverted with high accuracy based on the canopy reflectance model and optimal remote sensing data. The proposed information evaluation method can also be used in integrated multi-source inversion and the environment and geo-science application of the quantitative remote sensing.
英文关键词: information content of remote sensing data; canopy reflectance model; multi-angular/spectral remote sensing data; leaf area index; inversion