小麦氮素组分时空分布星地遥感监测机理与优化算法研究

Nitrogen status obtained through the current method of routine analysis or the satellite remote sensing monitoring based on leaves nitrogen cannot represent the canopy nitrogen level. In order to solve the practical problem and meet wheat production requirement well. the theory and experiment of monitoring temporal and spatial distribution of wheat nitrogen components based on satellite and ground remote sensing data were carried out. The satellite data applied in the research were HJ-1A/1B and CBERS-02B images. Agronomy knowledge was integrated to explore the mechanism and algorithm of monitoring temporal and spatial distribution of wheat nitrogen components through the satellite and ground remote sensing data, establish universal models of monitoring nitrogen components with high precision based on remote sensing data, and realize the objective for monitoring canopy nitrogen status through remote sensing. This study can provide a theoretical basis for the cooperative retrieval by combining ground and satellite remote sensing data in precision agriculture, and has the vital significance for improving the utilization rate of wheat nitrogen fertilizer, promoting rational utilization of nitrogen fertilizer, increasing wheat productivity, improving wheat quality and protecting environment. The main research work is listed as follows: 1)Carrying out the mechanism of monitoring temporal and spatial distribution of wheat nitrogen components based on ground remote sensing data, mainly exploring the disciplinarian of wheat nitrogen vertical distribution in spatial dimension and its spectral responses, and analyzing the quantitative relationships between wheat nitrogen vertical distribution, nitrogen in different organs and spectral parameters. 2)Exploring the mechanism of monitoring temporal and spatial distribution of wheat nitrogen components utilizing HJ-1A/1B and CBERS-02B images. 3)Exploring the optimization algorithm and models of monitoring temporal and spatial distribution of wheat nitrogen components. 4)Studying the development and application of developing the monitoring system of wheat nitrogen.

针对当前氮素获取中采用的常规分析或基于若干叶片的遥感监测不能代表冠层氮素水平这一亟待解决的实际问题和小麦生产需求。项目基于地面遥感数据、HJ-1A/1B和CBERS-02B影像数据，开展小麦氮素组分时空分布遥感监测理论和实验，融合农学知识探索氮素组分时空分布遥感监测机理与算法，建立较高精度的普适性氮素遥感监测模型，实现冠层氮素监测，为精准农业中星地遥感协同反演奠定理论基础，对提高小麦氮素利用率，合理施氮，提高产量、改善品质以及保护环境都有重要意义。研究内容包括：1）开展基于地面遥感的小麦氮素组分时空分布的监测机理研究，重点探索空间维上氮素组分垂直分布规律及其光谱响应和不同器官氮素与光谱参量间的定量关系；2）开展基于HJ-1A/1B和CBERS-02B影像的小麦氮素组分时空分布的监测机理研究；3）开展小麦氮素组分时空分布星地遥感监测优化算法与模型研究；4）开发及应用小麦氮素遥感监测系统。

1、项目背景.针对当前氮素获取中采用的常规分析或基于若干叶片的遥感监测不能代表冠层氮素水平这一亟待解决的实际问题和小麦生产需求。.2、主要研究内容.（1）研究基于地面遥感的小麦氮素组分时空分布的监测机理；（2）开展基于HJ-1A/1B影像的小麦氮素及其他相关生长指标时空分布的监测机理研究；（3）开展与氮素直接相关生长指标遥感监测优化算法与模型研究；（4）开发了小麦长势遥感监测系统及制定了长势遥感监测省级农业标准。.3、重要结果.已发表研究论文15篇，其中SCI 3篇、EI 4篇，主编出版专著1部，获软件著作权1项，申请发明专利1项，制定省级标准1项。主要结果如下：.（1）明确了小麦氮素组分与原始光谱反射率、一阶微分光谱以及基于光谱位置、基于光谱面积和基于光谱植被指数等光谱特征变量与氮素组分的定量关系，并构建监测模型，认为植被指数的归一化变量（SDr－SDb）/（SDr＋SDb）监测小麦氮素组分更为理想。.（2）明确了基于HJ-1A/1B影像的小麦叶片氮素含量遥感植被指数变换组合监测模式，认为拔节期用N（SIPI，EVI）、孕穗期用D（PSRI，DVI）和开花期用SIPI监测叶片氮素含量更可行，且精度较高。.（3）明确了基于HJ-1A/1B影像的小麦叶片叶绿素含量遥感植被指数变换组合模式，认为拔节期用N（NDVI，GNDVI）、孕穗期用R（NDVI，GNDVI）和开花期用D（NDVI，GNDVI）监测叶片叶绿素含量更可行，且精度较高。.（4）明确了与氮素组分密切相关的籽粒蛋白质含量以及理论产量和实际产量遥感监测优化算法与机理，认为PLS算法更适宜监测与氮素直接相关的小麦生长指标。.（5）开发了小麦长势遥感监测系统并制定了长势遥感监测省级农业标准。.4、关键科学意义.本研究有助于阐明小麦氮素及其他相关指标遥感监测机理，提高小麦长势遥感监测精度，增强监测模型的普适性，更有效地实施精确变量氮肥优化管理，为精准农业中星地遥感协同反演奠定理论基础，为小麦养分信息获取与诊断决策提供理论、模型和方法支持,尤其对基于国产自主卫星氮素监测研究具有重要的科学研究意义。