基于多源遥感的天然草地营养探测机理及模型研究

项目名称： 基于多源遥感的天然草地营养探测机理及模型研究

项目编号： No.41461081

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 王迅

作者单位： 青海省畜牧兽医科学院

项目金额： 50万元

中文摘要： 天然草地草畜营养平衡，是在以自然放牧为主的天然草地，为保持草地生态系统良性循环，使草地营养输出量与家畜营养需求量保持动态平衡。制定科学规划，有效地开展草畜营养平衡，对充分利用有限的草地资源，有效防止草地退化，提高草地利用有着十分重要的意义。草地营养物质输出量信息是科学制定草畜营养平衡的关键，如何快速获取草地营养动态输出量，准确预测未来草场的质量，是制定草畜营养平衡的难题，目前，基于遥感的方法缺乏对天然草地营养动态的探测。本项目旨在从草畜营养平衡对草地营养输出量数据的需求出发，开展天然草地营养遥感探测方法研究，建立草地营养动态探测模型。服务于模型对高时相高精度空间动态数据的需求，将开展多源数据融合及同化应用模型研究，服务于模型对不同营养成分探测精度的需求，将开展草地营养成分多源遥感与近红外/高光谱探测模型的综合研究，最终建立多源遥感反演的草地营养成分动态探测模型。

中文关键词： 草地营养；高光谱遥感；探测；营养载畜量

英文摘要： The nutritional balance between native grassland and livestock is to keeping the grassland nutrients output and livestock nutrition demand balanced in order to maintain the grassland ecosystem virtuous circle in the free farming on natural grassland. Making scientific planning and carrying out nutritional balance effectively is significance to make full use of limited grassland resources, to effectively prevent grassland degradation and to improve the grassland utilization degree. The grassland nutrients output information is the key issue to make scientific policy of nutritional balance. How to obtain the grassland nutrients output information quickly and to predict the quality of future pasture are the challenge to fulfill nutritional balance. At present, there is lack of natural grassland nutrient dynamic detection based on remote sensing. Taking into account the demands of nutritional balance of native grassland and livestock for grassland nutrients, this proposal will study on the estimation mechanism for grassland nutrient with remote sensing method and establish a detecting model for grassland nutrient. To serve on the requirement for high-temporal and high-spatial data, the research will study on multi-source data fusion and assimilation application to obtain dynamic nutrient inputs for detecting models. To serve on the requirement for different nutrient index detection accuracy based on remote sensing, this project will study on mutlti-source remote sensing and NIR/hyperspectral data to acquire dynamic nutrients retrieve index inputs for models. Based on ground-measured and chemical analysis, we will optimize the model parameters and finally establish a high-performance detecting model for grassland nutrients based on remote sensing data.

英文关键词： grass nutrition;hyperspectral;detection;nutrition stocking rate