基于MODIS时序NDVI主要农作物种植信息提取研究

发布时间：2018-06-28 21:25

本文选题：遥感 + 农作物种植信息提取　；参考：《自然资源学报》2017年10期

【摘要】：农业在黄河三角洲地区占有重要地位,及时、准确地掌握该地区农作物分布信息对政府有关部门制定农业政策、指导农业生产具有十分重要的意义。时序植被指数能够反映农作物物候特征,帮助识别农作物类型,在农作物种植信息提取方面具有明显优势。论文选取2014年MOD09Q1时序遥感数据集,以黄河三角洲主要农作物为研究对象,利用Harmonic Analysis of NDVI Time-Series(Hants)滤波重构NDVI时序曲线,通过对比待分像元NDVI时序曲线与参考时序曲线的相似性,实现农作物种植信息提取。对分类结果进行面积统计和空间分布精度检验:冬小麦、棉花、玉米的面积提取精度分别达到96.8%、95.5%、85.1%,空间匹配总体精度达86.9%。结果表明该方法有效可行,能够为该地区农业监测提供技术基础。
[Abstract]:Agriculture occupies an important position in the the Yellow River Delta region. Timely and accurate grasp of the distribution information of crops in this area is of great significance for the government departments concerned to formulate agricultural policies and guide agricultural production. The time series vegetation index can reflect the characteristics of Crop Phenology, help identify the types of crops, and extract information from crop planting. In this paper, the paper selects the 2014 MOD09Q1 temporal remote sensing data set, taking the main crops in the the Yellow River Delta as the research object, using the Harmonic Analysis of NDVI Time-Series (Hants) filter to reconstruct the NDVI timing curve, and by comparing the similarity of the NDVI timing curve with the reference time sequence curve, the crop planting letter is realized. The area statistics and spatial distribution precision test of the classification results: the area extraction precision of winter wheat, cotton and corn reached 96.8%, 95.5%, 85.1% respectively, and the overall precision of space matching reached 86.9%.. The results showed that the method was effective and feasible, and it could provide a technical basis for agricultural monitoring in this area.
【作者单位】：中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室;中国科学院大学;
【基金】：国家科技支撑计划项目(2013BAD05B03) 国家自然科学基金项目(41671422,41271407,41471335) 国家国际科技合作专项项目(2012DFG22050)~~
【分类号】：S127

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