| 引用本文: | 李正国,唐华俊,杨 鹏,吴文斌,陈仲新,周清波,张 莉,邹金秋.植被物候特征的遥感提取与农业应用综述[J].中国农业资源与区划,2012,33(5):20~28 |
| |
|
| 摘要: |
| 多时相遥感数据因其高时效、宽范围和低成本等优点正被广泛应用于对地观测活动中，为大区域 尺度掌握植被/作物空间格局提供了新的科学技术手段。通过对相关研究进展的回顾，该文系统归纳了植 被物候特征遥感提取的关键步骤。首先从数据获取与处理方面，整理了目前常用的NDVI数据集以及预处 理方法等相关背景信息;其次从提取原理、假设条件以及适用性等角度，比较了目前用于时序遥感数据重 构和特征提取的常用技术方法;在此基础上，归纳了基于时序遥感数据拟合曲线提取的植被物候特征及其 农业内涵意义;最后，结合目前的农业应用，探讨了其在识别作物物候期、确定种植制度以及提高遥感估 产精度等专业领域的应用方向，以期为区域尺度上生态管理与农业生产提供科学支持。 |
| 关键词: 多时相遥感数据 植被物候特征 农业应用 NDVI |
| DOI：10.7621/cjarrp.1005-9121.20120504 |
| 分类号: |
| 基金项目:农业部“948”项目（2011—G6）国家重点基础研究发展计划项目（“973”计划）（2010CB951502），国家自然科学基金项 目（40930101，41171328，41201089），中央级公益性科研院所专项资金项目（IARRP-2011-15） |
|
| PROGRESS IN REMOTE SENSING OF VEGETATION PHENOLOGY AND ITS APPLICATION IN AGRICULTURE |
|
Li Zhengguo, Tang Huajun, Yang Peng, Wu Wengbin, Chen Zhongxin, Zhou Qingbo, Zhang Li, Zou Jinqiu
|
|
Key Laboratory of Resources Remote Sensing & Digital Agriculture， Ministry of Agriculture， Beijing 100081， China/Institute of Agricultural Resources & Regional Planning， Chinese Academy of Agricultural Sciences， Beijing 100081， China
|
| Abstract: |
| Remote sensing technique had been proven to offer an optimal approach for detecting and monitoring the spatial patterns of vegetation because of its high temporal resolution， wide spatial coverage and low cost. The aim of this paper was to address the methodological techniques acquiring vegetation phenological information based on multi-temporal remote sensing archives and derive a more thorough understanding of the currently on-going re- search. First， the historical background of the processing methods for generalizing NDVI dataset from remote sens- ing dataset was reviewed; Second， this paper compared the current performed NDVI time series fitting techniques and phenological parameters extraction algorithms from the viewpoint of theorical hypothesis and suitability; On this basis， it summarized and interpreted the applications of employing NDVI time series dataset and phenological ex- traction algorithms into identifying agricultural phenological characteristics. Finally， with respect to the current re- search concerns of scientific community， the applications of the extracted phenological characteristics were dis- cussed， including how to identify major crop phenophases， to determine cropping systems and to improve crop yield estimation. The results were expected to provide scientific knowledge for regional ecological management and agri- cultural production. |
| Key words: multi-temporal remote sensing data vegetation phenology characteristics agricultural application NDVI |
