Recent Progresses in Monitoring Crop Spatial Patterns by Using Remote Sensing Technologies
Recent Progresses in Monitoring Crop Spatial Patterns by Using Remote Sensing Technologies
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发表时间：
2010
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通讯作者：
Tang Huajun;Wu Wenbin;Yang Peng;Zhou Qingbo;Chen Zhongxin
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作者：
Tang Huajun;Wu Wenbin;Yang Peng;Zhou Qingbo;Chen Zhongxin
遥感作为一种高新技术，具有时间分辨率高、覆盖范围广、成本低等优点，目前已广泛应用于对地观测活动，为农作物空间格局的监测提供了有力的工具。本文在系统总结近10年来农作物空间格局遥感监测研究进展及其理论基础的基础上，研究表明，利用卫星遥感器记录的不同作物的光谱特征差异，可以实现对作物种植面积的监测，目前主要有三种方法：一是利用光谱特征差异，利用光谱特征进行作物种植面积监测;二是利用光谱特征进行作物种植面积监测;三是利用光谱特征进行作物种植面积监测。复种系统的遥感识别方法主要有基于光谱的识别方法、基于物候的识别方法和基于多种数据融合的识别方法。复种系统的遥感制图主要基于作物生长曲线，作物生长曲线可以从平滑的时间序列植被指数（VI）数据中获得。此外，如何构建遥感影像分类的理论和技术体系，发展和验证遥感影像分类方法，优化时间平滑方法-系列化数据，提高信息的自动提取能力，将是该领域未来的主要发展趋势。
As a new high-technology with an advantage of high temporal resolution,wide coverage and low cost,remote sensing is currently used in a wide arrange of earth observation activities and thus provides a useful tool to detect and monitor the spatial patterns of crop cultivation.Based on the systematic summary of the progress of studies in remote-sensing-based monitoring of spatial patterns of agricultural crops in the latest decade,including its theories,methods and applications,a series of problems that should be urgently resolved in the study are put forward,and some important study directions and priorities for future are viewed.Studies show that crop acreage can be monitored according to the differences in spectral characteristics of different crops,which are normally recorded by the satellite sensors.There are three major approaches used for crop acreage monitoring:spectral-based identification,phenology-based identification and multiple data-fusion-based identification methods.Mapping multiple cropping systems using remote sensing is mainly based on the crop growth curves,which can be derived from the smoothed time-series vegetation index(VI) data.Furthermore,cropping patterns can be also examined through discriminating the crop growth period from variations in time-series VI data and characteristics of different cropping patterns.How to construct the theoretical and technological systems,to develop and verify the image classification methods,to optimize the smoothing methods for time-series data and to improve the capability of automatic extraction of information could be the major development trends of this field in the future.