陈尔学2,,,
李增元2,
杨浩3,
赵磊2
1.西南林业大学林学院 昆明 650224
2.中国林业科学研究院资源信息研究所 北京 100091
3.北京市农林科学院北京农业信息技术研究中心 北京 100097
基金项目:国家自然科学基金(31860240),国家重点研发计划(2017YFB0502700)
详细信息
作者简介:张王菲,女,山西阳城人,博士,西南林业大学林学院,副教授,硕士生导师,主要研究方向为农林业微波遥感应用研究
陈尔学,男,山东菏泽人,博士,中国林业科学研究院资源信息研究所研究员,博士生导师,主要研究方向为微波遥感机理及应用
李增元,男,内蒙古呼和浩特人,博士,研究员,中国林业科学研究院资源信息研究所研究员,博士生导师,主要研究方向为微波遥感机理及应用
通讯作者:陈尔学 chenerx@caf.ac.cn
责任主编:廖明生 Corresponding Editor: LIAO Mingsheng中图分类号:TN957.52
计量
文章访问数:1547
HTML全文浏览量:599
PDF下载量:342
被引次数:0
出版历程
收稿日期:2020-04-30
修回日期:2020-06-15
网络出版日期:2020-06-28
Review of Applications of Radar Remote Sensing in Agriculture (in English)
ZHANG Wangfei1,CHEN Erxue2,,,
LI Zengyuan2,
YANG Hao3,
ZHAO Lei2
1. College of Forestry, Southwest Forestry University, Kunming 650224, China
2. Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
3. Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
Funds:The National Natural Science Foundation of China (31860240), The National Key R & D Program of China (2017YFB0502700)
More Information
Corresponding author:CHEN Erxue, chenerx@caf.ac.cn
摘要
摘要:雷达遥感具有全天时、全天候监测的能力,对植被具有一定的穿透能力,对植被散射体形状、结构、介电常数敏感;这些特性使得其在农业应用中极具潜力。该文首先介绍了雷达遥感在农业中的应用领域,概略总结了目前在农作物识别与分类、农田土壤水分反演、农作物长势监测等多个领域研究的综述文献;然后分别阐述了雷达散射计和各类SAR特征(包括:SAR后向散射特征、极化特征、干涉特征、层析特征)在农业各领域中应用的现状和取得的研究成果,最后结合农业应用需求和SAR技术发展总结了目前研究中存在的问题和原因,并对未来的发展进行了展望。
关键词:雷达遥感/
农业/
后向散射特征/
极化特征/
干涉特征/
层析特征
Abstract:Active radar remote sensing technology, with its capability of acquiring all-weather data, has great potential for agricultural monitoring. This technology can penetrate vegetation cover more deeply than optical sensors and has sensitivity to the shapes, structures, and dielectric constants of vegetation scatterers. In this paper, we discuss the applications of radar remote sensing in crop identification, cropland soil moisture inversion, crop growth parameter inversion, crop phenology retrieval, agricultural disaster monitoring, and crop yield estimation. We review several specific papers focusing these fields, and then describe the results obtained using information extracted from radar scatterometers and Synthetic Aperture Radar (SAR). Extracted SAR data include characterizations of backscattering, polarimetry, interferometry, and tomography. Lastly, we summarize the problems faced by radar applications in agriculture and consider the future trend of these applications.
Key words:Radar remote sensing/
Agriculture/
Backscattering characterizations/
Polarimetric characterizations/
Interferometric characterizations/
Tomography characterizations
PDF全文下载地址:
https://plugin.sowise.cn/viewpdf/198_e9fb6878-88f4-4b1d-8e7f-aeaee315cb70_R20051