首页 | 官方网站   微博 | 高级检索  
     

高光谱遥感土壤湿度信息提取研究
引用本文:刘伟东,Fr&#;d&#;ricBaret,张兵,郑兰芬,童庆禧.高光谱遥感土壤湿度信息提取研究[J].土壤学报,2004,41(5):700-706.
作者姓名:刘伟东  Fr&#;d&#;ricBaret  张兵  郑兰芬  童庆禧
作者单位:1. 中国气象局北京城市气象研究所,北京,100089;Unité Chimat,Sol et Environnement-Institut National de la Recherche Agronomique,Avignon,84914,France;中国科学院遥感应用研究所遥感信息科学开放实验室,北京,100101
2. Unité Chimat,Sol et Environnement-Institut National de la Recherche Agronomique,Avignon,84914,France
3. 中国科学院遥感应用研究所遥感信息科学开放实验室,北京,100101
基金项目:北京市科委《奥运会气象保障科学技术试验与研究》项目资助
摘    要:精准农作管理中土壤水分、土壤养分等的空间信息分布 ,可通过高光谱遥感传感器获得。本文通过对土壤的光谱反射率与土壤的表面湿度进行分析 ,比较 5种方法在反演土壤表面湿度的能力 ,并对小汤山精准农业试验区的土壤表面湿度进行高光谱填图 ,建立了较为精细的土壤水分空间分布图 ,对高光谱遥感在精准农业中深入应用进行了有效探索。

关 键 词:土壤表面湿度  反射率  高光谱遥感  精准农业
收稿时间:2003/6/27 0:00:00
修稿时间:2/4/2004 12:00:00 AM

EXTRACTION OF SOIL MOISTURE INFORMATION BY HYPERSPECTRAL REMOTE SENSING
Liu Weidong,Fr&#;d&#;ricBaret,Zhang Bing,Zheng Lanfen and Tong Qingxi.EXTRACTION OF SOIL MOISTURE INFORMATION BY HYPERSPECTRAL REMOTE SENSING[J].Acta Pedologica Sinica,2004,41(5):700-706.
Authors:Liu Weidong  Fr&#;d&#;ricBaret  Zhang Bing  Zheng Lanfen and Tong Qingxi
Affiliation:Beijing Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China;UnitéClimat, Sol et Environnement-Institut National de la Recherche Agronomique, Avignon 84914, France;Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China;UnitéClimat, Sol et Environnement-Institut National de la Recherche Agronomique, Avignon 84914, France;Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China;Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China;Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China
Abstract:Development of precision farming calls urgently for remote sensing techniques capable of providing timely accu rate ground information.Estimation of soil moisture from reflectance measurements in the solar spectral domain (400~2 500 nm) was investigated.For this purpose,18 soils representing a large range of permanent characteristics were gathered for the test.Reflectance data were measured in the laboratory during the soil drying process with a high spectral resolution spectroradiometer.Five approaches were compared.The first one was based on single-band reflectance and on calibration of the reflectance data by the reflectance of the corresponding soil under dry conditions,the second and the third approaches on either reflectance deriva tives or absorbance derivatives and the fourth and fifth approaches on differences between reflectance and absorbance observed in two non consecutive bands.In the first step,the relationships were calibrated over half the dataset (nine soils) with emphasis on selection of the most pertinent spectral bands.Results showed that,for the first approach,the bands corresponding to the highest water absorption ca pacities (1 944 nm) yielded the best soil moisture retrieval performance.For the second and third approaches,the bands corre sponding to sharp edges of the water absorption features performed better (1 834 nm for the reflectance derivatives and 1 622 nm for the absorbance derivatives).The fourth and fifth approaches could be considered as a generalization of the derivative approach when bands were no longer consecutive.The best performance was achieved when the bands were not too far apart.The best overall retrieval performances were achieved with the absorbance derivatives and the absorbance difference,confirming the non linear character of the relationship between soil moisture and reflectance.
Keywords:Soil moisture  Reflectance  Hyperspectral remote sensing  Precision agriculture
本文献已被 万方数据 等数据库收录!
点击此处可从《土壤学报》浏览原始摘要信息
点击此处可从《土壤学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号