农业机械学报2018，Vol.49Issue(4)：212-221,10.DOI:10.6041/j.issn.1000-1298.2018.04.024
基于无人机遥感与植被指数的冬小麦覆盖度提取方法
Fractional Vegetation Cover Extraction Method of Winter Wheat Based on UAV Remote Sensing and Vegetation Index
摘要
Abstract
Fractional vegetation cover (FVC) is an important index of crop growth status,as well as one of the major factors affecting crop photosynthesis,transpiration and water use efficiency.Currently,there are some problems that satellite remote sensing technology widely used is difficult to meet the requirement of fractional vegetation cover extraction in field scale for the low temporal and spatial resolution,the extraction of vegetation coverage based on artificial ground image is time consuming and laborious,the operating cost is high,and the remote sensing image acquired by the unmanned aerial vehicle (UAV) remote sensing system without integrated gimbal is geometrically distorted.To address the issues above,a UAV multi-spectral remote sensing image acquisition system integrated gimbal and position and orientation system (POS)data acquisition modules was developed,which had the ability to acquire the reflection information for red,green and near-infrared bands between 520 nm and 920 nm.Taking winter wheat as an example,UAV flying experiments were conducted in different growing stages,covering over-wintering period,jointing stage,flag leaf stage and heading date,with 55 m flying height and 2.2 cm multispectral image resolution.A rapid FVC extraction method was proposed,combining supervised classification with vegetation index histogram,by which the classification thresholds of normalized difference vegetation index (NDVI),soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI) for field wheat were obtained with the value of 0.475 6,0.705 6 and 0.635 0,respectively.The FVC reference was extracted based on the visible light remote sensing image with a high spatial resolution of 0.8 cm captured synchronously with multi-spectral image.The results showed that the fractional vegetation cover of winter wheat could be extracted by multi-spectrum remote sensing technology and vegetation index method with good accuracy.Compared with SAVI and MSAVI,the extraction result based on NDVI classification threshold was the most accurate with the smallest absolute error.The use of UAV carrying a multi-spectral camera and vegetation index threshold method provided a new way to extract fractional vegetation cover,which had certain reference value for the extraction of fractional vegetation cover in field scale.关键词
冬小麦/植被覆盖度/无人机/多光谱遥感影像/植被指数/监督分类Key words
winter wheat/fractional vegetation cover/unmanned aerial vehicle/multispectral remote sensing image/vegetation index/supervision classification分类
信息技术与安全科学引用本文复制引用
牛亚晓,张立元,韩文霆,邵国敏..基于无人机遥感与植被指数的冬小麦覆盖度提取方法[J].农业机械学报,2018,49(4):212-221,10.基金项目
国家重点研发计划项目(2017YFC0403203)、新疆维吾尔自治区科技支疆项目(2016E02105)、旱区作物需水无人机遥感与精准灌溉技术及装备研发平台项目(2017-C03)和陕西省水利科技项目(2017SLKJ-7) （2017YFC0403203）
