摘要
及时准确地获取苜蓿空间分布信息有利于对草业生产发展和管理提供科学数据支撑。该研究基于GF-1/WFV和Sentinel-2遥感影像,以甘肃省金昌市作为研究区,构建了苜蓿的归一化植被指数(Normalized Difference Vegetation Index,NDVI)数据集,并结合苜蓿光谱反射率随生育期的变化规律,提出一种利用MATLAB寻峰函数(Findpeaks)提取苜蓿遥感特征的方法,通过确定最小峰值突出(Minimum Peak Prominence,MPP)值实现金昌市苜蓿空间分布信息的提取。研究结果表明,基于Sentinel-2遥感数据的识别苜蓿精度优于GF-1/WFV,识别精度和Kappa系数在85%和0.7以上,主要是由于Sentinel-2数据的NDVI时间序列曲线密度较GF-1/WFV大,可以更好地识别苜蓿刈割前后的关键时间点;寻谷法的苜蓿提取总体精度、Kappa系数、用户精度、制图精度指标均比寻峰法高,基于Sentinel-2影像的寻谷法苜蓿遥感识别总体精度为92.25%,Kappa系数为0.81,位置精度为86.44%;2019年金昌市苜蓿空间分布整体呈现从北到南逐渐增多的趋势,统计得到苜蓿种植面积为15449.07 hm^(2),其中金川区的苜蓿面积为1353.42 hm^(2),占金昌市苜蓿总面积的8.76%;永昌县的苜蓿面积为14095.65 hm^(2),占总面积的91.24%。研究结果证实,基于Sentinel-2遥感数据的寻谷法可以有效识别苜蓿空间分布,对于实现草牧场精准化管理和草牧业生产信息精准监测具有重要意义。
Alfalfa is a perennial crop to serve as a key feed variety for the development of herbivorous animal husbandry and food safety in China.Timely and accurate acquisition of alfalfa spatial distribution can greatly contribute to the data support for the scientific management of grass production.In this study,a new extraction was proposed to obtain the remote sensing characteristics of alfalfa using the Findpeaks function of MATLAB,combined with the change of spectral reflectance of alfalfa with the growth stage.A Normalized Difference Vegetation Index(NDVI)dataset was also constructed using high-resolution GF-1/WFV(Wide Field of View)and Sentinel-2 remote sensing images in Jinchang City,Gansu Province,China.The limitation of automatic identification and area extraction was solved to extract the spatial distribution of alfalfa via determining Minimum Peak Prominence(MPP)value.Firstly,an analysis was made on the time series of alfalfa NDVI.It was found that the alfalfa NDVI increased many times,as the peak value decreased in one year.Specifically,there were many peaks and troughs in the NDVI time series curve,among which the peaks represented the high value of NDVI in a growing period(the flourishing period of alfalfa growth and development),whereas,the troughs reflected the alfalfa from the peak period to the cutting state.Then,a field investigation was conducted to determine the peaks and troughs number of alfalfa,where the trough number was 3-4,and the peak number was 3-5 in the NDVI time series curve.Thirdly,a verification of position accuracy found that the classification accuracy increased when the value of MPP was in the range of 0.3 to 0.4 and reached the maximum when the value of MPP was 0.4,while the classification accuracy tended to decrease with the increase of MPP value.Therefore,the MPP value of 0.4 was set to extract the potential spatial distribution of alfalfa using the Findpeaks function of MATLAB software.As such,the spatial distribution dataset of alfalfa planting area was established in the study
作者
包旭莹
王燕
冯琦胜
葛静
侯蒙京
刘畅宇
高新华
梁天刚
Bao Xuying;Wang Yan;Feng Qisheng;Ge Jing;Hou Mengjing;Liu Changyu;Gao Xinhua;Liang Tiangang(State Key Laboratory of Grassland Agro-ecosystem,Key Laboratory of Grassland Livestock Industry Innovation,Ministry of Agriculture and Rural Affairs,Engineering Research Center of Grassland Industry,Ministry of Education,College of Pastoral Agriculture Science and Technology,Lanzhou University,Lanzhou 730020,China;Chongxin County No.1 Middle School,Pingliang 744200,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2021年第16期153-160,共8页
Transactions of the Chinese Society of Agricultural Engineering
基金
现代农业产业技术体系建设专项资金(CARS-34)
中国工程院重点咨询研究项目(2021-HZ-5,2020-XZ-29,2018-XZ-25)
兰州大学中央高校基本科研业务费专项(lzujbky-2020-kb29)
长江学者和创新团队发展计划(IRT_17R50)。