摘要
为了解决常规卫星遥感叶面积指数真实性检验方法存在的破坏样地植被、操作复杂、耗时费力,且难以用于对应大范围的植被采样等问题,该文以安徽省来安县为研究区,利用实测水稻冠层光谱结合GF1-WFV传感器进行光谱重采样并计算水稻NDVI,基于此进行LAI反演建模,通过光谱计算的LAI反演结果对GF-1星多光谱遥感水稻LAI的反演结果进行真实性检验,并结合野外LAI观测数据证明了该方法的有效性和可行性。研究表明,该方法操作简单,准确度高,大大减少了野外试验的工作量,为快速、准确获取大量真实性检验数据及定量化应用提供了有效的途径。
Validation of satellite remote sensing leaf area index (LAI)products is the important technical link of quantitative applications of vegetation LAI inversion on satellite remote sensing.Conventional validation methods are mostly based on vegetation leaf collection from field,or through direct measurement by instruments.It not only causes damage to vegetation samples,and operation is complex,time-consuming.It is also difficult to use for the sample corresponding to a wide range of vegetation.To solve the above problems,this paper takes Lai'an in Anhui Province as the research area.Combined GF1-WFV sensor to resample the mea measured spectra of rice canopy for NDVI computing,based on this to conduct LAI inversion model. Then using the results of LAI inversion from spectra computing to validate the results of rice LAI inversion on GF-1 satellite multispectral remote sensing,and combined with field LAI data to demonstrate the effectiveness and feasibility of this method. Study shows that this method is simple,accurate,and it can greatly reduce the workload of the field experiments.It also provides an effective way for quickly and accurately getting a lot of validation data and quantitative applications.
出处
《遥感信息》
CSCD
北大核心
2015年第5期62-68,共7页
Remote Sensing Information
基金
国家科技重大专项(30-Y20A01-9003-12/13)
国家重点基础研究发展计划项目(2010CB951503)
