{"title":"遥感多光谱影像玉米高程与光谱指标的关系分析","authors":"Aleem Khaliq, M. Musci, M. Chiaberge","doi":"10.1109/AIPR.2018.8707373","DOIUrl":null,"url":null,"abstract":"For maize crop, biophysical parameters such as canopy height and above ground biomass are the crucial agro-ecological indicator that can be used to describe the crop growth, photosynthetic efficiency and carbon stock. Remote sensing is widely used approach and most appropriate source in terms of area coverage that can be used to monitor vegetative conditions over the large area. In this study, sentinel-2 multispectral imagery is used to calculate spectral vegetation indices over the different maize growth period using some visible bands including near infrared spectrum. The relationship has been established and analyzed between maize biophysical variables (height of the canopy and above ground biomass) collected during the field measurements and derived spectral vegetation indices using simple linear regression and pearson correlation to exploit the possibility of using satellite imagery for estimation of crop biophysical parameters.","PeriodicalId":230582,"journal":{"name":"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Analyzing relationship between maize height and spectral indices derived from remotely sensed multispectral imagery\",\"authors\":\"Aleem Khaliq, M. Musci, M. Chiaberge\",\"doi\":\"10.1109/AIPR.2018.8707373\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For maize crop, biophysical parameters such as canopy height and above ground biomass are the crucial agro-ecological indicator that can be used to describe the crop growth, photosynthetic efficiency and carbon stock. Remote sensing is widely used approach and most appropriate source in terms of area coverage that can be used to monitor vegetative conditions over the large area. In this study, sentinel-2 multispectral imagery is used to calculate spectral vegetation indices over the different maize growth period using some visible bands including near infrared spectrum. The relationship has been established and analyzed between maize biophysical variables (height of the canopy and above ground biomass) collected during the field measurements and derived spectral vegetation indices using simple linear regression and pearson correlation to exploit the possibility of using satellite imagery for estimation of crop biophysical parameters.\",\"PeriodicalId\":230582,\"journal\":{\"name\":\"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2018.8707373\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2018.8707373","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analyzing relationship between maize height and spectral indices derived from remotely sensed multispectral imagery
For maize crop, biophysical parameters such as canopy height and above ground biomass are the crucial agro-ecological indicator that can be used to describe the crop growth, photosynthetic efficiency and carbon stock. Remote sensing is widely used approach and most appropriate source in terms of area coverage that can be used to monitor vegetative conditions over the large area. In this study, sentinel-2 multispectral imagery is used to calculate spectral vegetation indices over the different maize growth period using some visible bands including near infrared spectrum. The relationship has been established and analyzed between maize biophysical variables (height of the canopy and above ground biomass) collected during the field measurements and derived spectral vegetation indices using simple linear regression and pearson correlation to exploit the possibility of using satellite imagery for estimation of crop biophysical parameters.