{"title":"基于高光谱和分数阶差法估算樟树叶片的叶绿素含量","authors":"Baocheng Yang, Haina Zhang, Xianghui Lu, Yue Zhang, Haolong Wan, Xin Luo, Jie Zhang","doi":"10.1080/01431161.2024.2372064","DOIUrl":null,"url":null,"abstract":"Hyperspectral remote sensing combined with data preprocessing techniques and machine learning algorithms is a new way to efficiently estimate plant SPAD. In this study, the raw hyperspectral reflec...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"55 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of chlorophyll content of Cinnamomum camphora leaves based on hyperspectral and fractional order differentiation\",\"authors\":\"Baocheng Yang, Haina Zhang, Xianghui Lu, Yue Zhang, Haolong Wan, Xin Luo, Jie Zhang\",\"doi\":\"10.1080/01431161.2024.2372064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hyperspectral remote sensing combined with data preprocessing techniques and machine learning algorithms is a new way to efficiently estimate plant SPAD. In this study, the raw hyperspectral reflec...\",\"PeriodicalId\":14369,\"journal\":{\"name\":\"International Journal of Remote Sensing\",\"volume\":\"55 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/01431161.2024.2372064\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/01431161.2024.2372064","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
Estimation of chlorophyll content of Cinnamomum camphora leaves based on hyperspectral and fractional order differentiation
Hyperspectral remote sensing combined with data preprocessing techniques and machine learning algorithms is a new way to efficiently estimate plant SPAD. In this study, the raw hyperspectral reflec...
期刊介绍：
The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data. The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system. Principal topics include:
• Remotely sensed data collection, analysis, interpretation and display.
• Surveying from space, air, water and ground platforms.
• Imaging and related sensors.
• Image processing.
• Use of remotely sensed data.
• Economic surveys and cost-benefit analyses.
• Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).
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