{"title":"利用植被偏振测量反演太阳诱导的叶绿素荧光","authors":"Haiyan Yao, Ziying Li, Yang Han, Haofang Niu, Tianyi Hao, Yuyu Zhou","doi":"10.14358/pers.87.5.331","DOIUrl":null,"url":null,"abstract":"In vegetation remote sensing, the apparent radiation of the vegetation canopy is often combined with three components derived from different parts of vegetation that have different production mechanisms and optical properties: volume scattering Lvol, polarized light Lpol,\n and chlorophyll fluorescence ChlF. The chlorophyll fluorescence plays a very important role in vegetation remote sensing, and the polarization information in vegetation remote sensing has become an effective way to characterize the physical characteristics of vegetation. This study analyzes\n the difference between these three types of radiation flux and utilizes polarization radiation to separate them from the apparent radiation of the vegetation canopy. Specifically, solar-induced chlorophyll fluorescence is extracted from vegetation canopy radiation data using standard Fraunhofer-line\n discrimination. The results show that polarization measurements can quantitatively separate Lvol, Lpol, and ChlF and extract the solar-induced chlorophyll fluorescence. This study improves our understanding of the light-scattering properties of vegetation canopies and\n provides insights for developing building models and research algorithms.","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inversion of Solar-Induced Chlorophyll Fluorescence Using Polarization Measurements of Vegetation\",\"authors\":\"Haiyan Yao, Ziying Li, Yang Han, Haofang Niu, Tianyi Hao, Yuyu Zhou\",\"doi\":\"10.14358/pers.87.5.331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In vegetation remote sensing, the apparent radiation of the vegetation canopy is often combined with three components derived from different parts of vegetation that have different production mechanisms and optical properties: volume scattering Lvol, polarized light Lpol,\\n and chlorophyll fluorescence ChlF. The chlorophyll fluorescence plays a very important role in vegetation remote sensing, and the polarization information in vegetation remote sensing has become an effective way to characterize the physical characteristics of vegetation. This study analyzes\\n the difference between these three types of radiation flux and utilizes polarization radiation to separate them from the apparent radiation of the vegetation canopy. Specifically, solar-induced chlorophyll fluorescence is extracted from vegetation canopy radiation data using standard Fraunhofer-line\\n discrimination. The results show that polarization measurements can quantitatively separate Lvol, Lpol, and ChlF and extract the solar-induced chlorophyll fluorescence. This study improves our understanding of the light-scattering properties of vegetation canopies and\\n provides insights for developing building models and research algorithms.\",\"PeriodicalId\":49702,\"journal\":{\"name\":\"Photogrammetric Engineering and Remote Sensing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Photogrammetric Engineering and Remote Sensing\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.14358/pers.87.5.331\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photogrammetric Engineering and Remote Sensing","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.14358/pers.87.5.331","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
Inversion of Solar-Induced Chlorophyll Fluorescence Using Polarization Measurements of Vegetation
In vegetation remote sensing, the apparent radiation of the vegetation canopy is often combined with three components derived from different parts of vegetation that have different production mechanisms and optical properties: volume scattering Lvol, polarized light Lpol,
and chlorophyll fluorescence ChlF. The chlorophyll fluorescence plays a very important role in vegetation remote sensing, and the polarization information in vegetation remote sensing has become an effective way to characterize the physical characteristics of vegetation. This study analyzes
the difference between these three types of radiation flux and utilizes polarization radiation to separate them from the apparent radiation of the vegetation canopy. Specifically, solar-induced chlorophyll fluorescence is extracted from vegetation canopy radiation data using standard Fraunhofer-line
discrimination. The results show that polarization measurements can quantitatively separate Lvol, Lpol, and ChlF and extract the solar-induced chlorophyll fluorescence. This study improves our understanding of the light-scattering properties of vegetation canopies and
provides insights for developing building models and research algorithms.
期刊介绍:
Photogrammetric Engineering & Remote Sensing commonly referred to as PE&RS, is the official journal of imaging and geospatial information science and technology. Included in the journal on a regular basis are highlight articles such as the popular columns “Grids & Datums” and “Mapping Matters” and peer reviewed technical papers.
We publish thousands of documents, reports, codes, and informational articles in and about the industries relating to Geospatial Sciences, Remote Sensing, Photogrammetry and other imaging sciences.