Guanhua Zhou , Chen Tian , Yaxin Han , Chunyue Niu , Haoyu Miao , Guifei Jing , Franz Pablo Antezana Lopez , Guangjian Yan , Hilana Saleh Mahmoud Najjar , Feng Zhao , Shubha Sathyendranath
{"title":"行水生植被的冠层反射率建模:AVRM 和 AVMC","authors":"Guanhua Zhou , Chen Tian , Yaxin Han , Chunyue Niu , Haoyu Miao , Guifei Jing , Franz Pablo Antezana Lopez , Guangjian Yan , Hilana Saleh Mahmoud Najjar , Feng Zhao , Shubha Sathyendranath","doi":"10.1016/j.rse.2024.114296","DOIUrl":null,"url":null,"abstract":"<div><p>Row aquatic vegetation is characterized by distinctive features as inundated habitats and individuals arranged in rows. However, current radiative transfer models have not yet taken into account both the water background and the row structure. To address this problem, we developed a hybrid radiative transfer and geometric optical model (Aquatic Vegetation Row Model, AVRM) for row vegetation and taken rice at early growth stages as a typical example. We verified the model through field experiment and an independently developed Monte Carlo simulation model (Aquatic Vegetation Row Monte Carlo model, AVMC), and found that they could better simulate the canopy reflectance characteristics of rice before canopy closure than existing models: PROSAIL model for uniform terrestrial vegetation, AVRT model for uniform aquatic vegetation, and Kimes model for row terrestrial vegetation, respectively. The effects of row structure, leaf area index, and water background on the bidirectional reflectance spectra of rice canopies were investigated. Our models could be used as virtual laboratory to simulate the reflectance characteristics of rice at early growth stages, which may benefit rice condition monitoring and growth management.</p></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":null,"pages":null},"PeriodicalIF":11.1000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Canopy reflectance modeling of row aquatic vegetation: AVRM and AVMC\",\"authors\":\"Guanhua Zhou , Chen Tian , Yaxin Han , Chunyue Niu , Haoyu Miao , Guifei Jing , Franz Pablo Antezana Lopez , Guangjian Yan , Hilana Saleh Mahmoud Najjar , Feng Zhao , Shubha Sathyendranath\",\"doi\":\"10.1016/j.rse.2024.114296\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Row aquatic vegetation is characterized by distinctive features as inundated habitats and individuals arranged in rows. However, current radiative transfer models have not yet taken into account both the water background and the row structure. To address this problem, we developed a hybrid radiative transfer and geometric optical model (Aquatic Vegetation Row Model, AVRM) for row vegetation and taken rice at early growth stages as a typical example. We verified the model through field experiment and an independently developed Monte Carlo simulation model (Aquatic Vegetation Row Monte Carlo model, AVMC), and found that they could better simulate the canopy reflectance characteristics of rice before canopy closure than existing models: PROSAIL model for uniform terrestrial vegetation, AVRT model for uniform aquatic vegetation, and Kimes model for row terrestrial vegetation, respectively. The effects of row structure, leaf area index, and water background on the bidirectional reflectance spectra of rice canopies were investigated. Our models could be used as virtual laboratory to simulate the reflectance characteristics of rice at early growth stages, which may benefit rice condition monitoring and growth management.</p></div>\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2024-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0034425724003146\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425724003146","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Canopy reflectance modeling of row aquatic vegetation: AVRM and AVMC
Row aquatic vegetation is characterized by distinctive features as inundated habitats and individuals arranged in rows. However, current radiative transfer models have not yet taken into account both the water background and the row structure. To address this problem, we developed a hybrid radiative transfer and geometric optical model (Aquatic Vegetation Row Model, AVRM) for row vegetation and taken rice at early growth stages as a typical example. We verified the model through field experiment and an independently developed Monte Carlo simulation model (Aquatic Vegetation Row Monte Carlo model, AVMC), and found that they could better simulate the canopy reflectance characteristics of rice before canopy closure than existing models: PROSAIL model for uniform terrestrial vegetation, AVRT model for uniform aquatic vegetation, and Kimes model for row terrestrial vegetation, respectively. The effects of row structure, leaf area index, and water background on the bidirectional reflectance spectra of rice canopies were investigated. Our models could be used as virtual laboratory to simulate the reflectance characteristics of rice at early growth stages, which may benefit rice condition monitoring and growth management.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.